Awesome Big Data
A curated list of awesome big data frameworks, resources and other
awesomeness. Inspired by
awesome-php,
awesome-python,
awesome-ruby,
hadoopecosystemtable
& big-data.
Your contributions are always welcome!
RDBMS
-
MySQL The world’s most popular open
source database.
-
PostgreSQL The world’s most
advanced open source database.
-
Oracle Database
- object-relational database management system.
-
Teradata
- high-performance MPP data warehouse platform.
Frameworks
-
Bistro -
general-purpose data processing engine for both batch and stream
analytics. It is based on a novel data model, which represents data via
functions and processes data via column operations as
opposed to having only set operations in conventional approaches like
MapReduce or SQL.
-
IBM Streams
- platform for distributed processing and real-time analytics.
Integrates with many of the popular technologies in the Big Data
ecosystem (Kafka, HDFS, Spark, etc.)
-
Apache Hadoop - framework for
distributed processing. Integrates MapReduce (parallel processing), YARN
(job scheduling) and HDFS (distributed file system).
-
Tigon - High Throughput
Real-time Stream Processing Framework.
-
Pachyderm - Pachyderm is a data
storage platform built on Docker and Kubernetes to provide reproducible
data processing and analysis.
-
Polyaxon - A platform
for reproducible and scalable machine learning and deep learning.
-
Smooks - An extensible
Java framework for building XML and non-XML (CSV, EDI, Java, etc…)
streaming applications.
Distributed Programming
-
AddThis Hydra -
distributed data processing and storage system originally developed at
AddThis.
-
AMPLab SIMR - run Spark
on Hadoop MapReduce v1.
-
Apache APEX - a unified,
enterprise platform for big data stream and batch processing.
-
Apache Beam - an unified model
and set of language-specific SDKs for defining and executing data
processing workflows.
-
Apache Crunch - a simple Java
API for tasks like joining and data aggregation that are tedious to
implement on plain MapReduce.
-
Apache DataFu
- collection of user-defined functions for Hadoop and Pig developed by
LinkedIn.
-
Apache Flink - high-performance
runtime, and automatic program optimization.
-
Apache Gearpump - real-time
big data streaming engine based on Akka.
-
Apache Gora - framework for
in-memory data model and persistence.
-
Apache Hama - BSP (Bulk
Synchronous Parallel) computing framework.
-
Apache MapReduce
- programming model for processing large data sets with a parallel,
distributed algorithm on a cluster.
-
Apache Pig - high level language
to express data analysis programs for Hadoop.
-
Apache REEF - retainable evaluator
execution framework to simplify and unify the lower layers of big data
systems.
-
Apache S4 -
framework for stream processing, implementation of S4.
-
Apache Spark - framework
for in-memory cluster computing.
-
Apache Spark Streaming
- framework for stream processing, part of Spark.
-
Apache Storm - framework for
stream processing by Twitter also on YARN.
-
Apache Samza - stream processing
framework, based on Kafka and YARN.
-
Apache Tez - application
framework for executing a complex DAG (directed acyclic graph) of tasks,
built on YARN.
-
Apache Twill
- abstraction over YARN that reduces the complexity of developing
distributed applications.
-
Baidu Bigflow - an
interface that allows for writing distributed computing programs
providing lots of simple, flexible, powerful APIs to easily handle data
of any scale.
-
Cascalog - data processing and
querying library.
-
Cheetah
- High Performance, Custom Data Warehouse on Top of MapReduce.
-
Concurrent Cascading - framework
for data management/analytics on Hadoop.
-
Damballa Parkour -
MapReduce library for Clojure.
-
Datasalt Pangool -
alternative MapReduce paradigm.
-
DataTorrent StrAM - real-time
engine is designed to enable distributed, asynchronous, real time
in-memory big-data computations in as unblocked a way as possible, with
minimal overhead and impact on performance.
-
Facebook Corona
- Hadoop enhancement which removes single point of failure.
-
Facebook Peregrine
- Map Reduce framework.
-
Facebook Scuba
- distributed in-memory datastore.
-
Google Dataflow
- create data pipelines to help themæingest, transform and analyze data.
-
Google MapReduce
- map reduce framework.
-
Google MillWheel
- fault tolerant stream processing framework.
-
IBM Streams
- platform for distributed processing and real-time analytics. Provides
toolkits for advanced analytics like geospatial, time series, etc. out
of the box.
-
JAQL - declarative
programming language for working with structured, semi-structured and
unstructured data.
-
Kite - is a set of
libraries, tools, examples, and documentation focused on making it
easier to build systems on top of the Hadoop ecosystem.
-
Metamarkets Druid - framework for
real-time analysis of large datasets.
-
Netflix PigPen -
map-reduce for Clojure which compiles to Apache Pig.
-
Nokia Disco - MapReduce framework
developed by Nokia.
-
Onyx - Distributed
computation for the cloud.
-
Pinterest Pinlater
- asynchronous job execution system.
-
Pydoop - Python MapReduce
and HDFS API for Hadoop.
-
Ray - A fast and simple
framework for building and running distributed applications.
-
Rackerlabs Blueflood - multi-tenant
distributed metric processing system
-
Skale - High
performance distributed data processing in NodeJS.
-
Stratosphere - general purpose
cluster computing framework.
-
Streamdrill - useful for counting
activities of event streams over different time windows and finding the
most active one.
-
streamsx.topology
- Libraries to enable building IBM Streams application in Java, Python
or Scala.
-
Tuktu -
Easy-to-use platform for batch and streaming computation, built using
Scala, Akka and Play!
-
Twitter Heron - Heron is
a realtime, distributed, fault-tolerant stream processing engine from
Twitter replacing Storm.
-
Twitter Scalding -
Scala library for Map Reduce jobs, built on Cascading.
-
Twitter Summingbird
- Streaming MapReduce with Scalding and Storm, by Twitter.
-
Twitter TSAR
- TimeSeries AggregatoR by Twitter.
-
Wallaroo - The
ultrafast and elastic data processing engine. Big or fast data - no
fuss, no Java needed.
Distributed Filesystem
Distributed Index
-
Pilosa Open source
distributed bitmap index that dramatically accelerates queries across
multiple, massive data sets.
Document Data Model
-
Actian Versant
- commercial object-oriented database management systems .
-
Crate Data - is an open source massively
scalable data store. It requires zero administration.
-
Facebook Apollo
- Facebook’s Paxos-like NoSQL database.
-
jumboDB - document
oriented datastore over Hadoop.
-
LinkedIn Espresso -
horizontally scalable document-oriented NoSQL data store.
-
MarkLogic - Schema-agnostic
Enterprise NoSQL database technology.
-
Microsoft Azure DocumentDB
- NoSQL cloud database service with protocol support for MongoDB
-
MongoDB - Document-oriented
database system.
-
RavenDB - A transactional,
open-source Document Database.
-
RethinkDB - document database that
supports queries like table joins and group by.
Key Map Data Model
Note: There is some term confusion in the industry, and
two different things are called “Columnar Databases”. Some, listed here,
are distributed, persistent databases built around the “key-map” data
model: all data has a (possibly composite) key, with which a map of
key-value pairs is associated. In some systems, multiple such value maps
can be associated with a key, and these maps are referred to as “column
families” (with value map keys being referred to as “columns”).
Another group of technologies that can also be called “columnar databases”
is distinguished by how it stores data, on disk or in memory – rather than
storing data the traditional way, where all column values for a given key
are stored next to each other, “row by row”, these systems store all
column values next to each other. So more work is needed to get
all columns for a given key, but less work is needed to get all values for
a given column.
The former group is referred to as “key map data model” here. The line
between these and the
Key-value Data Model stores is fairly
blurry.
The latter, being more about the storage format than about the data model,
is listed under Columnar Databases.
You can read more about this distinction on Prof. Daniel Abadi’s blog:
Distinguishing two major types of Column Stores.
-
Apache Accumulo - distributed
key/value store, built on Hadoop.
-
Apache Cassandra -
column-oriented distributed datastore, inspired by BigTable.
-
Apache HBase - column-oriented
distributed datastore, inspired by BigTable.
-
Baidu Tera - an
Internet-scale database, inspired by BigTable.
-
Facebook HydraBase
- evolution of HBase made by Facebook.
-
Google BigTable
- column-oriented distributed datastore.
-
Google Cloud Datastore
- is a fully managed, schemaless database for storing non-relational
data over BigTable.
-
Hypertable - column-oriented
distributed datastore, inspired by BigTable.
-
InfiniDB - is
accessed through a MySQL interface and use massive parallel processing
to parallelize queries.
-
Tephra - Transactions
for HBase.
-
Twitter Manhattan
- real-time, multi-tenant distributed database for Twitter scale.
-
ScyllaDB - column-oriented
distributed datastore written in C++, totally compatible with Apache
Cassandra.
Key-value Data Model
-
Aerospike - NoSQL
flash-optimized, in-memory. Open source and “Server code in ‘C’ (not
Java or Erlang) precisely tuned to avoid context switching and memory
copies.”
-
Amazon DynamoDB -
distributed key/value store, implementation of Dynamo paper.
-
Badger - a fast,
simple, efficient, and persistent key-value store written natively in
Go.
-
Bolt - an embedded
key-value database for Go.
-
BTDB - Key Value Database
in .Net with Object DB Layer, RPC, dynamic IL and much more
-
BuntDB - a fast,
embeddable, in-memory key/value database for Go with custom indexing and
geospatial support.
-
Edis - is a
protocol-compatible Server replacement for Redis.
-
ElephantDB -
Distributed database specialized in exporting data from Hadoop.
-
EventStore - distributed time
series database.
-
GhostDB - a
distributed, in-memory, general purpose key-value data store that
delivers microsecond performance at any scale.
-
Graviton - a
simple, fast, versioned, authenticated, embeddable key-value store
database in pure Go(lang).
-
GridDB - suitable
for sensor data stored in a timeseries.
-
HyperDex - a scalable,
next generation key-value and document store with a wide array of
features, including consistency, fault tolerance and high performance.
-
Ignite - is an
in-memory key-value data store providing full SQL-compliant data access
that can optionally be backed by disk storage.
-
LinkedIn Krati
- is a simple persistent data store with very low latency and high
throughput.
-
Linkedin Voldemort
- distributed key/value storage system.
-
Oracle NoSQL Database
- distributed key-value database by Oracle Corporation.
-
Redis - in memory key value datastore.
-
Riak - a decentralized
datastore.
-
Storehaus - library
to work with asynchronous key value stores, by Twitter.
-
SummitDB - an
in-memory, NoSQL key/value database, with disk persistance and using the
Raft consensus algorithm.
-
Tarantool - an
efficient NoSQL database and a Lua application server.
-
TiKV - a distributed
key-value database powered by Rust and inspired by Google Spanner and
HBase.
-
Tile38 - a geolocation
data store, spatial index, and realtime geofence, supporting a variety
of object types including latitude/longitude points, bounding boxes, XYZ
tiles, Geohashes, and GeoJSON
-
TreodeDB - key-value store
that’s replicated and sharded and provides atomic multirow writes.
Graph Data Model
-
AgensGraph - a new generation
multi-model graph database for the modern complex data environment.
-
Apache Giraph - implementation
of Pregel, based on Hadoop.
-
Apache Spark Bagel
- implementation of Pregel, part of Spark.
-
ArangoDB - multi model
distributed database.
-
DGraph - A scalable,
distributed, low latency, high throughput graph database aimed at
providing Google production level scale and throughput, with low enough
latency to be serving real time user queries, over terabytes of
structured data.
-
EliasDB - a lightweight
graph based database that does not require any third-party libraries.
-
Facebook TAO
- TAO is the distributed data store that is widely used at facebook to
store and serve the social graph.
-
GCHQ Gaffer - Gaffer by
GCHQ is a framework that makes it easy to store large-scale graphs in
which the nodes and edges have statistics.
-
Google Cayley -
open-source graph database.
-
Google Pregel
- graph processing framework.
-
GraphLab PowerGraph
- a core C++ GraphLab API and a collection of high-performance machine
learning and data mining toolkits built on top of the GraphLab API.
-
GraphX
- resilient Distributed Graph System on Spark.
-
Gremlin - graph
traversal Language.
-
Infovore -
RDF-centric Map/Reduce framework.
-
Intel GraphBuilder - tools to
construct large-scale graphs on top of Hadoop.
-
JanusGraph - open-source,
distributed graph database with multiple options for storage backends
(Bigtable, HBase, Cassandra, etc.) and indexing backends (Elasticsearch,
Solr, Lucene).
-
MapGraph -
Massively Parallel Graph processing on GPUs.
-
Microsoft Graph Engine
- a distributed in-memory data processing engine, underpinned by a
strongly-typed in-memory key-value store and a general distributed
computation engine.
-
Neo4j - graph database written entirely
in Java.
-
OrientDB - document and graph
database.
-
Phoebus - framework for
large scale graph processing.
-
Titan - distributed
graph database, built over Cassandra.
-
Twitter FlockDB
- distributed graph database.
-
NodeXL - A free, open-source
template for Microsoft® Excel® 2007, 2010, 2013 and 2016 that makes it
easy to explore network graphs.
Columnar Databases
Note please read the note on
Key-Map Data Model section.
-
Columnar Storage
- an explanation of what columnar storage is and when you might want it.
-
Actian Vector - column-oriented
analytic database.
-
ClickHouse - an open-source
column-oriented database management system that allows generating
analytical data reports in real time.
-
EventQL - a distributed,
column-oriented database built for large-scale event collection and
analytics.
-
MonetDB - column store database.
-
Parquet - columnar storage
format for Hadoop.
-
Pivotal Greenplum -
purpose-built, dedicated analytic data warehouse that offers a columnar
engine as well as a traditional row-based one.
-
Vertica - is designed to manage
large, fast-growing volumes of data and provide very fast query
performance when used for data warehouses.
-
SQream DB - A GPU powered big data
database, designed for analytics and data warehousing, with ANSI-92
compliant SQL, suitable for data sets from 10TB to 1PB.
-
Google BigQuery
- Google’s cloud offering backed by their pioneering work on Dremel.
-
Amazon Redshift -
Amazon’s cloud offering, also based on a columnar datastore backend.
-
IndexR - an open-source
columnar storage format for fast & realtime analytic with big data.
-
LocustDB - an
experimental analytics database aiming to set a new standard for query
performance on commodity hardware.
NewSQL Databases
-
Actian Ingres
- commercially supported, open-source SQL relational database management
system.
-
ActorDB - a distributed
SQL database with the scalability of a KV store, while keeping the query
capabilities of a relational database.
-
Amazon RedShift - data
warehouse service, based on PostgreSQL.
-
BayesDB - statistic
oriented SQL database.
-
Bedrock - a simple, modular,
networked and distributed transaction layer built atop SQLite.
-
CitusDB - scales out PostgreSQL
through sharding and replication.
-
Cockroach -
Scalable, Geo-Replicated, Transactional Datastore.
-
Comdb2 - a clustered
RDBMS built on optimistic concurrency control techniques.
-
Datomic - distributed database
designed to enable scalable, flexible and intelligent applications.
-
FoundationDB - distributed
database, inspired by F1.
-
Google F1 -
distributed SQL database built on Spanner.
-
Google Spanner
- globally distributed semi-relational database.
-
H-Store - is an experimental
main-memory, parallel database management system that is optimized for
on-line transaction processing (OLTP) applications.
-
Haeinsa - linearly
scalable multi-row, multi-table transaction library for HBase based on
Percolator.
-
HandlerSocket
- NoSQL plugin for MySQL/MariaDB.
-
InfiniSQL - infinity scalable
RDBMS.
-
KarelDB - a relational
database backed by Apache Kafka.
-
Map-D - GPU in-memory database, big
data analysis and visualization platform.
-
MemSQL - in memory SQL database
witho optimized columnar storage on flash.
-
NuoDB - SQL/ACID compliant
distributed database.
-
Oracle TimesTen in-Memory Database
- in-memory, relational database management system with persistence and
recoverability.
-
Pivotal GemFire XD
- Low-latency, in-memory, distributed SQL data store. Provides SQL
interface to in-memory table data, persistable in HDFS.
-
SAP HANA - is an
in-memory, column-oriented, relational database management system.
-
SenseiDB - distributed,
realtime, semi-structured database.
-
Sky - database used for flexible, high
performance analysis of behavioral data.
-
SymmetricDS - open source
software for both file and database synchronization.
-
TiDB - TiDB is a
distributed SQL database. Inspired by the design of Google F1.
-
VoltDB - claims to be fastest
in-memory database.
-
yugabyteDB - open
source, high-performance, distributed SQL database compatible with
PostgreSQL.
Time-Series Databases
-
Axibase Time Series Database
- Integrated time series database on top of HBase with built-in
visualization, rule-engine and SQL support.
-
Chronix - a time series storage built
to store time series highly compressed and for fast access times.
-
Cube - uses MongoDB to store
time series data.
-
Heroic - is a
scalable time series database based on Cassandra and Elasticsearch.
-
InfluxDB - a time series database with
optimised IO and queries, supports pgsql and influx wire protocols.
-
QuestDB - distributed time
series database.
-
IronDB - scalable,
general-purpose time series database.
-
Kairosdb - similar to
OpenTSDB but allows for Cassandra.
-
M3DB - a distributed time
series database that can be used for storing realtime metrics at long
retention.
-
Newts - a time series
database based on Apache Cassandra.
-
TDengine - a time
series database in C utilizing unique features of IoT to improve
read/write throughput and reduce space needed to store data
-
OpenTSDB - distributed time series
database on top of HBase.
-
Prometheus - a time series database
and service monitoring system.
-
Beringei -
Facebook’s in-memory time-series database.
-
TrailDB - an efficient tool for storing
and querying series of events.
-
Druid Column oriented
distributed data store ideal for powering interactive applications
-
Riak-TS Riak TS is the
only enterprise-grade NoSQL time series database optimized specifically
for IoT and Time Series data.
-
Akumuli Akumuli is a
numeric time-series database. It can be used to capture, store and
process time-series data in real-time. The word “akumuli” can be
translated from esperanto as “accumulate”.
-
Rhombus A time-series
object store for Cassandra that handles all the complexity of building
wide row indexes.
-
Dalmatiner DB
Fast distributed metrics database
-
Blueflood A
distributed system designed to ingest and process time series data
-
Timely
Timely is a time series database application that provides secure access
to time series data based on Accumulo and Grafana.
-
SiriDB
Highly-scalable, robust and fast, open source time series database with
cluster functionality.
-
Thanos - Thanos
is a set of components to create a highly available metric system with
unlimited storage capacity using multiple (existing) Prometheus
deployments.
-
VictoriaMetrics
- fast, scalable and resource-effective open-source TSDB compatible with
Prometheus. Single-node and cluster versions included
SQL-like processing
-
Actian SQL for Hadoop
- high performance interactive SQL access to all Hadoop data.
-
Apache Drill - framework for
interactive analysis, inspired by Dremel.
-
Apache HCatalog
- table and storage management layer for Hadoop.
-
Apache Hive - SQL-like data
warehouse system for Hadoop.
-
Apache Calcite - framework that
allows efficient translation of queries involving heterogeneous and
federated data.
-
Apache Phoenix - SQL
skin over HBase.
-
Aster Database
- SQL-like analytic processing for MapReduce.
-
Cloudera Impala
- framework for interactive analysis, Inspired by Dremel.
-
Concurrent Lingual
- SQL-like query language for Cascading.
-
Datasalt Splout SQL
- full SQL query engine for big datasets.
-
Dremio - an open-source, SQL-like
Data-as-a-Service Platform based on Apache Arrow.
-
Facebook PrestoDB - distributed SQL
query engine.
-
Google BigQuery
- framework for interactive analysis, implementation of Dremel.
-
Materialize
- is a streaming database for real-time applications using SQL for
queries and supporting a large fraction of PostgreSQL.
-
Invantive SQL
- SQL engine for online and on-premise use with integrated local data
replication and 70+ connectors.
-
PipelineDB - an open-source
relational database that runs SQL queries continuously on streams,
incrementally storing results in tables.
-
Pivotal HDB - SQL-like data
warehouse system for Hadoop.
-
RainstorDB
- database for storing petabyte-scale volumes of structured and
semi-structured data.
-
Spark Catalyst
- is a Query Optimization Framework for Spark and Shark.
-
SparkSQL
- Manipulating Structured Data Using Spark.
-
Splice Machine - a
full-featured SQL-on-Hadoop RDBMS with ACID transactions.
-
Stinger -
interactive query for Hive.
-
Tajo - distributed data warehouse
system on Hadoop.
-
Trafodion
- enterprise-class SQL-on-HBase solution targeting big data
transactional or operational workloads.
Data Ingestion
-
redpanda - A Kafka®
replacement for mission critical systems; 10x faster. Written in C++.
-
Amazon Kinesis - real-time
processing of streaming data at massive scale.
-
Amazon Web Services Glue -
serverless fully managed extract, transform, and load (ETL) service
-
Census - A reverse ETL product that
let you sync data from your data warehouse to SaaS Applications. No
engineering favors required—just SQL.
-
Apache Chukwa - data collection
system.
-
Apache Flume - service to manage
large amount of log data.
-
Apache Kafka - distributed
publish-subscribe messaging system.
-
Apache NiFi - Apache NiFi is an
integrated data logistics platform for automating the movement of data
between disparate systems.
-
Apache Pulsar - a
distributed pub-sub messaging platform with a very flexible messaging
model and an intuitive client API.
-
Apache Sqoop - tool to transfer
data between Hadoop and a structured datastore.
-
Embulk - open-source bulk data
loader that helps data transfer between various databases, storages,
file formats, and cloud services.
-
Facebook Scribe
- streamed log data aggregator.
-
Fluentd - tool to collect events
and logs.
-
Gazette - Distributed
streaming infrastructure built on cloud storage which makes it easy to
mix and match batch and streaming paradigms.
-
Google Photon
- geographically distributed system for joining multiple continuously
flowing streams of data in real-time with high scalability and low
latency.
-
Heka - open
source stream processing software system.
-
HIHO - framework for
connecting disparate data sources with Hadoop.
-
Kestrel -
distributed message queue system.
-
LinkedIn Databus -
stream of change capture events for a database.
-
LinkedIn Kamikaze -
utility package for compressing sorted integer arrays.
-
LinkedIn White Elephant
- log aggregator and dashboard.
-
Logstash - a tool
for managing events and logs.
-
Netflix Suro - log
agregattor like Storm and Samza based on Chukwa.
-
Pinterest Secor - is a
service implementing Kafka log persistance.
-
Linkedin Gobblin -
linkedin’s universal data ingestion framework.
-
Skizze - sketch data
store to deal with all problems around counting and sketching using
probabilistic data-structures.
-
StreamSets Data Collector
- continuous big data ingest infrastructure with a simple to use IDE.
-
Alooma - data
pipeline as a service enabling moving data sources such as MySQL into
data warehouses.
-
RudderStack -
an open source customer data infrastructure (segment, mParticle
alternative) written in go.
Service Programming
-
Akka Toolkit - runtime for distributed,
and fault tolerant event-driven applications on the JVM.
-
Apache Avro - data serialization
system.
-
Apache Curator - Java libaries
for Apache ZooKeeper.
-
Apache Karaf - OSGi runtime that
runs on top of any OSGi framework.
-
Apache Thrift - framework to
build binary protocols.
-
Apache Zookeeper -
centralized service for process management.
-
Google Chubby
- a lock service for loosely-coupled distributed systems.
-
Hydrosphere Mist -
a service for exposing Apache Spark analytics jobs and machine learning
models as realtime, batch or reactive web services.
-
Linkedin Norbert -
cluster manager.
-
Mara - A
lightweight opinionated ETL framework, halfway between plain scripts and
Apache Airflow
-
OpenMPI - message passing
framework.
-
Serf - decentralized solution for
service discovery and orchestration.
-
Spotify Luigi - a Python
package for building complex pipelines of batch jobs. It handles
dependency resolution, workflow management, visualization, handling
failures, command line integration, and much more.
-
Spring XD -
distributed and extensible system for data ingestion, real time
analytics, batch processing, and data export.
-
Twitter Elephant Bird
- libraries for working with LZOP-compressed data.
-
Twitter Finagle -
asynchronous network stack for the JVM.
Scheduling
-
Apache Airflow
- a platform to programmatically author, schedule and monitor workflows.
-
Apache Aurora - is a service
scheduler that runs on top of Apache Mesos.
-
Apache Falcon - data management
framework.
-
Apache Oozie - workflow job
scheduler.
-
Azure Data Factory
- cloud-based pipeline orchestration for on-prem, cloud and HDInsight
-
Chronos - distributed and
fault-tolerant scheduler.
-
Cronicle -
Distributed, easy to install, NodeJS based, task scheduler
-
Dagster - a data
orchestrator for machine learning, analytics, and ETL.
-
Linkedin Azkaban - batch
workflow job scheduler.
-
Schedoscope -
Scala DSL for agile scheduling of Hadoop jobs.
-
Sparrow - scheduling
platform.
Machine Learning
-
Azure ML Studio - Cloud-based
AzureML, R, Python Machine Learning platform
-
brain - Neural networks
in JavaScript.
-
Oryx - Lambda
architecture on Apache Spark, Apache Kafka for real-time large scale
machine learning.
-
Concurrent Pattern
- machine learning library for Cascading.
-
convnetjs - Deep
Learning in Javascript. Train Convolutional Neural Networks (or ordinary
ones) in your browser.
-
DataVec - A
vectorization and data preprocessing library for deep learning in Java
and Scala. Part of the Deeplearning4j ecosystem.
-
Deeplearning4j - Fast,
open deep learning for the JVM (Java, Scala, Clojure). A neural network
configuration layer powered by a C++ library. Uses Spark and Hadoop to
train nets on multiple GPUs and CPUs.
-
Decider - Flexible
and Extensible Machine Learning in Ruby.
-
ENCOG - machine
learning framework that supports a variety of advanced algorithms, as
well as support classes to normalize and process data.
-
etcML - text classification with
machine learning.
-
Etsy Conjecture -
scalable Machine Learning in Scalding.
-
Feast - A feature store for
the management, discovery, and access of machine learning features.
Feast provides a consistent view of feature data for both model training
and model serving.
-
GraphLab Create - A
machine learning platform in Python with a broad collection of ML
toolkits, data engineering, and deployment tools.
-
H2O - statistical, machine
learning and math runtime with Hadoop. R and Python.
-
Karate Club
- An unsupervised machine learning library for graph structured data.
Python
-
Keras - An intuitive
neural net API inspired by Torch that runs atop Theano and Tensorflow.
-
Lambdo - Lambdo is a
workflow engine which significantly simplifies the analysis process by
unifying feature engineering and machine learning operations.
-
Little Ball of Fur
- A subsampling library for graph structured data. Python
-
Mahout - An Apache-backed
machine learning library for Hadoop.
-
MLbase - distributed machine
learning libraries for the BDAS stack.
-
MLPNeuralNet
- Fast multilayer perceptron neural network library for iOS and Mac OS
X.
-
ML Workspace -
All-in-one web-based IDE specialized for machine learning and data
science.
-
MOA - MOA performs big data
stream mining in real time, and large scale machine learning.
-
MonkeyLearn - Text mining made
easy. Extract and classify data from text.
-
ND4J - A matrix
library for the JVM. Numpy for Java.
-
nupic - Numenta Platform
for Intelligent Computing: a brain-inspired machine intelligence
platform, and biologically accurate neural network based on cortical
learning algorithms.
-
PredictionIO
- machine learning server buit on Hadoop, Mahout and Cascading.
-
PyTorch Geometric Temporal
- a temporal extension library for PyTorch Geometric .
-
RL4J -
Reinforcement learning for Java and Scala. Includes Deep-Q learning and
A3C algorithms, and integrates with Open AI’s Gym. Runs in the
Deeplearning4j ecosystem.
-
SAMOA - distributed
streaming machine learning framework.
-
scikit-learn
- scikit-learn: machine learning in Python.
-
Shapley - A
data-driven framework to quantify the value of classifiers in a machine
learning ensemble.
-
Spark MLlib
- a Spark implementation of some common machine learning (ML)
functionality.
-
Sibyl
- System for Large Scale Machine Learning at Google.
-
TensorFlow -
Library from Google for machine learning using data flow graphs.
-
Theano - A Python-focused
machine learning library supported by the University of Montreal.
-
Torch - A deep learning library
with a Lua API, supported by NYU and Facebook.
-
Velox - System
for serving machine learning predictions.
-
Vowpal Wabbit
- learning system sponsored by Microsoft and Yahoo!.
-
WEKA - suite of
machine learning software.
-
BidMach - CPU and
GPU-accelerated Machine Learning Library.
Benchmarking
Security
-
Apache Ranger - Central security
admin & fine-grained authorization for Hadoop
-
Apache Eagle - real time
monitoring solution
-
Apache Knox Gateway - single point
of secure access for Hadoop clusters.
-
Apache Sentry
- security module for data stored in Hadoop.
-
BDA - The vulnerability
detector for Hadoop and Spark
System Deployment
-
Apache Ambari - operational
framework for Hadoop mangement.
-
Apache Bigtop - system
deployment framework for the Hadoop ecosystem.
-
Apache Helix - cluster management
framework.
-
Apache Mesos - cluster manager.
-
Apache Slider -
is a YARN application to deploy existing distributed applications on
YARN.
-
Apache Whirr - set of libraries
for running cloud services.
-
Apache YARN - Cluster
manager.
-
Brooklyn - library that
simplifies application deployment and management.
-
Buildoop - Similar to Apache
BigTop based on Groovy language.
-
Cloudera HUE - web application for
interacting with Hadoop.
-
Facebook Prism
- multi datacenters replication system.
-
Google Borg
- job scheduling and monitoring system.
-
Google Omega -
job scheduling and monitoring system.
-
Hortonworks HOYA
- application that can deploy HBase cluster on YARN.
-
Kubernetes - a system for
automating deployment, scaling, and management of containerized
applications.
-
Marathon - Mesos
framework for long-running services.
-
Linkis - Linkis
helps easily connect to various back-end computation/storage engines.
Applications
-
411 - an web application for
alert management resulting from scheduled searches into Elasticsearch.
-
Adobe spindle -
Next-generation web analytics processing with Scala, Spark, and Parquet.
-
Apache Metron - a platform that
integrates a variety of open source big data technologies in order to
offer a centralized tool for security monitoring and analysis.
-
Apache Nutch - open source web
crawler.
-
Apache OODT - capturing,
processing and sharing of data for NASA’s scientific archives.
-
Apache Tika - content analysis
toolkit.
-
Argus - Time series
monitoring and alerting platform.
-
AthenaX - a streaming
analytics platform that enables users to run production-quality, large
scale streaming analytics using Structured Query Language (SQL).
-
Atlas - a backend for
managing dimensional time series data.
-
Countly - open source mobile and web
analytics platform, based on Node.js & MongoDB.
-
Domino - Run, scale, share,
and deploy models — without any infrastructure.
-
Eclipse BIRT - Eclipse-based
reporting system.
-
ElastAert - ElastAlert
is a simple framework for alerting on anomalies, spikes, or other
patterns of interest from data in ElasticSearch.
-
Eventhub - open
source event analytics platform.
-
HASH - open source simulation and
visualization platform.
-
Hermes - asynchronous
message broker built on top of Kafka.
-
Hunk -
Splunk analytics for Hadoop.
-
Imhotep - Large
scale analytics platform by indeed.
-
Indicative - Web & mobile
analytics tool, with data warehouse (AWS, BigQuery) integration.
-
Jupyter - Notebook and project
application for interactive data science and scientific computing across
all programming languages.
-
MADlib -
data-processing library of an RDBMS to analyze data.
-
Kapacitor - an
open source framework for processing, monitoring, and alerting on time
series data.
-
Kylin - open source Distributed
Analytics Engine from eBay.
-
PivotalR - R
on Pivotal HD / HAWQ and PostgreSQL.
-
Rakam - open-source
real-time custom analytics platform powered by Postgresql, Kinesis and
PrestoDB.
-
Qubole - auto-scaling Hadoop
cluster, built-in data connectors.
-
SnappyData - a
distributed in-memory data store for real-time operational analytics,
delivering stream analytics, OLTP (online transaction processing) and
OLAP (online analytical processing) built on Spark in a single
integrated cluster.
-
Snowplow -
enterprise-strength web and event analytics, powered by Hadoop, Kinesis,
Redshift and Postgres.
-
SparkR - R
frontend for Spark.
-
Splunk - analyzer for
machine-generated data.
-
Sumo Logic - cloud based
analyzer for machine-generated data.
-
Talend - unified
open source environment for YARN, Hadoop, HBASE, Hive, HCatalog &
Pig.
Search engine and framework
-
Apache Lucene - Search engine
library.
-
Apache Solr - Search
platform for Apache Lucene.
-
Elassandra - is a
fork of Elasticsearch modified to run on top of Apache Cassandra in a
scalable and resilient peer-to-peer architecture.
-
ElasticSearch - Search and
analytics engine based on Apache Lucene.
-
Enigma.io – Freemium robust web
application for exploring, filtering, analyzing, searching and exporting
massive datasets scraped from across the Web.
-
Google Caffeine
- continuous indexing system.
-
Google Percolator
- continuous indexing system.
-
HBase Coprocessor
- implementation of Percolator, part of HBase.
-
Lily HBase Indexer
- quickly and easily search for any content stored in HBase.
-
LinkedIn Bobo - is a
Faceted Search implementation written purely in Java, an extension to
Apache Lucene.
-
LinkedIn Cleo - is a
flexible software library for enabling rapid development of partial,
out-of-order and real-time typeahead search.
-
LinkedIn Galene
- search architecture at LinkedIn.
-
LinkedIn Zoie - is a
realtime search/indexing system written in Java.
-
MG4J - MG4J (Managing Gigabytes
for Java) is a full-text search engine for large document collections
written in Java. It is highly customisable, high-performance and
provides state-of-the-art features and new research algorithms.
-
Sphinx Search Server - fulltext
search engine.
-
Vespa - is an engine for low-latency
computation over large data sets. It stores and indexes your data such
that queries, selection and processing over the data can be performed at
serving time.
-
Facebook Faiss -
is a library for efficient similarity search and clustering of dense
vectors. It contains algorithms that search in sets of vectors of any
size, up to ones that possibly do not fit in RAM. It also contains
supporting code for evaluation and parameter tuning. Faiss is written in
C++ with complete wrappers for Python/numpy.
-
Annoy - is a C++ library
with Python bindings to search for points in space that are close to a
given query point. It also creates large read-only file-based data
structures that are mmapped into memory so that many processes may share
the same data.
-
Weaviate -
Weaviate is a GraphQL-based semantic search engine with build-in (word)
embeddings.
MySQL forks and evolutions
-
Amazon RDS - MySQL databases
in Amazon’s cloud.
-
Drizzle - evolution of MySQL 6.0.
-
Google Cloud SQL -
MySQL databases in Google’s cloud.
-
MariaDB - enhanced, drop-in
replacement for MySQL.
-
MySQL Cluster -
MySQL implementation using NDB Cluster storage engine.
-
Percona Server
- enhanced, drop-in replacement for MySQL.
-
ProxySQL - High
Performance Proxy for MySQL.
-
TokuDB - TokuDB is a storage
engine for MySQL and MariaDB.
-
WebScaleSQL - is a collaboration
among engineers from several companies that face similar challenges in
running MySQL at scale.
PostgreSQL forks and evolutions
-
HadoopDB -
hybrid of MapReduce and DBMS.
-
IBM Netezza -
high-performance data warehouse appliances.
-
Postgres-XL - Scalable Open
Source PostgreSQL-based Database Cluster.
-
RecDB - Open
Source Recommendation Engine Built Entirely Inside PostgreSQL.
-
Stado - open source
MPP database system solely targeted at data warehousing and data mart
applications.
-
Yahoo Everest
- multi-peta-byte database / MPP derived by PostgreSQL.
-
TimescaleDB - An open-source
time-series database optimized for fast ingest and complex queries
-
PipelineDB - The Streaming SQL
Database. An open-source relational database that runs SQL queries
continuously on streams, incrementally storing results in tables
Memcached forks and evolutions
Embedded Databases
-
Actian PSQL
- ACID-compliant DBMS developed by Pervasive Software, optimized for
embedding in applications.
-
BerkeleyDB
- a software library that provides a high-performance embedded database
for key/value data.
-
HanoiDB - Erlang
LSM BTree Storage.
-
LevelDB - a fast
key-value storage library written at Google that provides an ordered
mapping from string keys to string values.
-
LMDB - ultra-fast, ultra-compact
key-value embedded data store developed by Symas.
-
RocksDB - embeddable persistent
key-value store for fast storage based on LevelDB.
Business Intelligence
-
BIME Analytics -
business intelligence platform in the cloud.
-
Blazer - business
intelligence made simple.
-
Chartio - lean business intelligence
platform to visualize and explore your data.
-
Count - notebook-based anlytics and
visualisation platform using SQL or drag-and-drop.
-
datapine - self-service business
intelligence tool in the cloud.
-
Dekart - Large scale geospatial
analytics for Google BigQuery based on Kepler.gl.
-
GoodData - platform for data
products and embedded analytics.
-
Jaspersoft - powerful business
intelligence suite.
-
Jedox Palo - customisable
Business Intelligence platform.
-
Jethrodata - Interactive Big Data
Analytics.
-
intermix.io - Performance Monitoring
for Amazon Redshift
-
Metabase - The
simplest, fastest way to get business intelligence and analytics to
everyone in your company.
-
Microsoft
- business intelligence software and platform.
-
Microstrategy - software
platforms for business intelligence, mobile intelligence, and network
applications.
-
Numeracy - Fast, clean SQL client and
business intelligence.
-
Pentaho - business intelligence
platform.
-
Qlik - business intelligence and
analytics platform.
-
Redash - Open source business
intelligence platform, supporting multiple data sources and planned
queries.
-
Saiku Analytics - Open source
analytics platform.
-
Knowage - open source
business intelligence platform. (former
SpagoBi)
-
SparklineData SNAP - modern B.I
platform powered by Apache Spark.
-
Tableau - business intelligence
platform.
-
Zoomdata - Big Data Analytics.
Data Visualization
-
Airpal - Web UI for
PrestoDB.
-
AnyChart - fast, simple and
flexible JavaScript (HTML5) charting library featuring pure JS API.
-
Arbor - graph
visualization library using web workers and jQuery.
-
Banana - visualize
logs and time-stamped data stored in Solr. Port of Kibana.
-
Bloomery - Web UI for
Impala.
-
Bokeh - A powerful
Python interactive visualization library that targets modern web
browsers for presentation, with the goal of providing elegant, concise
construction of novel graphics in the style of D3.js, but also
delivering this capability with high-performance interactivity over very
large or streaming datasets.
-
C3 - D3-based reusable chart library
-
CartoDB - open-source
or freemium hosting for geospatial databases with powerful front-end
editing capabilities and a robust API.
-
chartd - responsive, retina-compatible
charts with just an img tag.
-
Chart.js - open source HTML5
Charts visualizations.
-
Chartist.js -
another open source HTML5 Charts visualization.
-
Crossfilter -
JavaScript library for exploring large multivariate datasets in the
browser. Works well with dc.js and d3.js.
-
Cubism - JavaScript
library for time series visualization.
-
Cytoscape - JavaScript library
for visualizing complex networks.
-
DC.js - Dimensional charting
built to work natively with crossfilter rendered using d3.js. Excellent
for connecting charts/additional metadata to hover events in D3.
-
D3 - javaScript library for manipulating
documents.
-
D3.compose - Compose
complex, data-driven visualizations from reusable charts and components.
-
D3Plus - A fairly robust set of reusable
charts and styles for d3.js.
-
Dash - Analytical Web Apps
for Python, R, Julia, and Jupyter. Built on top of plotly, no JS
required
-
Dekart - Large scale geospatial
analytics for Google BigQuery based on Kepler.gl.
-
DevExtreme React Chart
- High-performance plugin-based React chart for Bootstrap and Material
Design.
-
Echarts - Baidus
enterprise charts.
-
Envisionjs -
dynamic HTML5 visualization.
-
FnordMetric - write SQL queries
that return SVG charts rather than tables
-
Frappe Charts - GitHub-inspired
simple and modern SVG charts for the web with zero dependencies.
-
Freeboard - pen
source real-time dashboard builder for IOT and other web mashups.
-
Gephi - An award-winning
open-source platform for visualizing and manipulating large graphs and
network connections. It’s like Photoshop, but for graphs. Available for
Windows and Mac OS X.
-
Google Charts -
simple charting API.
-
Grafana - graphite dashboard
frontend, editor and graph composer.
-
Graphite - scalable Realtime
Graphing.
-
Highcharts - simple and
flexible charting API.
-
IPython - provides a rich architecture
for interactive computing.
-
Kibana - visualize
logs and time-stamped data
-
Lumify - open source big data analysis
and visualization platform
-
Matplotlib -
plotting with Python.
-
Metricsgraphic.js - a
library built on top of D3 that is optimized for time-series data
- NVD3 - chart components for d3.js.
-
Peity - Progressive
SVG bar, line and pie charts.
-
Plot.ly - Easy-to-use web service that
allows for rapid creation of complex charts, from heatmaps to
histograms. Upload data to create and style charts with Plotly’s online
spreadsheet. Fork others’ plots.
-
Plotly.js The open
source javascript graphing library that powers plotly.
-
Recline - simple but
powerful library for building data applications in pure Javascript and
HTML.
-
Redash - open-source
platform to query and visualize data.
-
ReCharts - A composable charting
library built on React components
-
Shiny - a web application
framework for R.
-
Sigma.js - JavaScript
library dedicated to graph drawing.
-
Superset - a
data exploration platform designed to be visual, intuitive and
interactive, making it easy to slice, dice and visualize data and
perform analytics at the speed of thought.
-
Vega - a visualization
grammar.
-
Zeppelin - a
notebook-style collaborative data analysis.
-
Zing Charts - JavaScript
charting library for big data.
-
DataSphere Studio
- one-stop data application development management portal.
Internet of things and sensor data
-
Apache Edgent (Incubating) - a
programming model and micro-kernel style runtime that can be embedded in
gateways and small footprint edge devices enabling local, real-time,
analytics on the edge devices.
-
Azure IoT Hub
- Cloud-based bi-directional monitoring and messaging hub
-
TempoIQ - Cloud-based sensor
analytics.
-
2lemetry - Platform for Internet of
things.
-
Pubnub - Data stream network
-
ThingWorx - Rapid development
and connection of intelligent systems
- IFTTT - If this then that
-
Evrything- Making products smart
-
NetLytics -
Analytics platform to process network data on Spark.
Interesting Readings
-
Big Data Benchmark
- Benchmark of Redshift, Hive, Shark, Impala and Stiger/Tez.
-
NoSQL Comparison
- Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase vs Couchbase
vs Neo4j vs Hypertable vs ElasticSearch vs Accumulo vs VoltDB vs
Scalaris comparison.
-
Monitoring Kafka performance
- Guide to monitoring Apache Kafka, including native methods for metrics
collection.
-
Monitoring Hadoop performance
- Guide to monitoring Hadoop, with an overview of Hadoop architecture,
and native methods for metrics collection.
-
Monitoring Cassandra performance
- Guide to monitoring Cassandra, including native methods for metrics
collection.
Interesting Papers
2015 - 2016
-
2015 -
Facebook - One Trillion Edges: Graph Processing at
Facebook-Scale.
2013 - 2014
-
2014 -
Stanford - Mining of Massive Datasets.
-
2013
- AMPLab - Presto: Distributed Machine Learning and
Graph Processing with Sparse Matrices.
-
2013
- AMPLab - MLbase: A Distributed Machine-learning
System.
-
2013
- AMPLab - Shark: SQL and Rich Analytics at Scale.
-
2013
- AMPLab - GraphX: A Resilient Distributed Graph System
on Spark.
-
2013
- Google - HyperLogLog in Practice: Algorithmic
Engineering of a State of The Art Cardinality Estimation Algorithm.
-
2013
- Microsoft - Scalable Progressive Analytics on Big
Data in the Cloud.
-
2013 -
Metamarkets - Druid: A Real-time Analytical Data Store.
-
2013
- Google - Online, Asynchronous Schema Change in F1.
-
2013
- Google - F1: A Distributed SQL Database That Scales.
-
2013
- Google - MillWheel: Fault-Tolerant Stream Processing
at Internet Scale.
-
2013
- Facebook - Scuba: Diving into Data at Facebook.
-
2013
- Facebook - Unicorn: A System for Searching the Social
Graph.
-
2013
- Facebook - Scaling Memcache at Facebook.
2011 - 2012
-
2012
- Twitter - The Unified Logging Infrastructure for Data
Analytics at Twitter.
-
2012
- AMPLab - Blink and It’s Done: Interactive Queries on
Very Large Data.
-
2012
- AMPLab - Fast and Interactive Analytics over Hadoop
Data with Spark.
-
2012
- AMPLab - Shark: Fast Data Analysis Using
Coarse-grained Distributed Memory.
-
2012
- Microsoft - Paxos Replicated State Machines as the
Basis of a High-Performance Data Store.
-
2012
- Microsoft - Paxos Made Parallel.
-
2012 -
AMPLab - BlinkDB: Queries with Bounded Errors and
Bounded Response Times on Very Large Data.
-
2012
- Google - Processing a trillion cells per mouse click.
-
2012
- Google - Spanner: Google’s Globally-Distributed
Database.
-
2011
- AMPLab - Scarlett: Coping with Skewed Popularity
Content in MapReduce Clusters.
-
2011
- AMPLab - Mesos: A Platform for Fine-Grained Resource
Sharing in the Data Center.
-
2011
- Google - Megastore: Providing Scalable, Highly
Available Storage for Interactive Services.
2001 - 2010
-
2010
- Facebook - Finding a needle in Haystack: Facebook’s
photo storage.
-
2010
- AMPLab - Spark: Cluster Computing with Working Sets.
-
2010 -
Google - Pregel: A System for Large-Scale Graph
Processing.
-
2010
- Google - Large-scale Incremental Processing Using
Distributed Transactions and Notifications base of Percolator and
Caffeine.
-
2010
- Google - Dremel: Interactive Analysis of Web-Scale
Datasets.
-
2010 - Yahoo -
S4: Distributed Stream Computing Platform.
-
2009 -
HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for
Analytical Workloads.
-
2008
- AMPLab - Chukwa: A large-scale monitoring system.
-
2007
- Amazon - Dynamo: Amazon’s Highly Available Key-value
Store.
-
2006
- Google - The Chubby lock service for loosely-coupled
distributed systems.
-
2006
- Google - Bigtable: A Distributed Storage System for
Structured Data.
-
2004
- Google - MapReduce: Simplied Data Processing on Large
Clusters.
-
2003
- Google - The Google File System.
Videos
-
Spark in Motion
- Spark in Motion teaches you how to use Spark for batch and streaming
data analytics.
-
Machine Learning, Data Science and Deep Learning with Python
- LiveVideo tutorial that covers machine learning, Tensorflow,
artificial intelligence, and neural networks.
-
Data warehouse schema design - dimensional modeling and star
schema
- Introduction to schema design for data warehouse using the star schema
method.
-
Elasticsearch 7 and Elastic Stack
- LiveVideo tutorial that covers searching, analyzing, and visualizing
big data on a cluster with Elasticsearch, Logstash, Beats, Kibana, and
more.
Books
Streaming
-
Data Science at Scale with Python and Dask
- Data Science at Scale with Python and Dask teaches you how to build
distributed data projects that can handle huge amounts of data.
-
Streaming Data
- Streaming Data introduces the concepts and requirements of streaming
and real-time data systems.
-
Storm Applied
- Storm Applied is a practical guide to using Apache Storm for the
real-world tasks associated with processing and analyzing real-time data
streams.
-
Fundamentals of Stream Processing: Application Design, Systems, and
Analytics
- This comprehensive, hands-on guide combining the fundamental building
blocks and emerging research in stream processing is ideal for
application designers, system builders, analytic developers, as well as
students and researchers in the field.
-
Stream Data Processing: A Quality of Service Perspective
- Presents a new paradigm suitable for stream and complex event
processing.
-
Unified Log Processing
- Unified Log Processing is a practical guide to implementing a unified
log of event streams (Kafka or Kinesis) in your business
-
Kafka Streams in Action
- Kafka Streams in Action teaches you everything you need to know to
implement stream processing on data flowing into your Kafka platform,
allowing you to focus on getting more from your data without sacrificing
time or effort.
-
Big Data - Big Data
teaches you to build big data systems using an architecture that takes
advantage of clustered hardware along with new tools designed
specifically to capture and analyze web-scale data.
-
Spark in Action
&
Spark in Action 2nd Ed.
- Spark in Action teaches you the theory and skills you need to
effectively handle batch and streaming data using Spark. Fully updated
for Spark 2.0.
-
Kafka in Action
- Kafka in Action is a fast-paced introduction to every aspect of
working with Kafka you need to really reap its benefits.
-
Fusion in Action
- Fusion in Action teaches you to build a full-featured data analytics
pipeline, including document and data search and distributed data
clustering.
-
Reactive Data Handling
- Reactive Data Handling is a collection of five hand-picked chapters,
selected by Manuel Bernhardt, that introduce you to building reactive
applications capable of handling real-time processing with large data
loads–free eBook!
-
Azure Data Engineering
- A book about data engineering in general and the Azure platform
specifically
-
Grokking Streaming Systems
- Grokking Streaming Systems helps you unravel what streaming systems
are, how they work, and whether they’re right for your business. Written
to be tool-agnostic, you’ll be able to apply what you learn no matter
which framework you choose.
Distributed systems
Graph Based approach
Data Visualization
Other Awesome Lists