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data-engineering-collection
A collection of awesome software, libraries, Learning Tutorials, documents, books, resources and interesting stuff about Big Data Science & Engineering
https://github.com/exajobs/data-engineering-collection
Last synced: about 12 hours ago
JSON representation
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`RDBMS `
- PostgreSQL
- MySQL
- Teradata - high-performance MPP data warehouse platform.
- Oracle Database - object-relational database management system.
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`Distributed Programming `
- 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 Gearpump - real-time big data streaming engine based on Akka.
- 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 Spark Streaming - framework for stream processing, part of Spark.
- 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.
- 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.
- Google MapReduce - map reduce framework.
- Google MillWheel - fault tolerant stream processing framework.
- Kite - is a set of libraries, tools, examples, and documentation focused on making it easier to build systems on top of the Hadoop ecosystem.
- Nokia Disco - MapReduce framework developed by Nokia.
- Pinterest Pinlater - asynchronous job execution system.
- Rackerlabs Blueflood - multi-tenant distributed metric processing system
- Stratosphere - general purpose cluster computing framework.
- Streamdrill - useful for counting activities of event streams over different time windows and finding the most active one.
- Wallaroo - The ultrafast and elastic data processing engine. Big or fast data - no fuss, no Java needed.
- Google Dataflow - create data pipelines to help themæingest, transform and analyze data.
- Twitter TSAR - TimeSeries AggregatoR by Twitter.
- Facebook Peregrine - Map Reduce framework.
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`Distributed Filesystem `
- BeeGFS - formerly FhGFS, parallel distributed file system.
- Google Megastore - scalable, highly available storage.
- GridGain - GGFS, Hadoop compliant in-memory file system.
- Microsoft Azure Data Lake Store - HDFS-compatible storage in Azure cloud
- Quantcast File System QFS - open-source distributed file system.
- Tahoe-LAFS - decentralized cloud storage system.
- Google GFS - distributed filesystem.
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`Document Data Model `
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`Key Map Data Model `
- Distinguishing two major types of Column Stores
- Google BigTable - column-oriented distributed datastore.
- Google Cloud Datastore - is a fully managed, schemaless database for storing non-relational data over BigTable.
- Twitter Manhattan - real-time, multi-tenant distributed database for Twitter scale.
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Key-value Data Model
- Badger - a fast, simple, efficient, and persistent key-value store written natively in Go.
- 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.
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Graph Data Model
- GraphX - resilient Distributed Graph System on Spark.
- MapGraph - Massively Parallel Graph processing on GPUs.
- NodeXL - A free, open-source template for Microsoft® Excel® 2007, 2010, 2013 and 2016 that makes it easy to explore network graphs.
- Titan - distributed graph database, built over Cassandra.
- Google Pregel - graph processing framework.
- AgensGraph - a new generation multi-model graph database for the modern complex data environment.
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Databases
- Riak
- Cassandra Calculator
- HBase
- Couchbase
- Titan - machine cluster.
- Apache Geode - memory database for scale-out applications.
- TimescaleDB - series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.
- AWS DynamoDB - digit millisecond latency at any scale.
- Redis - value cache and store.
- RavenDB
- Neo4j
- RethinkDB - source database for the realtime web.
- Percona XtraBackup
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`Columnar Databases`
- MonetDB - column store database.
- Vertica - is designed to manage large, fast-growing volumes of data and provide very fast query performance when used for data warehouses.
- EventQL - a distributed, column-oriented database built for large-scale event collection and analytics.
- Amazon Redshift - Amazon's cloud offering, also based on a columnar datastore backend.
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`NewSQL Databases`
- CitusDB - scales out PostgreSQL through sharding and replication.
- Google F1 - distributed SQL database built on Spanner.
- Google Spanner - globally distributed semi-relational database.
- InfiniSQL - infinity scalable RDBMS.
- Map-D - GPU in-memory database, big data analysis and visualization platform.
- 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.
- Sky - database used for flexible, high performance analysis of behavioral data.
- Sky - database used for flexible, high performance analysis of behavioral data.
- FoundationDB - distributed database, inspired by F1.
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Time-Series Databases
- Axibase Time Series Database - Integrated time series database on top of HBase with built-in visualization, rule-engine and SQL support.
- InfluxDB - a time series database with optimised IO and queries, supports pgsql and influx wire protocols.
- M3DB - a distributed time series database that can be used for storing realtime metrics at long retention.
- Prometheus - a time series database and service monitoring system.
- Rhombus - series object store for Cassandra that handles all the complexity of building wide row indexes.
- QuestDB - high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability.
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SQL-like processing
- Actian SQL for Hadoop - high performance interactive SQL access to all Hadoop data.
- Apache HCatalog - table and storage management layer for Hadoop.
- Aster Database - SQL-like analytic processing for MapReduce.
- 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.
- Spark Catalyst - is a Query Optimization Framework for Spark and Shark.
- Splice Machine - a full-featured SQL-on-Hadoop RDBMS with ACID transactions.
- Trafodion - enterprise-class SQL-on-HBase solution targeting big data transactional or operational workloads.
- Cloudera Impala - framework for interactive analysis, Inspired by Dremel.
- Datasalt Splout SQL - full SQL query engine for big datasets.
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Data Ingestion
- Amazon Kinesis - real-time processing of streaming data at massive scale.
- Amazon Web Services Glue - serverless fully managed extract, transform, and load (ETL) service
- Apache NiFi - Apache NiFi is an integrated data logistics platform for automating the movement of data between disparate systems.
- Google Photon - geographically distributed system for joining multiple continuously flowing streams of data in real-time with high scalability and low latency.
- Kestrel - distributed message queue system.
- 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.
- redpanda - A Kafka® replacement for mission critical systems; 10x faster. Written in C++.
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Service Programming
- Google Chubby - a lock service for loosely-coupled distributed systems.
- OpenMPI - message passing framework.
- Serf - decentralized solution for service discovery and orchestration.
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Scheduling
- Linkedin Azkaban - batch workflow job scheduler.
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Machine Learning
- Azure ML Studio - Cloud-based AzureML, R, Python Machine Learning platform
- 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.
- etcML - text classification with machine learning.
- GraphLab Create - A machine learning platform in Python with a broad collection of ML toolkits, data engineering, and deployment tools.
- MLbase - distributed machine learning libraries for the BDAS stack.
- MonkeyLearn - Text mining made easy. Extract and classify data from text.
- ND4J - A matrix library for the JVM. Numpy for Java.
- 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.
- Sibyl - System for Large Scale Machine Learning at Google.
- 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.
- WEKA - suite of machine learning software.
- WEKA - suite of machine learning software.
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Benchmarking
- PUMA Benchmarking - benchmark suite for MapReduce applications.
- Yahoo Gridmix3 - Hadoop cluster benchmarking from Yahoo engineer team.
- Deeplearning4j Benchmarks
- Apache Hadoop Benchmarking - micro-benchmarks for testing Hadoop performances.
- Berkeley SWIM Benchmark - real-world big data workload benchmark.
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System Deployment
- Brooklyn - library that simplifies application deployment and management.
- Buildoop - Similar to Apache BigTop based on Groovy language.
- Google Borg - job scheduling and monitoring system.
- Google Omega - job scheduling and monitoring system.
- Kubernetes - a system for automating deployment, scaling, and management of containerized applications.
- Apache YARN - Cluster manager.
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Applications
- Apache Tika - content analysis toolkit.
- Qubole - auto-scaling Hadoop cluster, built-in data connectors.
- 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.
- 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.
- PivotalR - R on Pivotal HD / HAWQ and PostgreSQL.
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Search engine and framework
- Enigma.io
- Google Percolator - continuous indexing system.
- Lily HBase Indexer - quickly and easily search for any content stored in HBase.
- LinkedIn Galene - search architecture at LinkedIn.
- Sphinx Search Server - fulltext search engine.
- ElasticSearch - Search and analytics engine based on Apache Lucene.
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MySQL forks and evolutions
- Drizzle - evolution of MySQL 6.0.
- Google Cloud SQL - MySQL databases in Google's cloud.
- MySQL Cluster - MySQL implementation using NDB Cluster storage engine.
- 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.
- Amazon RDS - MySQL databases in Amazon's cloud.
- MariaDB - enhanced, drop-in replacement for MySQL.
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PostgreSQL forks and evolutions
- 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.
- Postgres-XL - Scalable Open Source PostgreSQL-based Database Cluster.
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Embedded Databases
- LMDB - ultra-fast, ultra-compact key-value embedded data store developed by Symas.
- Actian PSQL - ACID-compliant DBMS developed by Pervasive Software, optimized for embedding in applications.
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Business Intelligence
- BIME Analytics - business intelligence platform in the cloud.
- GoodData - platform for data products and embedded analytics.
- Jaspersoft - powerful business intelligence suite.
- Jedox Palo - customisable Business Intelligence platform.
- Jethrodata - Interactive Big Data Analytics.
- Microstrategy - software platforms for business intelligence, mobile intelligence, and network applications.
- 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](http://www.spagobi.org/))
- SparklineData SNAP - modern B.I platform powered by Apache Spark.
- Tableau - business intelligence platform.
- Dekart - Large scale geospatial analytics for Google BigQuery based on Kepler.gl.
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Data Visualization
- chartd - responsive, retina-compatible charts with just an img tag.
- D3 - javaScript library for manipulating documents.
- DevExtreme React Chart - High-performance plugin-based React chart for Bootstrap and Material Design.
- FnordMetric - write SQL queries that return SVG charts rather than tables
- Grafana - graphite dashboard frontend, editor and graph composer.
- Graphite - scalable Realtime Graphing.
- Highcharts - simple and flexible charting API.
- Metricsgraphic.js - a library built on top of D3 that is optimized for time-series data
- Zing Charts - JavaScript charting library for big data.
- Lumify - open source big data analysis and visualization platform
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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.
- TempoIQ - Cloud-based sensor analytics.
- Pubnub - Data stream network
- IFTTT - If this then that
- Evrything - Making products smart
- Ably - Pub/sub messaging platform for IoT
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Interesting Readings
- Big Data Benchmark - Benchmark of Redshift, Hive, Shark, Impala and Stiger/Tez.
- Monitoring Cassandra performance - Guide to monitoring Cassandra, including native methods for metrics collection.
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Interesting Papers
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2015 - 2016
- 2015 - **Facebook** - One Trillion Edges: Graph Processing at Facebook-Scale.
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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 - **Metamarkets** - Druid: A Real-time Analytical Data Store.
- 2013 - **Google** - F1: A Distributed SQL Database That Scales.
- 2013 - **Facebook** - Scaling Memcache at Facebook.
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2011 - 2012
- 2012 - **Twitter** - The Unified Logging Infrastructure
- 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 - **AMPLab** - BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data.
- 2012 - **Google** - Processing a trillion cells per mouse click.
- 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.
- 2012 - **AMPLab** - Blink and It’s Done: Interactive Queries on Very Large Data.
- 2012 - **Google** - Spanner: Google’s Globally-Distributed Database.
- 2012 - **AMPLab** - BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data.
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2001 - 2010
- 2010 - **AMPLab** - Spark: Cluster Computing with Working Sets.
- 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.
- 2006 - **Google** - The Chubby lock service for loosely-coupled distributed systems.
- 2004 - **Google** - MapReduce: Simplied Data Processing on Large Clusters.
- 2010 - **Facebook** - Finding a needle in Haystack: Facebook’s photo storage.
- 2010 - **Google** - Large-scale Incremental Processing Using Distributed Transactions and Notifications base of Percolator and Caffeine.
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Videos
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2001 - 2010
- 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.
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Books
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2001 - 2010
- 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 - in-action-second-edition) - 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!
- Distributed Systems for fun and profit
- Graph-Powered Machine Learning - Alessandro Negro. Combine graph theory and models to improve machine learning projects
- 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.
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Data Visualization
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Contributing
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`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.
Categories
Interesting Papers
30
`Distributed Programming `
23
Books
21
Machine Learning
14
Business Intelligence
13
Databases
13
SQL-like processing
11
Applications
11
Data Visualization
10
`NewSQL Databases`
10
Data Ingestion
8
`Distributed Filesystem `
7
MySQL forks and evolutions
7
Graph Data Model
6
System Deployment
6
Time-Series Databases
6
Internet of things and sensor data
6
Search engine and framework
6
Benchmarking
5
`Key Map Data Model `
4
PostgreSQL forks and evolutions
4
`Columnar Databases`
4
Key-value Data Model
4
Videos
4
`RDBMS `
4
Service Programming
3
`Document Data Model `
2
License
2
Embedded Databases
2
Interesting Readings
2
`Frameworks `
1
Scheduling
1
Sub Categories