MySQL
The world's most popular open source database.
A curated list of awesome big data frameworks, ressources and other awesomeness.
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
The world's most advanced open source database.
object-relational database management system.
high-performance MPP data warehouse platform.
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.
platform for distributed processing and real-time analytics. Integrates with many of the popular technologies in the Big Data ecosystem (Kafka, HDFS, Spark, etc.)
framework for distributed processing. Integrates MapReduce (parallel processing), YARN (job scheduling) and HDFS (distributed file system).
High Throughput Real-time Stream Processing Framework.
Kubernetes-native stream processing platform.
Pachyderm is a data storage platform built on Docker and Kubernetes to provide reproducible data processing and analysis.
A platform for reproducible and scalable machine learning and deep learning.
An extensible Java framework for building XML and non-XML (CSV, EDI, Java, etc...) streaming applications.
distributed data processing and storage system originally developed at AddThis.
run Spark on Hadoop MapReduce v1.
a unified, enterprise platform for big data stream and batch processing.
an unified model and set of language-specific SDKs for defining and executing data processing workflows.
a simple Java API for tasks like joining and data aggregation that are tedious to implement on plain MapReduce.
collection of user-defined functions for Hadoop and Pig developed by LinkedIn.
high-performance runtime, and automatic program optimization.
real-time big data streaming engine based on Akka.
framework for in-memory data model and persistence.
BSP (Bulk Synchronous Parallel) computing framework.
programming model for processing large data sets with a parallel, distributed algorithm on a cluster.
high level language to express data analysis programs for Hadoop.
retainable evaluator execution framework to simplify and unify the lower layers of big data systems.
framework for stream processing, implementation of S4.
framework for in-memory cluster computing.
framework for stream processing, part of Spark.
framework for stream processing by Twitter also on YARN.
stream processing framework, based on Kafka and YARN.
application framework for executing a complex DAG (directed acyclic graph) of tasks, built on YARN.
abstraction over YARN that reduces the complexity of developing distributed applications.
an interface that allows for writing distributed computing programs providing lots of simple, flexible, powerful APIs to easily handle data of any scale.
data processing and querying library.
High Performance, Custom Data Warehouse on Top of MapReduce.
framework for data management/analytics on Hadoop.
MapReduce library for Clojure.
alternative MapReduce paradigm.
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.
Hadoop enhancement which removes single point of failure.
Map Reduce framework.
distributed in-memory datastore.
create data pipelines to help them ingest, transform and analyze data.
map reduce framework.
fault tolerant stream processing framework.
platform for distributed processing and real-time analytics. Integrates with many of the popular technologies in the Big Data ecosystem (Kafka, HDFS, Spark, etc.)
declarative programming language for working with structured, semi-structured and unstructured data.
is a set of libraries, tools, examples, and documentation focused on making it easier to build systems on top of the Hadoop ecosystem.
framework for real-time analysis of large datasets.
map-reduce for Clojure which compiles to Apache Pig.
MapReduce framework developed by Nokia.
Distributed computation for the cloud.
asynchronous job execution system.
Python MapReduce and HDFS API for Hadoop.
multi-tenant distributed metric processing system
High performance distributed data processing in NodeJS.
general purpose cluster computing framework.
useful for counting activities of event streams over different time windows and finding the most active one.
Libraries to enable building IBM Streams application in Java, Python or Scala.
Easy-to-use platform for batch and streaming computation, built using Scala, Akka and Play!
Heron is a realtime, distributed, fault-tolerant stream processing engine from Twitter replacing Storm.
Scala library for Map Reduce jobs, built on Cascading.
Streaming MapReduce with Scalding and Storm, by Twitter.
TimeSeries AggregatoR by Twitter.
The ultrafast and elastic data processing engine. Big or fast data - no fuss, no Java needed.
a distributed object store that supports storage of trillion of small immutable objects as well as billions of large objects.
framework for distributed processing. Integrates MapReduce (parallel processing), YARN (job scheduling) and HDFS (distributed file system).
Hadoop's storage layer to enable fast analytics on fast data.
formerly FhGFS, parallel distributed file system.
software storage platform designed.
distributed filesystem.
object storage system.
distributed filesystem.
scalable, highly available storage.
GGFS, Hadoop compliant in-memory file system.
high-performance distributed filesystem.
HDFS-compatible storage in Azure cloud
open-source distributed file system.
scale-out network-attached storage file system.
simple and highly scalable distributed file system.
reliable file sharing at memory speed across cluster frameworks.
decentralized cloud storage system.
distributed filesystem.
Open source distributed bitmap index that dramatically accelerates queries across multiple, massive data sets.
commercial object-oriented database management systems .
is an open source massively scalable data store. It requires zero administration.
Facebook’s Paxos-like NoSQL database.
document oriented datastore over Hadoop.
horizontally scalable document-oriented NoSQL data store.
Schema-agnostic Enterprise NoSQL database technology.
NoSQL cloud database service with protocol support for MongoDB
A transactional, open-source Document Database.
document database that supports queries like table joins and group by.
distributed key/value store, built on Hadoop.
column-oriented distributed datastore, inspired by BigTable.
column-oriented distributed datastore, inspired by BigTable.
an Internet-scale database, inspired by BigTable.
evolution of HBase made by Facebook.
column-oriented distributed datastore.
is a fully managed, schemaless database for storing non-relational data over BigTable.
column-oriented distributed datastore, inspired by BigTable.
is accessed through a MySQL interface and use massive parallel processing to parallelize queries.
Transactions for HBase.
real-time, multi-tenant distributed database for Twitter scale.
column-oriented distributed datastore written in C++, totally compatible with Apache Cassandra.
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."
distributed key/value store, implementation of Dynamo paper.
a fast, simple, efficient, and persistent key-value store written natively in Go.
Key Value Database in .Net with Object DB Layer, RPC, dynamic IL and much more
a fast, embeddable, in-memory key/value database for Go with custom indexing and geospatial support.
is a protocol-compatible Server replacement for Redis.
Distributed database specialized in exporting data from Hadoop.
distributed time series database.
a distributed, in-memory, general purpose key-value data store that delivers microsecond performance at any scale.
a simple, fast, versioned, authenticated, embeddable key-value store database in pure Go(lang).
suitable for sensor data stored in a timeseries.
a scalable, next generation key-value and document store with a wide array of features, including consistency, fault tolerance and high performance.
is an in-memory key-value data store providing full SQL-compliant data access that can optionally be backed by disk storage.
is a simple persistent data store with very low latency and high throughput.
distributed key/value storage system.
distributed key-value database by Oracle Corporation.
a decentralized datastore.
library to work with asynchronous key value stores, by Twitter.
an in-memory, NoSQL key/value database, with disk persistence and using the Raft consensus algorithm.
an efficient NoSQL database and a Lua application server.
a distributed key-value database powered by Rust and inspired by Google Spanner and HBase.
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
key-value store that's replicated and sharded and provides atomic multirow writes.
a database for user interactions (likes, views, follows) with precomputed reads, supports HBase.
transactional graph database based on PostgreSQL.
multi-model database with graph, document, key-value, time-series and vector support.
implementation of Pregel, part of Spark.
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.
a lightweight graph based database that does not require any third-party libraries.
TAO is the distributed data store that is widely used at Facebook to store and serve the social graph.
Gaffer by GCHQ is a framework that makes it easy to store large-scale graphs in which the nodes and edges have statistics.
open-source graph database.
graph processing framework.
resilient Distributed Graph System on Spark.
graph traversal Language.
RDF-centric Map/Reduce framework.
open-source, distributed graph database with multiple options for storage backends (Bigtable, HBase, Cassandra, etc.) and indexing backends (Elasticsearch, Solr, Lucene).
a distributed in-memory data processing engine, underpinned by a strongly-typed in-memory key-value store and a general distributed computation engine.
distributed graph database for large-scale graphs with low-latency queries.
document and graph database.
framework for large scale graph processing.
distributed graph database, built over Cassandra.
an explanation of what columnar storage is and when you might want it.
column-oriented analytic database.
an open-source column-oriented database management system that allows generating analytical data reports in real time.
a distributed, column-oriented database built for large-scale event collection and analytics.
column store database.
columnar storage format for Hadoop.
purpose-built, dedicated analytic data warehouse that offers a columnar engine as well as a traditional row-based one.
is designed to manage large, fast-growing volumes of data and provide very fast query performance when used for data warehouses.
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's cloud offering backed by their pioneering work on Dremel.
Amazon's cloud offering, also based on a columnar datastore backend.
an open-source columnar storage format for fast & realtime analytic with big data.
an experimental analytics database aiming to set a new standard for query performance on commodity hardware.
commercially supported, open-source SQL relational database management system.
a distributed SQL database with the scalability of a KV store, while keeping the query capabilities of a relational database.
data warehouse service, based on PostgreSQL.
statistic oriented SQL database.
a simple, modular, networked and distributed transaction layer built atop SQLite.
scales out PostgreSQL through sharding and replication.
a clustered RDBMS built on optimistic concurrency control techniques.
distributed database designed to enable scalable, flexible and intelligent applications.
distributed database, inspired by F1.
distributed SQL database built on Spanner.
globally distributed semi-relational database.
is an experimental main-memory, parallel database management system that is optimized for on-line transaction processing (OLTP) applications.
linearly scalable multi-row, multi-table transaction library for HBase based on Percolator.
NoSQL plugin for MySQL/MariaDB.
infinity scalable RDBMS.
a relational database backed by Apache Kafka.
GPU in-memory database, big data analysis and visualization platform.
in memory SQL database witho optimized columnar storage on flash.
SQL/ACID compliant distributed database.
in-memory, relational database management system with persistence and recoverability.
Low-latency, in-memory, distributed SQL data store. Provides SQL interface to in-memory table data, persistable in HDFS.
is an in-memory, column-oriented, relational database management system.
distributed, realtime, semi-structured database.
database used for flexible, high performance analysis of behavioral data.
open source software for both file and database synchronization.
claims to be fastest in-memory database.
open source, high-performance, distributed SQL database compatible with PostgreSQL.
Integrated time series database on top of HBase with built-in visualization, rule-engine and SQL support.
a time series storage built to store time series highly compressed and for fast access times.
uses MongoDB to store time series data.
is a scalable time series database based on Cassandra and Elasticsearch.
a time series database with optimised IO and queries, supports pgsql and influx wire protocols.
high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability.
scalable, general-purpose time series database.
similar to OpenTSDB but allows for Cassandra.
a distributed time series database that can be used for storing realtime metrics at long retention.
a time series database based on Apache Cassandra.
open-source time-series database with high-performance ingestion, SQL support, and IoT-oriented storage.
distributed time series database on top of HBase.
a time series database and service monitoring system.
Facebook's in-memory time-series database.
an efficient tool for storing and querying series of events.
Column oriented distributed data store ideal for powering interactive applications
Riak TS is the only enterprise-grade NoSQL time series database optimized specifically for IoT and Time Series data.
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".
A time-series object store for Cassandra that handles all the complexity of building wide row indexes.
Fast distributed metrics database
A distributed system designed to ingest and process time series data
Timely is a time series database application that provides secure access to time series data based on Accumulo and Grafana.
Highly-scalable, robust and fast, open source time series database with cluster functionality.
Thanos is a set of components to create a highly available metric system with unlimited storage capacity using multiple (existing) Prometheus deployments.
fast, scalable and resource-effective open-source TSDB compatible with Prometheus. Single-node and cluster versions included
open data lakehouse platform and table format for high-throughput incremental data pipelines.
open table format for huge analytic datasets with schema evolution, hidden partitioning, and time travel.
lake format for building real-time lakehouse architectures with Flink and Spark.
incubating Apache project for interoperability across lakehouse table formats.
open-source storage framework for building lakehouse architectures on data lakes.
high performance interactive SQL access to all Hadoop data.
real-time analytical database for high-concurrency SQL analytics, search, and warehousing.
framework for interactive analysis, inspired by Dremel.
table and storage management layer for Hadoop.
SQL-like data warehouse system for Hadoop.
framework that allows efficient translation of queries involving heterogeneous and federated data.
SQL skin over HBase.
SQL-like analytic processing for MapReduce.
in-process OLAP SQL engine powered by ClickHouse, callable from Python with native pandas/Arrow DataFrame interop.
framework for interactive analysis, Inspired by Dremel.
SQL-like query language for Cascading.
full SQL query engine for big datasets.
an open-source, SQL-like Data-as-a-Service Platform based on Apache Arrow.
in-process analytical SQL database for local analytics over files, data lakes, and data frames.
distributed SQL query engine.
framework for interactive analysis, implementation of Dremel.
is a streaming database for real-time applications using SQL for queries and supporting a large fraction of PostgreSQL.
SQL engine for online and on-premise use with integrated local data replication and 70+ connectors.
an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.
SQL-like data warehouse system for Hadoop.
managed lakehouse query service using DuckDB over Apache Iceberg tables on object storage.
database for storing petabyte-scale volumes of structured and semi-structured data.
is a Query Optimization Framework for Spark and Shark.
Manipulating Structured Data Using Spark.
a full-featured SQL-on-Hadoop RDBMS with ACID transactions.
high-performance MPP SQL engine for real-time analytics and lakehouse queries.
interactive query for Hive.
distributed data warehouse system on Hadoop.
enterprise-class SQL-on-HBase solution targeting big data transactional or operational workloads.
open-source embedding database for AI applications.
AI-native database for hybrid vector, sparse vector, tensor, full-text, and structured search.
open-source embedded vector database built on the Lance columnar format.
vector database and similarity search engine with REST, gRPC, and client SDKs.
open-source vector database for semantic search with structured filtering.
A Kafka® replacement for mission critical systems; 10x faster. Written in C++.
open-source data movement platform for ELT pipelines and connector-based replication.
real-time processing of streaming data at massive scale.
serverless fully managed extract, transform, and load (ETL) service
data collection system.
service to manage large amount of log data.
distributed publish-subscribe messaging system.
Apache NiFi is an integrated data logistics platform for automating the movement of data between disparate systems.
a distributed pub-sub messaging platform with a very flexible messaging model and an intuitive client API.
high-performance, distributed data integration platform for batch and streaming synchronization.
tool to transfer data between Hadoop and a structured datastore.
end-to-end data pipeline tool combining ingestion, transformations, and data quality checks.
A reverse ETL product that let you sync data from your data warehouse to SaaS Applications. No engineering favors required—just SQL.
managed cloud object storage transfers for data ingestion workflows.
self-hosted CDC replication and database migration tool.
open-source distributed platform for change data capture.
open-source visual ETL/ELT platform built on DuckDB with connectors, data quality checks, and lineage.
open-source bulk data loader that helps data transfer between various databases, storages, file formats, and cloud services.
SaaS platform based on Gazette with plug-and-play connectors.
streamed log data aggregator.
streaming data integration tool powered by Apache Flink.
tool to collect events and logs.
Distributed streaming infrastructure built on cloud storage which makes it easy to mix and match batch and streaming paradigms.
geographically distributed system for joining multiple continuously flowing streams of data in real-time with high scalability and low latency.
log management platform for collecting, storing, searching, and alerting on machine data.
open source stream processing software system.
managed data pipeline platform for moving data from databases, SaaS apps, cloud storage, SDKs, and streaming services.
reverse ETL platform for syncing warehouse data into business applications.
framework for connecting disparate data sources with Hadoop.
distributed message queue system.
horizontally scalable document-oriented NoSQL data store.
utility package for compressing sorted integer arrays.
log aggregator and dashboard.
lightweight shipper for system and service metrics.
log agregattor like Storm and Samza based on Chukwa.
is a service implementing Kafka log persistance.
linkedin's universal data ingestion framework.
sketch data store to deal with all problems around counting and sketching using probabilistic data-structures.
continuous big data ingest infrastructure with a simple to use IDE.
data pipeline as a service enabling moving data sources such as MySQL into data warehouses.
an open source customer data infrastructure (segment, mParticle alternative) written in go.
open-source data observability for monitoring data journeys, data quality, and pipeline events.
open-source framework for validating, documenting, and testing data quality.
open standard and reference implementation for collecting lineage metadata from data pipelines.
open-source Python library and CLI for data quality tests.
runtime for distributed, and fault tolerant event-driven applications on the JVM.
data serialization system.
Java libraries for Apache ZooKeeper.
OSGi runtime that runs on top of any OSGi framework.
framework to build binary protocols.
centralized service for process management.
a lock service for loosely-coupled distributed systems.
a service for exposing Apache Spark analytics jobs and machine learning models as realtime, batch or reactive web services.
horizontally scalable document-oriented NoSQL data store.
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
message passing framework.
decentralized solution for service discovery and orchestration.
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.
distributed and extensible system for data ingestion, real time analytics, batch processing, and data export.
libraries for working with LZOP-compressed data.
asynchronous network stack for the JVM.
a platform to programmatically author, schedule and monitor workflows.
is a service scheduler that runs on top of Apache Mesos.
data management framework.
workflow job scheduler.
cloud-based pipeline orchestration for on-prem, cloud and HDInsight
distributed and fault-tolerant scheduler.
Distributed, easy to install, NodeJS based, task scheduler
batch workflow job scheduler.
Scala DSL for agile scheduling of Hadoop jobs.
scheduling platform.
Cloud-based AzureML, R, Python Machine Learning platform
Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning.
machine learning library for Cascading.
Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.
A vectorization and data preprocessing library for deep learning in Java and Scala. Part of the Deeplearning4j ecosystem.
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.
Flexible and Extensible Machine Learning in Ruby.
machine learning framework that supports a variety of advanced algorithms, as well as support classes to normalize and process data.
text classification with machine learning.
scalable Machine Learning in Scalding.
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.
A machine learning platform in Python with a broad collection of ML toolkits, data engineering, and deployment tools.
distributed Spark and Scala implementation of isolation forest for unsupervised outlier detection.
An unsupervised machine learning library for graph structured data. Python
An intuitive neural net API inspired by Torch that runs atop Theano and Tensorflow.
Lambdo is a workflow engine which significantly simplifies the analysis process by unifying feature engineering and machine learning operations.
A subsampling library for graph structured data. Python
An Apache-backed machine learning library for Hadoop.
distributed machine learning libraries for the BDAS stack.
Fast multilayer perceptron neural network library for iOS and Mac OS X.
All-in-one web-based IDE specialized for machine learning and data science.
MOA performs big data stream mining in real time, and large scale machine learning.
Text mining made easy. Extract and classify data from text.
A matrix library for the JVM. Numpy for Java.
experiment tracking and model registry for research and production machine learning teams.
Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.
machine learning server built on Hadoop, Mahout and Cascading.
a temporal extension library for PyTorch Geometric .
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.
distributed streaming machine learning framework.
scikit-learn: machine learning in Python.
A data-driven framework to quantify the value of classifiers in a machine learning ensemble.
a Spark implementation of some common machine learning (ML) functionality.
System for Large Scale Machine Learning at Google.
Library from Google for machine learning using data flow graphs.
A Python-focused machine learning library supported by the University of Montreal.
A deep learning library with a Lua API, supported by NYU and Facebook.
System for serving machine learning predictions.
learning system sponsored by Microsoft and Yahoo!.
suite of machine learning software.
CPU and GPU-accelerated Machine Learning Library.
load testing tool for measuring performance of services and distributed systems.
real-world big data workload benchmark.
reproducible, vendor-neutral data warehouse benchmark.
a Hadoop benchmark suite.
benchmark suite for MapReduce applications.
Hadoop cluster benchmarking from Yahoo engineer team.
extended Yahoo Cloud Serving Benchmark for NoSQL databases.
Central security admin & fine-grained authorization for Hadoop
real time monitoring solution
single point of secure access for Hadoop clusters.
security module for data stored in Hadoop.
The vulnerability detector for Hadoop and Spark
zero-knowledge encrypted file transfer for sharing large datasets.
operational framework for Hadoop management.
system deployment framework for the Hadoop ecosystem.
cluster management framework.
cluster manager.
is a YARN application to deploy existing distributed applications on YARN.
set of libraries for running cloud services.
Cluster manager.
library that simplifies application deployment and management.
Similar to Apache BigTop based on Groovy language.
web application for interacting with Hadoop.
multi datacenters replication system.
job scheduling and monitoring system.
job scheduling and monitoring system.
application that can deploy HBase cluster on YARN.
a system for automating deployment, scaling, and management of containerized applications.
Mesos framework for long-running services.
Linkis helps easily connect to various back-end computation/storage engines.
an web application for alert management resulting from scheduled searches into Elasticsearch.
Next-generation web analytics processing with Scala, Spark, and Parquet.
a platform that integrates a variety of open source big data technologies in order to offer a centralized tool for security monitoring and analysis.
open source web crawler.
capturing, processing and sharing of data for NASA's scientific archives.
content analysis toolkit.
Time series monitoring and alerting platform.
a streaming analytics platform that enables users to run production-quality, large scale streaming analytics using Structured Query Language (SQL).
a backend for managing dimensional time series data.
Comet provides an end-to-end model evaluation platform for AI developers, with best in class LLM evaluations, experiment tracking, and production monitoring.
Eclipse-based reporting system.
ElastAlert is a simple framework for alerting on anomalies, spikes, or other patterns of interest from data in ElasticSearch.
open source event analytics platform.
cloud spreadsheet for exploring and analyzing large datasets.
open source simulation and visualization platform.
asynchronous message broker built on top of Kafka.
Splunk analytics for Hadoop.
Web & mobile analytics tool, with data warehouse (AWS, BigQuery) integration.
Notebook and project application for interactive data science and scientific computing across all programming languages.
data-processing library of an RDBMS to analyze data.
an open source framework for processing, monitoring, and alerting on time series data.
open source Distributed Analytics Engine from eBay.
R on Pivotal HD / HAWQ and PostgreSQL.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
open-source real-time custom analytics platform powered by Postgresql, Kinesis and PrestoDB.
auto-scaling Hadoop cluster, built-in data connectors.
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.
enterprise-strength web and event analytics, powered by Hadoop, Kinesis, Redshift and Postgres.
R frontend for Spark.
analyzer for machine-generated data.
cloud based analyzer for machine-generated data.
Substation is a cloud native data pipeline and transformation toolkit written in Go.
unified open source environment for YARN, Hadoop, HBASE, Hive, HCatalog & Pig.
Search engine library.
Search platform for Apache Lucene.
is a fork of Elasticsearch modified to run on top of Apache Cassandra in a scalable and resilient peer-to-peer architecture.
Search and analytics engine based on Apache Lucene.
Freemium robust web application for exploring, filtering, analyzing, searching and exporting massive datasets scraped from across the Web.
continuous indexing system.
continuous indexing system.
implementation of Percolator, part of HBase.
quickly and easily search for any content stored in HBase.
is a Faceted Search implementation written purely in Java, an extension to Apache Lucene.
is a flexible software library for enabling rapid development of partial, out-of-order and real-time typeahead search.
search architecture at LinkedIn.
is a realtime search/indexing system written in Java.
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.
fulltext search engine.
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.
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…
MySQL databases in Amazon's cloud.
evolution of MySQL 6.0.
MySQL databases in Google's cloud.
enhanced, drop-in replacement for MySQL.
MySQL implementation using NDB Cluster storage engine.
enhanced, drop-in replacement for MySQL.
High Performance Proxy for MySQL.
TokuDB is a storage engine for MySQL and MariaDB.
is a collaboration among engineers from several companies that face similar challenges in running MySQL at scale.
hybrid of MapReduce and DBMS.
high-performance data warehouse appliances.
Scalable Open Source PostgreSQL-based Database Cluster.
Open Source Recommendation Engine Built Entirely Inside PostgreSQL.
open source MPP database system solely targeted at data warehousing and data mart applications.
multi-peta-byte database / MPP derived by PostgreSQL.
An open-source time-series database optimized for fast ingest and complex queries
an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.
key/value cache for flash storage.
fork of Memcache.
A fast, light-weight proxy for memcached and redis.
key/value cache for flash storage.
fork of Memcache.
commercially supported, open-source SQL relational database management system.
a software library that provides a high-performance embedded database for key/value data.
Erlang LSM BTree Storage.
a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
ultra-fast, ultra-compact key-value embedded data store developed by Symas.
embeddable persistent key-value store for fast storage based on LevelDB.
business intelligence platform in the cloud.
business intelligence made simple.
lean business intelligence platform to visualize and explore your data.
notebook-based anlytics and visualisation platform using SQL or drag-and-drop.
self-service business intelligence tool in the cloud.
Large scale geospatial analytics for Google BigQuery based on Kepler.gl.
platform for data products and embedded analytics.
powerful business intelligence suite.
customisable Business Intelligence platform.
Interactive Big Data Analytics.
Performance Monitoring for Amazon Redshift
The open source Looker alternative built on dbt
The simplest, fastest way to get business intelligence and analytics to everyone in your company.
business intelligence software and platform.
software platforms for business intelligence, mobile intelligence, and network applications.
Fast, clean SQL client and business intelligence.
business intelligence platform.
business intelligence and analytics platform.
collaborative SQL notebooks for querying, scheduling, and sharing reporting workflows.
Open source business intelligence platform, supporting multiple data sources and planned queries.
BI and data platform with AI exploration, dashboards, and pixel-perfect report generation; formerly ReportBurster.
Open source analytics platform.
open source business intelligence platform. (former SpagoBi)
modern B.I platform powered by Apache Spark.
Big Data Analytics.
Web UI for PrestoDB.
fast, simple and flexible JavaScript (HTML5) charting library featuring pure JS API.
graph visualization library using web workers and jQuery.
visualize logs and time-stamped data stored in Solr. Port of Kibana.
Web UI for Impala.
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…
D3-based reusable chart library
open-source or freemium hosting for geospatial databases with powerful front-end editing capabilities and a robust API.
responsive, retina-compatible charts with just an img tag.
open source HTML5 Charts visualizations.
another open source HTML5 Charts visualization.
JavaScript library for exploring large multivariate datasets in the browser. Works well with dc.js and d3.js.
JavaScript library for visualizing complex networks.
Dimensional charting built to work natively with crossfilter rendered using d3.js. Excellent for connecting charts/additional metadata to hover events in D3.
Compose complex, data-driven visualizations from reusable charts and components.
A fairly robust set of reusable charts and styles for d3.js.
Analytical Web Apps for Python, R, Julia, and Jupyter. Built on top of plotly, no JS required
Large scale geospatial analytics for Google BigQuery based on Kepler.gl.
High-performance plugin-based React chart for Bootstrap and Material Design.
dynamic HTML5 visualization.
JavaScript component for pivot tables, charts, and web reporting.
write SQL queries that return SVG charts rather than tables
GitHub-inspired simple and modern SVG charts for the web with zero dependencies.
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.
simple charting API.
scalable Realtime Graphing.
simple and flexible charting API.
provides a rich architecture for interactive computing.
open source big data analysis and visualization platform
plotting with Python.
a library built on top of D3 that is optimized for time-series data
chart components for d3.js.
Progressive SVG bar, line and pie charts.
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.
simple but powerful library for building data applications in pure Javascript and HTML.
A composable charting library built on React components
a web application framework for R.
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.
a visualization grammar.
free web pivot table component for embedding analytics in applications.
a notebook-style collaborative data analysis.
JavaScript charting library for big data.
one-stop data application development management portal.
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.
Cloud-based bi-directional monitoring and messaging hub
Cloud-based sensor analytics.
Platform for Internet of things.
Data stream network
Rapid development and connection of intelligent systems
Making products smart
Analytics platform to process network data on Spark.
Pub/sub messaging platform for IoT
Benchmark of Redshift, Hive, Shark, Impala and Stiger/Tez.
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.
Guide to monitoring Apache Kafka, including native methods for metrics collection.
Guide to monitoring Hadoop, with an overview of Hadoop architecture, and native methods for metrics collection.
Guide to monitoring Cassandra, including native methods for metrics collection.
Facebook - One Trillion Edges: Graph Processing at Facebook-Scale.
Stanford - Mining of Massive Datasets.
AMPLab - Presto: Distributed Machine Learning and Graph Processing with Sparse Matrices.
AMPLab - MLbase: A Distributed Machine-learning System.
AMPLab - Shark: SQL and Rich Analytics at Scale.
AMPLab - GraphX: A Resilient Distributed Graph System on Spark.
Google - HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm.
Microsoft - Scalable Progressive Analytics on Big Data in the Cloud.
Metamarkets - Druid: A Real-time Analytical Data Store.
Google - Online, Asynchronous Schema Change in F1.
Google - F1: A Distributed SQL Database That Scales.
Google - MillWheel: Fault-Tolerant Stream Processing at Internet Scale.
Facebook - Scuba: Diving into Data at Facebook.
Facebook - Unicorn: A System for Searching the Social Graph.
Facebook - Scaling Memcache at Facebook.
Twitter - The Unified Logging Infrastructure for Data Analytics at Twitter.
AMPLab - Blink and It’s Done: Interactive Queries on Very Large Data.
AMPLab - Fast and Interactive Analytics over Hadoop Data with Spark.
AMPLab - Shark: Fast Data Analysis Using Coarse-grained Distributed Memory.
Microsoft - Paxos Replicated State Machines as the Basis of a High-Performance Data Store.
Microsoft - Paxos Made Parallel.
AMPLab - BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data.
Google - Processing a trillion cells per mouse click.
Google - Spanner: Google’s Globally-Distributed Database.
AMPLab - Scarlett: Coping with Skewed Popularity Content in MapReduce Clusters.
AMPLab - Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center.
Google - Megastore: Providing Scalable, Highly Available Storage for Interactive Services.
Facebook - Finding a needle in Haystack: Facebook’s photo storage.
AMPLab - Spark: Cluster Computing with Working Sets.
graph processing framework.
Google - Large-scale Incremental Processing Using Distributed Transactions and notifications base of Percolator and Caffeine.
Google - Dremel: Interactive Analysis of Web-Scale Datasets.
Yahoo - S4: Distributed Stream Computing Platform.
HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads.
AMPLab - Chukwa: A large-scale monitoring system.
Amazon - Dynamo: Amazon’s Highly Available Key-value Store.
Google - The Chubby lock service for loosely-coupled distributed systems.
Google - Bigtable: A Distributed Storage System for Structured Data.
Google - MapReduce: Simplied Data Processing on Large Clusters.
distributed filesystem.
Spark in Motion teaches you how to use Spark for batch and streaming data analytics.
LiveVideo tutorial that covers machine learning, Tensorflow, artificial intelligence, and neural networks.
Introduction to schema design for data warehouse using the star schema method.
LiveVideo tutorial that covers searching, analyzing, and visualizing big data on a cluster with Elasticsearch, Logstash, Beats, Kibana, and more.
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 introduces the concepts and requirements of streaming and real-time data systems.
Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams.
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.
Presents a new paradigm suitable for stream and complex event 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 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 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 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 is a fast-paced introduction to every aspect of working with Kafka you need to really reap its benefits.
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 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!
A book about data engineering in general and the Azure platform specifically
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.
tutorial for using PySpark to build data-driven applications at scale.
practical guide to building and maintaining data pipelines with Airflow.
Theory of distributed systems. Include parts about time and ordering, replication and impossibility results.
Alessandro Negro. Combine graph theory and models to improve machine learning projects
igorbarinov/awesome-data-engineering
A curated list of data engineering tools for software developers
awesomedata/awesome-public-datasets
A topic-centric list of HQ open datasets.
ohenley/awesome-ada
A curated list of awesome resources related to the Ada and SPARK programming language
briatte/awesome-network-analysis
A curated list of awesome network analysis resources.
bytewax/awesome-public-real-time-datasets
A list of publicly available datasets with real-time data maintained by the team at bytewax.io
manuzhang/awesome-streaming
a curated list of awesome streaming frameworks, applications, etc