Voldemort is a distributed key-value storage system. Data is automatically replicated over multiple servers. Data is automatically partitioned so each server contains only a subset of the total data. 
Server failure is handled transparently. It is used at LinkedIn for certain high-scalability storage problems where simple functional partitioning is not sufficient.

Project-voldemort - A distributed database, Clone of Amazon's Dynamo

Elixir is a dynamic, functional language designed for building scalable and maintainable applications. Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.
 
All Elixir code runs inside lightweight threads of execution (called processes) that are isolated and exchange information via messages. Elixir provides supervisors which describe how to restart parts of your system when things go awry, going back to a known initial state that is guaranteed to work.

Elixir is a dynamic, functional language designed for building scalable and maintainable applications. Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.

Elixir - Dynamic, Functional Language designed for building scalable and maintainable application

The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model. Cassandra is suitable for applications that can't afford to lose data. Data is automatically replicated to multiple nodes for fault-tolerance. 

 Cassandra provides support for Scale out, load balancing, cluster growth, Flexible schema, Key-oriented queries and CAP theorem (Consistency, Availability, Partition tolerance). It is in use at Digg, Facebook, Twitter, Reddit, Rackspace, Cloudkick, Cisco and more companies.

The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model. Cassandra is suitable for applications that can't afford to lose data. Data is automatically replicated to multiple nodes for fault-tolerance.

Cassandra - Scalable Distributed Database

Hypertable is based on Google's Bigtable Design, which is a proven scalable design that powers hundreds of Google services. Many of the current scalable NoSQL database offerings are based on a hash table design which means that the data they manage is not kept physically ordered. Hypertable keeps data physically sorted by a primary key and it is well suited for Analytics.
 
This project is for the design and implementation of a high performance, scalable, distributed storage and processing system for structured and unstructured data. It is designed to manage the storage and processing of information on a large cluster of commodity servers, providing resilience to machine and component failures. Data is represented in the system as a multi-dimensional table of information. The data in a table can be transformed and organized at high speed by performing computations in parallel, pushing them to where the data is physically stored.

Hypertable is based on Google's Bigtable Design, which is a proven scalable design that powers hundreds of Google services. Many of the current scalable NoSQL database offerings are based on a hash table design which means that the data they manage is not kept physically ordered. Hypertable keeps data physically sorted by a primary key and it is well suited for Analytics.

Hypertable - A high performance, scalable, distributed storage and processing system for structured 

HBase provides support to handle BigTable - billions of rows X millions of columns. It is a scalable, distributed, versioned, column-oriented store modeled after Google's Bigtable and runs on top of HDFS (Hadoop Distributed Filesystem). It features compression, in-memory operation per-column. Data could be replicated between the nodes. HBase is used in Facebook and Twitter.

HBase -  Hadoop database

GVFS stands for Git Virtual File System, It manages massive Git repositories possible. GVFS virtualizes the file system beneath your git repo so that git and all tools see what appears to be a normal repo, but GVFS only downloads objects as they are needed. GVFS also manages git's sparse-checkout to ensure that git operations like status, checkout, etc., can be as quick as possible because they will only consider the files that the user has accessed, not all files in the repo.
 
Git struggles to handle enterprise-scale repositories. Operations like cloning will slow to a crawl when you have millions of files in a repository, and even something as simple as getting your repository status will leave you waiting. GVFS was created by the Visual Studio Team Services team at Microsoft, specifically to deal with these scale issues for Microsoft's own codebases.

GVFS stands for Git Virtual File System, It manages massive Git repositories possible. GVFS virtualizes the file system beneath your git repo so that git and all tools see what appears to be a normal repo, but GVFS only downloads objects as they are needed. GVFS also manages git's sparse-checkout to ensure that git operations like status, checkout, etc., can be as quick as possible because they will only consider the files that the user has accessed, not all files in the repo.

GVFS - Git Virtual File System, Manages massive Git repositories

ONGR is a toolkit built for Symfony to make development of transactional websites Fast and Easy. It is built on Symfony and Elasticsearch. ONGR bundle includes Elasticsearch Bundle, Filter Manager Bundle, Router Bundle, Currency Exchange Bundle, Settings Bundle, API Bundle, Translation Bundle. 

ONGR - A toolkit built for Symfony to make development of transactional websites Fast and Easy

ProxySQL is a high performance, high availability, protocol aware proxy for MySQL and forks (like Percona Server and MariaDB). It has an advanced multi-core architecture. It's built from the ground up to support hundreds of thousands of concurrent connections, multiplexed to potentially hundreds of backend servers. The largest ProxySQL deployment spans several hundred proxies.
 
ProxySQL’s configuration system is inspired from routers. You can dynamically configure everything, persist the configuration and modify it. All with 0 downtime. Its other feature include Query caching, Query Routing, Application layer proxy, Advanced topology support and lot more.
 
It also acts as a Firewall, In case of offending queries that cause problems to the DB (SQL injection or inefficient retrieval of information via SELECT * without WHERE, for example), ProxySQL acts as a gatekeeper between the application and the DB, allowing DBAs to react quickly.

ProxySQL is a high performance, high availability, protocol aware proxy for MySQL and forks (like Percona Server and MariaDB). It has an advanced multi-core architecture. It's built from the ground up to support hundreds of thousands of concurrent connections, multiplexed to potentially hundreds of backend servers. The largest ProxySQL deployment spans several hundred proxies.

ProxySQL - High-performance MySQL proxy

Apache Doris is a modern MPP analytical database product. It can provide sub-second queries and efficient real-time data analysis. With it's distributed architecture, up to 10PB level datasets will be well supported and easy to operate. Doris provides batch data loading and real-time mini-batch data loading. It provides high availability, reliability, fault tolerance, and scalability. Its original name was Palo, developed in Baidu. 
 
<ul><li>Uses MySQL protocol to communicate. Users can connect to Doris cluster through MySQL client or MySQL JDBC</li><li>Support standard SQL language, compatible with MySQL protocol</li><li>Vectorized SQL executor</li><li>Getting result of a query within one second</li><li>Rollup, novel pre-computation mechanism
</li><li>Effective data model for aggregation</li><li>High performance, high availability, high reliability</li><li>Easy for operation, Elastic data warehouse for big data</li></ul>

Apache Doris is a modern MPP analytical database product. It can provide sub-second queries and efficient real-time data analysis. With it's distributed architecture, up to 10PB level datasets will be well supported and easy to operate. Doris provides batch data loading and real-time mini-batch data loading. It provides high availability, reliability, fault tolerance, and scalability. Its original name was Palo, developed in Baidu. 

Apache Doris -  A fast MPP database for all modern analytics on big data

kumofs is a scalable and highly available distributed key-value store. 
Data is replicated over multiple servers. 
Data is partitioned over multiple servers. 
Extreme single node performance; comparable with memcached. 
Both read and write performance got improved as servers added. 
Servers can be added without stopping the system. 
Servers can be added without changing the client applications. 
The system does not stop even if one or two servers crashed. 
The system does not stop to recover crashed servers. 
Scalable from 2 to 60 servers. (more than 60 servers has not be tested yet) 
Optimized for storing a large amount of small data. 
memcached protocol support. (get, set and delete only; expiration time and flags must be 0)

kumofs is a scalable and highly available distributed key-value store.

Kumofs

Hippo CMS (Hippo Content Management System) is the web-based graphical user interface that provides access to the content in the repository. It provides an easy way to create and manage your content, i.e. to write or upload, share, print, search, refer to, edit and structure content, assign rights to do so, have content automatically validated against your business rules and restore previous versions of the content. Hippo CMS is a web application, essentially providing the user interface through which the content management and administrative functionalities exposed by Hippo Repository can be used in an intuitive and user friendly way. Hippo CMS is fully customizable through a GUI plugin architecture based on the Apache Wicket web application framework. It provides features such as Multi user management, Content search, Versioning, Out of the box support for multi-language, multi-site and multi-channel implementations. Query content using REST, hook up an external application into the rendering phase via Spring. Build a Mobile app or an AngularJS app that consumes content from Hippo.

Hippo CMS (Hippo Content Management System) is the web-based graphical user interface that provides access to the content in the repository. It provides an easy way to create and manage your content, i.e. to write or upload, share, print, search, refer to, edit and structure content, assign rights to do so, have content automatically validated against your business rules and restore previous versions of the content.

Hippo CMS - Enterprise Java Content Management system

Node.js is a server-side JavaScript environment that uses an asynchronous event-driven model. It could handle thousands of concurrent connections. This allows Node.js to get excellent performance based on the architectures of many Internet applications. It is an evented I/O for <A HREF="http://code.google.com/p/v8/" target="_blank">V8</A>, which is Google's open source JavaScript engine. Using Javascript in the server and in the browser helps to work in a single programming environment. They could communicate using JSON.

Node.js is a server-side JavaScript environment that uses an asynchronous event-driven model. It could handle  thousands of concurrent connections. This allows Node.js to get excellent performance based on the architectures of many Internet applications. It is an evented I/O for V8, which is Google's open source JavaScript engine.

Node.JS - Builds Scalable Network Programs

OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase.  OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating
systems, applications) at a large scale, and make this data easily accessible and graphable.

OpenTSDB - A scalable, distributed Time Series Database.

Crate is an open source, highly scalable, shared-nothing distributed SQL database. Crate offers the scalability and performance of a modern No-SQL database with the power of Standard SQL. Crate’s distributed SQL query engine lets you use the same syntax that already exists in your applications or integrations, and have queries seamlessly executed across the crate cluster, including any aggregations, if needed.

Crate - The fast, scalable, easy to use SQL database with native full text search

Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals. It is a native Blueprints enabled graph database and as such, it supports the full TinkerPop stack of technologies.

Titan - Scalable Graph Database 

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