Dgraph is a horizontally scalable and distributed graph database, providing ACID transactions, consistent replication and linearizable reads. It's built from ground up to perform for a rich set of queries. Being a native graph database, it tightly controls how the data is arranged on disk to optimize for query performance and throughput, reducing disk seeks and network calls in a cluster.
 
Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC.

Dgraph is a horizontally scalable and distributed graph database, providing ACID transactions, consistent replication and linearizable reads. It's built from ground up to perform for a rich set of queries. Being a native graph database, it tightly controls how the data is arranged on disk to optimize for query performance and throughput, reducing disk seeks and network calls in a cluster.

Dgraph - Fast, Transactional, Distributed Graph Database

KeyDB is a high performance fork of Redis with a focus on multithreading, memory efficiency, and high throughput. In addition to multithreading, KeyDB also has features only available in Redis Enterprise such as Active Replication, FLASH storage support, and some not available at all such as direct backup to AWS S3.
 
KeyDB maintains full compatibility with the Redis protocol, modules, and scripts. This includes the atomicity guarantees for scripts and transactions. Because KeyDB keeps in sync with Redis development KeyDB is a superset of Redis functionality, making KeyDB a drop in replacement for existing Redis deployments.
 
In addition to supporting LUA, KeyDB also supports JavaScript using the powerful V8 JIT engine. ModJS lets you write functions in javascript that can in turn be called directly by KeyBD.

KeyDB is a high performance fork of Redis with a focus on multithreading, memory efficiency, and high throughput. In addition to multithreading, KeyDB also has features only available in Redis Enterprise such as Active Replication, FLASH storage support, and some not available at all such as direct backup to AWS S3.

Keydb - A Multithreaded Fork of Redis 

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

OrbitDB is a serverless, distributed, peer-to-peer database. OrbitDB uses IPFS as its data storage and IPFS Pubsub to automatically sync databases with peers. It's an eventually consistent database that uses CRDTs for conflict-free database merges making OrbitDB an excellent choice for decentralized apps (dApps), blockchain applications and offline-first web applications.
 
OrbitDB provides various types of databases for different data models and use cases:
<ul>
<li><a href="https://github.com/orbitdb/orbit-db/blob/master/API.md#orbitdblognameaddress" target="_blank">log</a>: an immutable (append-only) log with traversable history. Useful for "latest N" use cases or as a message queue.</li>
<li><a href="https://github.com/orbitdb/orbit-db/blob/master/API.md#orbitdbfeednameaddress" target="_blank">feed</a>: a mutable log with traversable history. Entries can be added and removed. Useful for "shopping cart" type of use cases, or for example as a feed of blog posts or "tweets".</li>
<li><a href="https://github.com/orbitdb/orbit-db/blob/master/API.md#orbitdbkeyvaluenameaddress" target="_blank">keyvalue</a>: a key-value database just like your favourite key-value database.</li>
<li><a href="https://github.com/orbitdb/orbit-db/blob/master/API.md#orbitdbdocsnameaddress-options" target="_blank">docs</a>: a document database to which JSON documents can be stored and indexed by a specified key. Useful for building search indices or version controlling documents and data.</li>
<li><a href="https://github.com/orbitdb/orbit-db/blob/master/API.md#orbitdbcounternameaddress" target="_blank">counter</a>: Useful for counting events separate from log/feed data.</li>
</ul>

OrbitDB is a serverless, distributed, peer-to-peer database. OrbitDB uses IPFS as its data storage and IPFS Pubsub to automatically sync databases with peers. It's an eventually consistent database that uses CRDTs for conflict-free database merges making OrbitDB an excellent choice for decentralized apps (dApps), blockchain applications and offline-first web applications.

orbit-db - Peer-to-Peer Databases for the Decentralized Web

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 

Scylladb is a Cassandra compatible NoSQL column store which can do 1MM transactions/sec per server. It scales up linearly with number of cores. 

ScyllaDB - NoSQL Column Store Database compatible with Cassandra

Dqlite is a fast, embedded, persistent SQL database with Raft consensus that is perfect for fault-tolerant IoT and Edge devices. Dqlite (“distributed SQLite”) extends SQLite across a cluster of machines, with automatic failover and high-availability to keep your application running. It uses C-Raft, an optimised Raft implementation in C, to gain high-performance transactional consensus and fault tolerance while preserving SQlite’s outstanding efficiency and tiny footprint.

Dqlite - High-availability SQLite

BigchainDB allows developers and enterprise to deploy blockchain proof-of-concepts, platforms and applications with a scalable blockchain database, supporting a wide range of industries and use cases. It is a decentralization ecosystem: a decentralized database, at scale. It can perform 1 million writes per second throughput, store petabytes of data, and sub-second latency.
 
The BigchainDB design starts with a distributed database (DB), and through a set of innovations adds blockchain characteristics: decentralized control, immutability, and creation & movement of digital assets. BigchainDB inherits characteristics of modern distributed databases: linear scaling in throughput and capacity with the number of nodes, a full-featured NoSQL query language, efficient querying, and permissioning. Being built on an existing distributed DB, it also inherits enterprise-hardened code for most of its codebase.

BigchainDB allows developers and enterprise to deploy blockchain proof-of-concepts, platforms and applications with a scalable blockchain database, supporting a wide range of industries and use cases.  It is a decentralization ecosystem: a decentralized database, at scale. It can perform 1 million writes per second throughput, store petabytes of data, and sub-second latency.

BigchainDB - The Scalable Blockchain Database

EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries. Its features include Automatic partitioning, Columnar storage, Standard SQL support, Scales to petabytes, Timeseries and relational data, Fast range scans and lot more.
 
Use case: 
<ul>
 <li>
 Storage and analysis of streaming event, timeseries or relational data
 </li>
 <li>
 High volume event and sensor data logging
 </li>
 <li>
 Joining and correlating of timeseries data with relational tables
 </li>
 </ul>

 EventQL is a distributed, column-oriented database built for large-scale event collection and analytics. It runs super-fast SQL and MapReduce queries. Its features include Automatic partitioning, Columnar storage, Standard SQL support, Scales to petabytes, Timeseries and relational data, Fast range scans and lot more.

EventQL - The database for large-scale event analytics

SpiceDB is a database system for managing security-critical application permissions. Developers create a schema that models their permissions requirements and use a client library to apply the schema to the database, insert data into the database, and query the data to efficiently check permissions in their applications.
 
The data used to calculate permissions have the most critical correctness requirements in the entirety a software system. Despite that, developers continue to build their own ad-hoc solutions coupled to the internal code of each new project. By developing a SpiceDB schema, you can iterate far more quickly and exhaustively test designs before altering any application code. This becomes especially important as you introduce backwards-compatible changes to the schema and want to ensure that the system remains secure.

SpiceDB is a database system for managing security-critical application permissions. Developers create a schema that models their permissions requirements and use a client library to apply the schema to the database, insert data into the database, and query the data to efficiently check permissions in their applications.

SpiceDB - Inspired by Google's Zanzibar paper, SpiceDB is a database system for managing security-critical application permissions

SurrealDB is the ultimate mult--modal database for tomorrow's applications. SurrealDB is an end-to-end cloud-native database designed for modern applications, including web, mobile, serverless, Jamstack, backend, and traditional applications. With SurrealDB, you can simplify your database and API infrastructure, reduce development time, and build secure, performant apps quickly and cost-effectively.
<ul dir="auto">
<li>Reduces development time: SurrealDB simplifies your database and API stack by removing the need for most server-side components, allowing you to build secure, performant apps faster and cheaper.</li>
<li>Real-time collaborative API backend service:&nbsp;SurrealDB functions as both a database and an API backend service, enabling real-time collaboration.</li>
<li>Support for multiple querying languages:&nbsp;SurrealDB supports SQL querying from client devices, GraphQL, ACID transactions, WebSocket connections, structured and unstructured data, graph querying, full-text indexing, and geospatial querying.</li>
<li>Granular access control: SurrealDB provides row-level permissions-based access control, giving you the ability to manage data access with precision.</li>
<li class="task-list-item">Record links and directed typed graph connections</li>
<li>Incrementally computed views for pre-computed advanced analytics</li>
<li>Connect and query directly from web-browsers and client devices</li>
<li>Store and model data in any way with tables, documents, and graph</li>
<li>Simple schema definition for frontend and backend development</li>
<li>Use embedded JavaScript functions for custom advanced functionality</li>
</ul>

SurrealDB is an end-to-end cloud-native database designed for modern applications, including web, mobile, serverless, Jamstack, backend, and traditional applications.

SurrealDB - A scalable, distributed, collaborative, document-graph database, for the realtime web

VoltDB was specifically designed for contemporary software applications that are pushed beyond their limits by high volume data sources. VoltDB provides the ability to capture, store and process incoming data at millions of read/write operations per second. And VoltDB’s relational model opens that data to be analyzed in real-time, using familiar Business Intelligence tools, to identify data patterns and trends, spot anomalies, or perform tracking and alerting. In addition to supporting real-time analytics, VoltDB seamlessly integrates with data warehousing and Hadoop infrastructures, feeding data to those environments for deep analytical exploration. Large database gets automatically sharded to multiple nodes, basically it supports database to scale out. VoltDB implements HA using K-Safety, a configurable, active-active durability model for high performance distributed systems. Client connectors are available in languages like Java, C++, Python, PHP, HTTP/JSON, Ruby and Erlang.

VoltDB was specifically designed for contemporary software applications that are pushed beyond their limits by high volume data sources. VoltDB provides the ability to capture, store and process incoming data at millions of read/write operations per second. And VoltDB’s relational model opens that data to be analyzed in real-time, using familiar Business Intelligence tools, to identify data patterns and trends, spot anomalies, or perform tracking and alerting.

VoltDB - Fast Scalable SQL DBMS with ACID

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