TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. TimescaleDB is packaged as a PostgreSQL extension and released under the Apache 2 open-source license. 
 
TimescaleDB automatically scales and spreads data written to a hypertable into many dynamically-created chunks. Hypertables present the abstraction of a single table, yet transparently partitioned by time and space, they enable high insert rates even at billions of rows.

 TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. TimescaleDB is packaged as a PostgreSQL extension and released under the Apache 2 open-source license. 

Timescaledb - An open-source time-series database optimized for fast ingest and complex queries

MapD Core is an in-memory, column store, SQL relational database that was designed from the ground up to run on GPUs. MapD Core is the foundational element of a larger data exploration platform that emphasizes speed at scale. By taking advantage of the parallel processing power of the hardware, MapD Core can query billions of rows in milliseconds. Furthermore, by using the graphics pipelines of GPUs, MapD Core can render graphics directly from the server.
 
MapD can operate as a standalone database using the command line or its administration console. MapD can also output to its native interface, MapD Immerse, or to third-party software such as Tableau, Qlik, or Birst, using a variety of connectors. 
 
Within a single server, MapD Core can handle datasets 1.5-3TB in raw size in GPU RAM, or 10-15TB in CPU RAM. In distributed deployments, that number scales linearly.

 MapD Core is an in-memory, column store, SQL relational database that was designed from the ground up to run on GPUs. MapD Core is the foundational element of a larger data exploration platform that emphasizes speed at scale. By taking advantage of the parallel processing power of the hardware, MapD Core can query billions of rows in milliseconds. Furthermore, by using the graphics pipelines of GPUs, MapD Core can render graphics directly from the server.

MapD - The MapD Core database

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. Large queries are parallelized using multiple cores, taking all the necessary resources available on the current server. It supports distributed processing, data can reside on different shards. Each shard can be a group of replicas used for fault tolerance. All shards are used to run a query in parallel, transparently for the user.
 
ClickHouse implements user account management using SQL queries and allows for role-based access control configuration similar to what can be found in ANSI SQL standard and popular relational database management systems. It uses asynchronous multi-master replication. After being written to any available replica, all the remaining replicas retrieve their copy in the background. It adaptively chooses how to JOIN multiple tables, by preferring hash-join algorithm and falling back to the merge-join algorithm if there’s more than one large table.

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. Large queries are parallelized using multiple cores, taking all the necessary resources available on the current server. It supports distributed processing, data can reside on different shards. Each shard can be a group of replicas used for fault tolerance. All shards are used to run a query in parallel, transparently for the user.

ClickHouse - Column-oriented database management system that allows generating analytical data reports in real time

QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports.
 
QuestDB implements ANSI SQL with native extensions for time-oriented language features. These extensions make it simple to correlate data from multiple sources using relational and time series joins. QuestDB achieves high performance from a column-oriented storage model, massively-parallelized vector execution, SIMD instructions, and various low-latency techniques. The entire codebase was built from the ground up in Java and C++, with no dependencies, and is 100% free from garbage collection.

QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports.

QuestDB - Fast relational time-series database

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. 
 
Access data from multiple systems within a single query. For example, join historic log data stored in an S3 object storage with customer data stored in a MySQL relational database.

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. 

Trino - A query engine that runs at ludicrous speed

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

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.
 
OmniSciDB optimizes the memory and compute layers to deliver unprecedented performance. OmniSciDB was designed to keep hot data in GPU memory for the fastest access possible. Other GPU database systems have taken the approach of storing the data in CPU memory, only moving it to GPU at query time, trading the gains they receive from GPU parallelism with transfer overheads over the PCIe bus.
 
OmniSciDB natively supports standard SQL and returns query results hundreds of times faster than CPU-only analytical database platforms. Analysts and data scientists can still rely on their existing SQL knowledge, querying data using industry-standard SQL.

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.

OmniSciDB - Open Source Analytical Database & SQL Engine

Kibi extends Kibana 5.5.2 with data intelligence features; the core feature of Kibi is the capability to join and filter data from multiple Elasticsearch indexes and from SQL/NOSQL data sources ("external queries").In addition, Kibi provides UI features and visualizations like dashboard groups, tabs, cross entity relational navigation buttons, an enhanced search results table, analytical aggregators, HTML templates on query results, and much more.

kibi - Kibi is a friendly - kept in sync - Kibana fork which add support for joins across indexes and external sources, tabbed navigation interface and more

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