ClickHouse is an open source column-oriented database management system capable of real time generation of analytical data reports using SQL queries. It is Linearly Scalable, Blazing Fast, Highly Reliable, Fault Tolerant, Data compression, Real time query processing, Web analytics, Vectorized query execution, Local and distributed joins. It can process hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second.

ClickHouse - Columnar DBMS and Real Time Analytics

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

Storm is a distributed real time computation system. Storm makes it easy to reliably process unbounded streams of data, doing for real time processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. 
Storm integrates with the queueing and database technologies you already use. A Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed.

Storm is a distributed real time computation system. Storm makes it easy to reliably process unbounded streams of data, doing for real time processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. 

Apache Storm - Distributed and fault-tolerant realtime computation

Kudu is a storage system for tables of structured data. Kudu provides a combination of fast inserts/updates and efficient columnar scans to enable multiple real-time analytic workloads across a single storage layer. As a new complement to HDFS and Apache HBase, Kudu gives architects the flexibility to address a wider variety of use cases without exotic workarounds.

Kudu - Hadoop storage layer to enable fast analytics on fast data

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ClickHouse - Columnar DBMS and Real Time Analytics

OmniSciDB - Open Source Analytical Database & SQL Engine

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Kudu - Hadoop storage layer to enable fast analytics on fast data

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ClickHouse - Columnar DBMS and Real Time Analytics

OmniSciDB - Open Source Analytical Database & SQL Engine

Apache Storm - Distributed and fault-tolerant realtime computation

Kudu - Hadoop storage layer to enable fast analytics on fast data

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