Hybrid Transactional/Analytical Processing (HTAP)

Hybrid Transactional/Analytical Processing (HTAP) for OLTP and OLAP in One Platform

Hybrid transactional/analytical processing (HTAP) leverages the power of in-memory computing to bring OLTP and OLAP processing onto one data platform. Before in-memory computing, transactional and analytical processes were split onto two separate data platforms to reduce load on the transactional database. OLTP was run on an operational database. The transactional data was periodically loaded into a separate analytics database via ETL where often long-running OLAP queries could be run without slowing the transactional database performance. Implementing an in-memory HTAP platform can power a single data platform which can support transactional processing and analytical processing on the same dataset. In-memory HTAP can power real-time insights and business decision making which can drive better business outcomes.

HTAP supports OLTP and OLAP processing on the same data set, significantly reducing complexity and cost

Hybrid Transactional/Analytical Processing (HTAP) with In-Memory Computing

The GridGain® in-memory computing platform provides speed and scale to in-memory HTAP architectures. By moving in-memory HTAP infrastructures to an in-memory computing platform which increases application performance by up to 1,000x compared to applications based on disk-based databases, concerns about analytic processing slowing the transactional database are removed. Both transactions and analytics can be run on the same GridGain in-memory dataset with no negative impact on performance. In addition, the amount of data that can be held in-memory can be scaled out to petabytes of in-memory data easily by adding nodes to the GridGain cluster. Organizations can then keep an arbitrarily large set of data in-memory to support analytical processing requirements in in-memory HTAP use cases. GridGain can be deployed on-premises, in private or public clouds, or in hybrid environments.

The GridGain in-memory computing platform is ANSI SQL-99 compliant, allowing users to easily run SQL analytical queries against the in-memory transactional dataset. Full SQL indexing and querying at in-memory speeds provides a powerful and fast solution for ad hoc or scheduled HTAP analytical jobs. GridGain SQL support includes support for DML and DDL.

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