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RESEARCH & RESOURCES

New PostgreSQL Acceleration Software Boosts Open Source Database Performance

Swarm64 DA 4.0 accelerates PostgreSQL performance 20x or more to help expand use of open source in data warehousing, data science, and other analytics projects.

Note: TDWI’s editors carefully choose press releases related to the data and analytics industry. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the author's statements.

Swarm64, a database acceleration solutions provider for the PostgreSQL open source database, released Swarm64 DA 4.0, database acceleration software that extends PostgreSQL with the ability to analyze data orders of magnitude faster than usual, even as data streams into the database. This enables more people to choose free open source PostgreSQL over costly proprietary databases for new analytics and data warehouse modernization projects.

"PostgreSQL is immensely popular and battle-hardened as a primary database, yet, for performance reasons it’s historically less popular in data warehousing and analytics," said Thomas Richter, CEO and co-founder of Swarm64. "Now, when extended with the Swam64 DA accelerator, PostgreSQL runs orders of magnitude faster because we’ve tripled the acceleration effects in release 4.0. This enables people to cut database costs by 75 percent or more by using free, open source PostgreSQL in a greater number of projects and to meet performance requirements that until now only costly, proprietary data warehouse and analytics databases could satisfy.”

New PostgreSQL Acceleration Features in Swarm64 DA 4.0

With Swarm64, it is easy to accelerate and scale PostgreSQL performance. It installs as an extension to free, open source PostgreSQL and does not require changes to a user’s SQL or application code. New features of Swarm64 DA include:

  • Greater parallel processing: The Swarm64 DA extension rewrites query patterns that execute in parallel at every phase of the query. It parallelizes scanning, filtering, joining, and merging and spins up to 64 parallel threads.
  • Accelerated SQL joins: JOIN conditions are widely used in SQL queries, but they are notoriously slow to process. With join acceleration in release 4.0, PostgreSQL can answer a wider variety of queries, which had heretofore been prohibitively slow for most users.
  • Reduced I/O: Swarm64 DA compresses data 5x to 25x depending on the data type. Besides reducing storage costs, reading compressed data, along with columnar indexing, reduces I/O by about 20 times relative to standard Postgres.
  • Accelerated text search: Swarm64 DA 4.0 speeds up PostgreSQL text search query extensions, enabling people to use it for larger-scale log analytics and other search applications without switching to specialized search databases.
  • FPGA support option: If an FPGA coprocessor is present on the server, Swarm64 initiates an additional 100+ SQL reader and writer processes working in parallel on the FPGA. FPGAs are a cost-efficient way to further increase the acceleration effects of Swarm64 DA to handle bigger databases, real-time analytics, or greater concurrency.

New Analytics Project Opportunities for Accelerated PostgreSQL

Within organizations using or considering Postgres, primary use cases for Swarm64 DA-accelerated PostgreSQL include:

  • Data warehouse modernization: Data warehouse architects can save millions in annual IT costs by moving data warehousing to free, open source PostgreSQL from expensive legacy platforms.
  • Scaling analytics software as a service (SaaS): Developers of fast-growing SaaS businesses that include PostgreSQL-based analytics and reporting can scale concurrent users and cut cloud database costs.
  • Machine learning and IoT: Data engineers can scale machine learning and IoT systems or analyze time-series data in real-time or at scale.

Swarm64 DA 4.0 is available immediately via the Swarm64 website or from the Amazon AWS Marketplace. Swarm64 DA software is licensed on an annual subscription basis; free trials are available.

 

 

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