Swarm64 learning center
Learn new ways to accelerate PostgreSQL performance.
Product & technical briefs
Swarm64 DA vs. MongoDB for machine learning (.pdf)
Turbit Systems chose Swarm64 DA over MongoDB for real-time machine learning to control wind turbines.
Read it >Swarm64 DA for Data Warehousing (.pdf)
Fast, scalable open source data warehouses built on Swarm64 DA-accelerated PostgreSQL.
Read it >Swarm64 DA for IoT (.pdf)
Query data in real time as it streams into PostgreSQL to monitor, control, and predict the behavior of IoT devices.
Read it >Upcoming webinars
Faster PostgreSQL query performance on Amazon with PG Nitrous
MAY 6, 10 am PST How to accelerate Amazon RDS PostgreSQL query performance by 30x by using PG Nitrous as a fast-query replica.
Register here>Webcasts
Configuring PostgreSQL for Faster Analytic Query Performance
Swarm64 Solution Architect, Sebastian Dressler, will cover proven PostgreSQL configuration tuning best practices that have helped PostgreSQL users significantly boost analytic query performance.
On-Demand >PostgreSQL Columnstore Indexing Best Practices
Swarm64 Solution Architect, Sebastian Dressler will explain columnstore indexing best practices to help you get the best query performance out of your Postgres database.
On-Demand >Modernizing Legacy Data Warehousing with Open Source PostgreSQL
Join PostgreSQL experts from CYBERTEC and Swarm64 to learn about modernizing your SQL data warehouse & analytics platforms with open source PostgreSQL.
On-Demand >Introduction to PG Nitrous – PostgreSQL Cloud
PG Nitrous is a new PostgreSQL cloud, hosted on AWS and accelerated by Swarm64 DA.
On-Demand >Intro to Columnstore Indexing in PostgreSQL
Learn how to use new Columnstore indexes–an easy way to speed up PostgreSQL query performance by 20x.
On-Demand >PostgreSQL Parallelism Do’s & Don’ts
Learn about parallelism in the PostgreSQL query engine and best practices to maximize your PostgreSQL query performance.
On-Demand >Turbit Systems – Postgres vs. MongoDB for machine learning
Learn why Turbit Systems chose PostgreSQL over MongoDB to capture and analyze wind turbine data at scale.
On-Demand >