Introducing Managed TimescaleDB on ObjectRocket

By March 31, 2020 April 1st, 2020 No Comments

Today we’re excited to announce that we have added managed TimescaleDB to the ObjectRocket platform. We’ve never had a time series data store on our service, so TimescaleDB fills a key gap and enables us to help with even more of your database workloads.

Though TimescaleDB is a PostgreSQL extension and the product shares a lot of the features of our hosted PostgreSQL product, we felt it deserved top billing as a fully supported service. We’re keeping it in Beta status for a few more weeks while we add some additional capabilities and continue to load test, but we’re making it available for you to try today.

What You Get with Managed TimescaleDB on ObjectRocket

First and foremost you get a database instance with the open source TimescaleDB extension preloaded and ready to go. Since it’s based on our hosted PostgreSQL product, you also get all of the same features we offer there as well. Here’s the full rundown:

    • TimescaleDB 1.6 on a PostgreSQL 11 base – We’ll keep this updated and generally offer the latest within a month of release
    • Availability in AWS and GCP
    • Managed Backups with 2 week retention and Point-in-Time recovery included
    • Single node and HA (master/replica) setups available
    • Library of additional extensions available
    • Configuration setting customization
    • 24×7 support from Database engineers and DBAs included

Why TimescaleDB?

The path to TimescaleDB started with us looking across the market at the open source time series database options available. What we found were that some leaned too heavily toward a single use case, or perhaps didn’t have a robust enough open source offering, or didn’t have the level of adoption we would like to see. Not only does TimescaleDB solve all of those issues, but offers a number of great advantages:

  • Speed: Timescale has done a lot of testing with their Time Series Benchmark Suite to show how TimescaleDB compares with other solutions. The bottom line is that it provides better performance than the alternatives across many scenarios.
  • SQL: When adopting a new (or another) data technology, the additional hurdle of learning a new language or standard can be daunting. With TimescaleDB, you don’t have to worry about that. SQL is extremely well known, battle-tested, and provides a rich query language for most anything that you’d need to do. TimescaleDB expands that with custom time series functions, so you get more power in a language you already know.
  • PostgreSQL: This may seem redundant with the previous, but it’s not. There are a number of other time series focused data stores that also support SQL queries. The difference here is that TimescaleDB runs on PostgreSQL, so it comes with a massive community and ecosystem of tools built in. Pretty much anything that works with PostgreSQL will work with TimescaleDB.

What’s Next?

We’re currently in Beta and we have more functionality to come before we fully launch the product. However, we’d love for you to try it out and let us know what other features and capabilities you’d like to see.

Steve Croce

Steve Croce

Steve Croce is currently a Senior Product Manager and Head of User Experience at ObjectRocket. Today, Steve leads the UX/UI team through rebuilding out the platform’s user interface, scopes the company’s product and feature roadmap, and oversees the day to day development for ObjectRocket's Elasticsearch and PostgreSQL offerings. A product manager by day, he still likes to embrace his engineer roots by night and develop with Elasticsearch, SQL, Kubernetes, and web application stacks. He's spoken at KubeCon + CloudNativeCon, OpenStack summit, Percona Live, and various ObjectRocket events.