9 Reasons to Choose Timescale vs. Influx and AWS Timestream

9 Reasons to Choose Timescale vs. Influx and AWS Timestream

Why should you choose TimescaleDB over InfluxDB or AWS Timestream? Let us count the ways.

We know there are a lot of options for developers who want (and need) to store time-series data, and as we’ve discussed before, all data is time-series data. We’re biased, but we’ve built TimescaleDB to solve complex data challenges with features custom-designed for time-series workloads – and the best way to get TimescaleDB is via Managed Service for TimescaleDB, our fully-managed database-as-a-service.

Simply put, we handle the operations and management of your database, so you focus on building great applications and analyzing the metrics that matter to your business.

To help you weigh your options, we’ve compiled nine reasons customers tell us Managed Service for TimescaleDB is the best choice for solving their time-series and analytics problems:

1. More clouds and more regions

Only Managed Service for TimescaleDB is available in the three major cloud providers (Amazon Web Services, Microsoft Azure, and Google Cloud Platform), in over 75 regions around the world. Influx Cloud is generally available in only 2 clouds and 3 regions. AWS Timestream, whenever it officially launches, will only be available on AWS.

2. Migrate between clouds and regions with a single click

With Managed Service for TimescaleDB, you can start your project in one cloud provider and easily migrate to a different cloud as your business needs change. You never have to talk to us (although we’d love to hear from you and have an active public Slack community!). It just works.

3. More scalable

Managed Service for TimescaleDB offers over 2000 different CPU and storage configurations, including up to 72 CPUs and 10TB of storage (which is equivalent to 150TB+ of uncompressed data, thanks to TimescaleDB’s best-in-class compression).

4. Deterministic pricing

Managed Service for TimescaleDB provides crystal clear pricing calculators so that you know ahead of time how much you’re going to pay at the end of the month.

5. Yes, SQL

You can query all your Managed Service for TimescaleDB data using SQL, a query language known the world over. SQL has a rich history, is well-documented, and, at last count, is the 3rd most commonly used programming language among developers.

Have a question on how to structure a query? Millions of developers in SQL communities around the world stand ready to help you.

TimescaleDB functionality builds on top of the SQL syntax and optimizes it for time-series analysis. For example, time_bucket expands on SQL's date_trunc function to allow you to query over arbitrary time intervals, like 1 week, 5 mins, or 3 seconds, instead of being limited to second, minute, hour, etc. Unlike a brand new, still-in-development, and proprietary query language like Influx’s Flux, which you and all your colleagues now need to learn.

6. PostgreSQL

TimescaleDB is built on PostgreSQL, a battle-tested and trusted relational database. With TimescaleDB, you can easily join your time-series analytics with the other business data you store in PostgreSQL, so that you can add context, write more powerful queries, gain greater insight, and make better decisions.

7. More cost-effective

For some use cases, developers save thousands of dollars per day by using Managed Service for TimescaleDB. For example, AWS Timestream can be anywhere from 9X to 72X more expensive than Managed Service for TimescaleDB, depending on the type of workload.

8. We try harder

Our world-class support and customer success team is always here to help you. We’re focused on your entire solution, not just your TimescaleDB problems. That means we do whatever it takes to ensure your success, from advising on database design to giving you specific advice for query optimization and everything in between. When you look good, we look good.

9. It exists

Unlike AWS Timestream.

Ready to get started with Managed Service for TimescaleDB?

👉 Sign up now.

We know every customer and scenario is unique, and we’re here to help with any questions along the way (reach out to us on Slack at any time - our engineers, co-founders, and community members are active on all channels).

You can also learn more about how Timescale stacks up against InfluxDB.

If you need to migrate from InfluxDB, we built a utility for you called Outflux.

Or, if you’re trying to build your own time-series solution on a NoSQL database, why you should think twice before choosing MongoDB for time-series data.

The open-source relational database for time-series and analytics.
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