Viewing profile — mfreed

github.com/timescale/tigerfs

Hey, author here. Just noticed this. Yes, TigerFS works well with local PG - in fact, all of my testing framework uses this setup. Big upside of this is latency; main downside is t…

None of this. It's in the blog post in a lot of detail =) The 5ms write latency is because the backend distributed block storage layer is doing synchronous replication to multiple …

Currently support multi-AZ clusters and multi-region disaster recovery (continuous PITR between regions). We're continuing to evaluate demand for multi-region clusters, love to hea…

I'm not aware of any published source for this time limit, nor ways to reduce it. The docs do say, however, "If the volume has been impaired for more than 20 minutes, you can conta…

Tiger Cloud certainly continues to run on AWS. We have built it to rely on fairly low-level AWS primitives like EC2, EBS, and S3 (as opposed to some of the higher-level service off…

A few datapoints that might help frame this: - EBS typically operates in the millisecond range. AWS' own documentation suggests "several milliseconds"; our own experience with EBS …

TimescaleDB primarily serves operational use cases: Developers building products on top of live data, where you are regularly streaming in fresh data, and you often know what many …

Our experience is that Clickhouse and Timescale are designed for different workloads, and that Timescale is optimized for many of the time-series workloads people use in production…

All depends on the benchmark :) https://www.timescale.com/blog/what-is-clickhouse-how-does-i...

That PoC benchmark didn't turn on Timescale's columnar compression, which every real deployment uses. So misleading at best. (Timescaler)

Check out how TimescaleDB adds columnar compression to PostgreSQL, typically saving 95% of storage overhead: https://www.timescale.com/blog/building-columnar-compression...

https://www.timescale.com/blog/how-we-scaled-postgresql-to-3... Staring at a >trillion rows in a TimescaleDB hypertable on PostgreSQL.

Also, Timescale similarly introduced S3 for bottomless data tiering: https://www.timescale.com/blog/expanding-the-boundaries-of-p...

Can you say more about "dynamic labels"? Do you just mean that as you evolve, you want to add a new type of "key-value" pair? The most common approach here is just to store the ste…

If you are open, would love to hear more about some of the challenges you had with Timescale, esp. with your workload. mike (at) timescale or DM on twitter?

Do you use AWS Athena as the "database/serving layer" for customer-facing applications where performance matters? Our experience is that isn't a common use case for Athena, while i…

Very much agree. Even without this new capability of S3-based storage, Timescale's native columnar compression often gets like 95% storage reduction, even while staying fully in th…

This is a great observation. As you point out, this was designed for the workload patterns we typically see with time-series, events, and analytical data, where the query (& insert…

"Can I use Timescale to provide a SaaS service that collects application traces, and I provide a DSL to query the database that is not exposing the DB directly?" Yes you can. (Time…

TimescaleDB supports compression for all data types, it just uses type-aware compression algorithms that it applies automatically/transparently based on typing. - Gorilla compressi…

We see those types of queries commonly in TimescaleDB. And, for example, both compression and "horizontal" scale out has ways where you can optimize your code for these types of an…

I'm not sure what "recent license changes" you are referring to? The Timescale License was introduced in late 2018, although we never _relicensed_ any of our Apache 2 code, we only…

We actually do this within Timescale Cloud, and it's amazing. It allows us to cohort performance data across data stored in others microservice databases (e.g., by account types, p…