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Great support, questions are answered almost immediately
What do you like best about the product?
Basically no weird issues that one often finds with newish software. Haven't had to jump through strange SQL hoops, or weird commands. Stuff just works more or less like any old relational DB.
What do you dislike about the product?
Only odd thing is the get-size commands are not obvious. Since you are actually creating many tables, some of the commands on normal tables need something different.
What problems is the product solving and how is that benefiting you?
We store huge amounts of financial data
It really is "just PostgreSQL" for time series data
What do you like best about the product?
I did not have to learn any groundbreaking technology to become an expert at analyzing time series data hosted with TimescaleDB. That in itself makes TSDB groundbreaking.
What do you dislike about the product?
You will end up putting TimescaleDB proprietary query logic into your system. There is no way around it unless you build your own custom interface against Timescale.
What problems is the product solving and how is that benefiting you?
Timescale efficiently and fully aggregates multiple time windows of any domain data I throw at it. It would be such a tedious development task to maintain that feature. Yet, because TimescaleDB solves this at the database later I don't have to worry about it at all on my application layer! All of my business logic can relate to WHY the time series data relates to each other rather than how I manage the relation.
The best time series database in 2023 is not a time series database
What do you like best about the product?
Timescale has predictable cost anchored in familiar reality; it is driven by storage volume and system load. You don't have that familiar, awful cardinality problem that is common to _every_ tag-set-series data model system. It performs very well and predictably. It's really awesome.
It's open source and self-hosting is easy: It is postgresql. You already know what self-hosting implies from that one statement and whether you're willing to do it. If you're not, you can pay Timescale to do it for you with Timescale Cloud. In my experience, Timescale Cloud was very effective for the months my team used it.
Their community is great, and the Timescale maintainers actually address issues reported by the community (including me personally)! It was a welcome 180 degree change from the seemingly antagonistic stance certain other related open source projects take toward their community. Their people are really good.
It's open source and self-hosting is easy: It is postgresql. You already know what self-hosting implies from that one statement and whether you're willing to do it. If you're not, you can pay Timescale to do it for you with Timescale Cloud. In my experience, Timescale Cloud was very effective for the months my team used it.
Their community is great, and the Timescale maintainers actually address issues reported by the community (including me personally)! It was a welcome 180 degree change from the seemingly antagonistic stance certain other related open source projects take toward their community. Their people are really good.
What do you dislike about the product?
There's no well-defined guidance about how time series data should be generally modeled in Postgresql. There are helpful discussions about EAV and wide schemas, but up to now, Timescale seems to shy from taking a stance.
Also, ingesting data is a pain if you don't already have some postgresql tie-in for your service. It's not really the best way to ingest time series data from disparate service hosts though; you'll have connection count issues and weird back pressure. Upgrades become very difficult that way (just ask Promscale about that, RIP). I would love to see real direct RPC integrations with de-facto standards like opentelemetry (gag) and better standards like goodmetrics on the TimescaleDB host process itself. This would make TimescaleDB's time series ingest from service hosts perfectly seamless, and would establish common standards for data modeling.
Also, ingesting data is a pain if you don't already have some postgresql tie-in for your service. It's not really the best way to ingest time series data from disparate service hosts though; you'll have connection count issues and weird back pressure. Upgrades become very difficult that way (just ask Promscale about that, RIP). I would love to see real direct RPC integrations with de-facto standards like opentelemetry (gag) and better standards like goodmetrics on the TimescaleDB host process itself. This would make TimescaleDB's time series ingest from service hosts perfectly seamless, and would establish common standards for data modeling.
What problems is the product solving and how is that benefiting you?
Internal service operations metrics. Monitoring and alerting on microservice performance, errors and the like. Root causing bad system behaviors via rich dimensionality for metrics data and expressive SQL.
Good. But more focus on performance would be nice
What do you like best about the product?
The feature set (especially cont queries and the sql extensions)
What do you dislike about the product?
Performance is lacking compared to questdb and clickhouse
What problems is the product solving and how is that benefiting you?
Storing of market data and energy meter data
Time series databases have never been so easier
What do you like best about the product?
When I first started evaluating time series databases, Timescale was already on my list.
What I love about them is,
1. Natively built atop Postgresql, so one gets the best of both worlds
2. One can choose between their self-hosted, managed and cloud flavours
3. Excellent support and success teams that make sure you are set up, are good to go and help you with queries quickly
4. Excellent community, especially on slack, where you can ask/answer questions and support each other
What I love about them is,
1. Natively built atop Postgresql, so one gets the best of both worlds
2. One can choose between their self-hosted, managed and cloud flavours
3. Excellent support and success teams that make sure you are set up, are good to go and help you with queries quickly
4. Excellent community, especially on slack, where you can ask/answer questions and support each other
What do you dislike about the product?
Sometimes the documentation is hard to navigate and get started with the samples. For example, the commands around routine jobs for continuous aggregates, how to check and manage them, etc. Again, this is if I were to be highly critical, but as I said earlier, they have a fantastic product and ecosystem.
What problems is the product solving and how is that benefiting you?
We've a time-series data use case that Timescale solves for us superbly.
Smooth Migration and Improved Performance with Timescale Cloud
What do you like best about the product?
We recently migrated from self-hosted influxDB to Timescale Cloud and couldn't be happier. The transition was smooth and easy, and our engineers love the ability to use SQL instead of a custom query language. We've seen a significant performance increase just by using familiar SQL tricks.
What do you dislike about the product?
The only minor complaint we have is that the UI of the Cloud distribution, could use a bit more polishing, and that they are not yet listed on AWS marketplace. However, this hasn't affected the functionality or performance of the product, so it's not a significant issue.
What problems is the product solving and how is that benefiting you?
At Bloobirds, we were facing several challenges with our previous self-hosted influxDB solution. One of the biggest challenges was that we had to use a custom query language, which required a significant amount of time and resources to learn and use effectively. Additionally, our influxDB solution was not as performant as we needed it to be, especially as our data volumes continued to grow.
By migrating to Timescale Cloud, we were able to address these challenges and benefit from a number of key features. For example, Timescale Cloud allows us to use SQL to query our time-series data, which is much more familiar and easier for our engineers. This has saved us a significant amount of time and resources and has made it much easier for us to get insights from our data.
In addition, Timescale Cloud provides excellent performance, even with large volumes of data. This has allowed us to handle our growing data volumes without experiencing any slowdowns or other performance issues.
Overall, Timescale Cloud has been a major benefit to our organization, allowing us to manage and analyze our time-series data more effectively and efficiently.
By migrating to Timescale Cloud, we were able to address these challenges and benefit from a number of key features. For example, Timescale Cloud allows us to use SQL to query our time-series data, which is much more familiar and easier for our engineers. This has saved us a significant amount of time and resources and has made it much easier for us to get insights from our data.
In addition, Timescale Cloud provides excellent performance, even with large volumes of data. This has allowed us to handle our growing data volumes without experiencing any slowdowns or other performance issues.
Overall, Timescale Cloud has been a major benefit to our organization, allowing us to manage and analyze our time-series data more effectively and efficiently.
Best time-series database
What do you like best about the product?
Uses SQL -> Super easy to get into
Time-series data -> We have tons of frequently generated data, and it is able to handle it with ease
Relational data -> One database to keep other data related/connected. Makes life extremely easy!
Support -> Top notch!
Pricing -> Not more than any other cheap database you could choose. Simply perfect!
Time-series data -> We have tons of frequently generated data, and it is able to handle it with ease
Relational data -> One database to keep other data related/connected. Makes life extremely easy!
Support -> Top notch!
Pricing -> Not more than any other cheap database you could choose. Simply perfect!
What do you dislike about the product?
We have not come across anything that restricted us from making our cloud platform a success.
JSONB columns were a little bit slow when trying to do aggregations, so we had to change JSONB to another table structure, but this is just a limitation overall with any relational database, not specific to TimescaleDB!
JSONB columns were a little bit slow when trying to do aggregations, so we had to change JSONB to another table structure, but this is just a limitation overall with any relational database, not specific to TimescaleDB!
What problems is the product solving and how is that benefiting you?
Extremely frequent data. We got 50 different values rolling in every second per "device". That is a lot of data for most databases, but Timescale is able to handle it with ease.
A performant time-series database built on the rock-solid Postgres DB, with stellar support to boot
What do you like best about the product?
TimescaleDB is an extension of Postgres for time-series. As long-time Postgres users needing a time-series database, we viewed it as a great benefit that TimescaleDB is built on top of a tried and tested technology. In addition, we could continue to use ubiquitous SQL to perform our queries. The particular benefits of TimescaleDB include high compression ratios achieved through type-specific compression (we reached > 10x compression) along with much more performant time-series queries than standard Postgres. Finally, the suite of hyperfunctions in the TimescaleDB toolkit are particularly useful for our domain (high frequency financial tick data). The Timescale team has also been extremely helpful and supportive through the process of migrating to TimescaleDB.
What do you dislike about the product?
Migrating large volumes of data to the cloud (~100 TB uncompressed) is time-consuming and requires careful thought. That said, the Timescale team has been a great help to us in navigating this process.
What problems is the product solving and how is that benefiting you?
The storage and analysis of large volumes of high-frequency financial tick data (market data). These data are the foundation of our analyses as an electronic trading quant team.
The Easiest, Fastest and Most Cost Effective Time Series Database - Period
What do you like best about the product?
We loved the ease of installation and the familiarity of Timescale with PostgreSQL. It was easy to get started, and it has been easy to maintain the database. Most importantly, the ingestion rate is INSANE, even on a small server instance. The time_bucket() and time_bucket_gapfill() functions in queries make retrieval of our data a trivial issue, so we can focus on our business needs instead of lengthy development cycles. Also, Timescale maintains an active Slack channel where we can find the support we need.
What do you dislike about the product?
I'm wracking my brain to find anything I dislike about using TimescaleDB. The only issues we experienced during the implementation and upkeep of our self-hosted TimescaleDB instances have all been addressed either by small code changes or by the improved TimescaleDB version releases.
What problems is the product solving and how is that benefiting you?
We needed to find a time series database solution with a high ingestion rate due to the speed of telemetry data coming from our devices. The added benefit of the fact that the software is essentially free for the community edition is the icing on the cake.
Real time tracking app for watersport enthusiasts build on a time series & geo-spatial database.
What do you like best about the product?
- Performance for time series real time data processing.
- Relational database as a service -> less system skills and sysadmin tasks
- Support responsiveness
- Relational database as a service -> less system skills and sysadmin tasks
- Support responsiveness
What do you dislike about the product?
- lack of superuser rights preventing the use of some extensions such as pgTap or pg_cron
- no easy solution to trigger processing outside the database.
- no easy solution to trigger processing outside the database.
What problems is the product solving and how is that benefiting you?
Ingesting, cleaning, contextualizing and visualizing in realtime a lot of navigation data coming from a lot of different sources.
This is a core technology, simply critical to grow our business.
This is a core technology, simply critical to grow our business.
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