Tiger Cloud - Annual Commit
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Great database for time series data
What do you like best about the product?
Timescale is a powerful extension to Postgresql with special features for time series data storage and processing. It has proven very useful in our IoT projects, where the compression keeps disk usage to a minimum and the continuous aggregates give a very quick overview of the data. And since it's all Postgres - no need to learn a new query language.
The managed Timescale cloud service is a cost effective and stable alternative for us, since we don't have the resources to maintain the required infrastructure and installation. Added to this, there is a strong community and helpful support should one need guidance along the road to production.
The managed Timescale cloud service is a cost effective and stable alternative for us, since we don't have the resources to maintain the required infrastructure and installation. Added to this, there is a strong community and helpful support should one need guidance along the road to production.
What do you dislike about the product?
Well, not really a dislike, but at a first glance Timescale may possibly be perceived as an easy-to-use product where a few clicks of a button gives you an optimal setup. However, it's still a database with an extra layer of added functionality, which requires a few runs down various rabbitholes to utilize its full power. A helpful community, a responsive support and well-written docs are great aids during this exercise.
What problems is the product solving and how is that benefiting you?
Ingestion, processing and storage of IoT time series data as a foundation for various services.
Excellent performance in terms of speed and storage dimensions
What do you like best about the product?
I like very much the continuous aggregates and the jobs one can define to regularly update them.
What do you dislike about the product?
There isn't something I dislike. The online documentation is not perfect. I believe it has some room for improvement.
What problems is the product solving and how is that benefiting you?
It solves the problem of building up time-based reports on multiple dimensions. We use these to prepare to present our creators with analytics on how listeners they listen to audio content published.
Timescale Cloud got us up and running quick and easy
What do you like best about the product?
We were evaluating technologies for hosting time series data and came across TimescaleDB and Timescale Cloud. We were able to get up and running in minutes, to be able to evaluate the technology, and we have been running it in production for the past year now.
The support has been stellar, and the service does exactly what we needed. We haven't had any issues with performance or downtime and currently host ~15 instances with Timescale Cloud.
The support has been stellar, and the service does exactly what we needed. We haven't had any issues with performance or downtime and currently host ~15 instances with Timescale Cloud.
What do you dislike about the product?
Some of the enterprise features around Disaster Recovery are still in development.
It can be tedious to size down databases after doing an initial historical load of data and compressing it.
It can be tedious to size down databases after doing an initial historical load of data and compressing it.
What problems is the product solving and how is that benefiting you?
We store operational data for our SaaS product in Postgres alongside time series data, like SCADA, for analytics and visualization. Timescale makes storing and managing the time series data simple, performant, and efficient.
Efficient Time Series Database with Powerful Aggregation and Exceptional User Support
What do you like best about the product?
I've been using Timescale for several months now, and I'm extremely impressed with its performance. The database excels in storing and retrieving time series data, making it an ideal choice for my work. One of its standout features is the ability to aggregate data, which has been incredibly useful for generating insights and reports. Additionally, the compression capabilities are quite powerful, enabling us to store a large amount of data without sacrificing performance.
But what really sets Timescale apart is its outstanding user support. Whenever I've had a question or issue, the team has been quick to respond and provide helpful solutions. Overall, I highly recommend Timescale to anyone in need of a reliable and efficient time series database.
But what really sets Timescale apart is its outstanding user support. Whenever I've had a question or issue, the team has been quick to respond and provide helpful solutions. Overall, I highly recommend Timescale to anyone in need of a reliable and efficient time series database.
What do you dislike about the product?
While Timescale's compression capabilities are powerful, some of the nuances and limitations can be a bit tricky to fully grasp at first. As a result, there may be a learning curve involved in leveraging the product to its fullest capabilities. However, once you become familiar with these nuances, Timescale can be a highly effective tool for managing and analyzing time series data.
What problems is the product solving and how is that benefiting you?
At our organization, we rely on Timescale to collect and manage meter and site data from a variety of energy management systems across the country. Thanks to Timescale's robust capabilities, we're able to effectively track and analyze this data.
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.
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