QuestDB shines as a high-performance, time-series database that seamlessly integrates with our renewable energy telemetry platform. Its exceptional ingestion speed, capable of processing millions of rows per second, aligns perfectly with the high-velocity data from our sensors. The SQL and time-series extensions offer a developer-friendly experience, making it straightforward to create complex queries for real-time analytics. Additionally, its compatibility with Grafana enables us to effortlessly visualize data trends, historical records, and sensor data, providing invaluable insights into our operations. The open-source nature of QuestDB, coupled with its enterprise-grade features like role-based access control and multiple availability zones, offers both flexibility and reliability, ensuring our data is not only accessible but also secure. Review collected by and hosted on G2.com.

While QuestDB offers numerous advantages, its documentation and learning curve can pose challenges for new users unfamiliar with time-series databases. Navigating through its advanced features and optimizing queries for maximum performance may require a bit more initial effort and exploration. Additionally, although QuestDB's community and support are growing, the ecosystem is not as vast as some other databases. Review collected by and hosted on G2.com.

QuestDB is extremely performant. Both with data ingest and querying the performance is unmatched. It is reliable and fast enough for any financial application you might need it for. It is easy to set up and get started with right away with a local database and you are off running. Review collected by and hosted on G2.com.

QuestDB is still working on maturing in some aspects. The documentation is lacking in a few areas. There are also no hosted options for QuestDB so you have to host yourself. Review collected by and hosted on G2.com.

QuestDB is easy to deploy, the documentation available is great, and the value of the product is superb.

Overall it was very easy to implement. Review collected by and hosted on G2.com.

I'd like to have the ability to centrally control multiple DB instances at the same time.

There's no native OPC-UA support for manufacturing. Not that it can't be done, just that it's not a native source feature. Review collected by and hosted on G2.com.

+ Very fast

+ Extremly feature rich

+ Nice time Zone Handling integrated

+ Very fast en knowledgable support

+ Easy to setup Review collected by and hosted on G2.com.

- Limited regions in their cloud offering Review collected by and hosted on G2.com.

QuestDB and it's development team have enabled us to shape our product to our liking. We are working with very large datasets 6000+ columns x 150 rows per second and questdb has enabled us to ingest that quickly. This one feature cannot be understated as we found ourselves limited by an SQL restriction of 4096 columns in other databases. In our year of using QuestDB, the development team has made tremendous progress. In a recent release, a commit was made "5x speed up of WAL Apply for small transaction and add SQL" that opened up a whole new world of speed for us. If you tried it before and it wasn't quite there yet, I would reccomend trying it again, as this single update really allow us to be near livestreaming of all this data. We love that QuestDB uses a SQL backend, as that enables us to quickly bring new team members up to speed. Another huge benefit has been QuestDBs developer connected slack channel. When things have gone wrong, the developers at QuestDB have been quick to step in and provide feedback (generally on what we are doing wrong! haha). Occasionally we have had real bugs, and have seen a direct improvements in the next release cycle. Another benefit we've found has been the variety of languages QuestDB supports. We were quick to integrate with a pandas ingestion libaray and have been off to the races since. Review collected by and hosted on G2.com.

There are drawbacks to a newer product like QuestDB. For us it has been mostly minor things as we are building a product from scratch. Not being in production has its benefits. Mostly for us, is it took a decent amount of effort to figure out what was going wrong when it did go wrong. It takes some time to grok that while a failed ingestion via pandas doesn't directly tell you what you did wrong, the logs WILL tell you. Or when you broke your table from having Linux having too low of a max open files amount, we were initially unsure why ingestion just suddenly stopped. I have since seen most of these addressed in the Documentation, as more guinea pigs like myself have bumped into them, so that is great! Review collected by and hosted on G2.com.

As a quant researcher that need to monitor and diagnose details from high frequency sampling of market and trading data, QuestDB has proved to be reliable, performant and easy to use. Specifically I like

1. Helpful time series features that neatly fit the use cases in high frequency trading. E.g. the symbol data type, the sample by, asof join, the window function(could be more complete) etc.

2. High efficiency so that don't need to spend much on the hardware. A couple of hundred million rows with wide columns on a 4-core box serve my needs pretty well

3. Some user-friendly features that makes it easy to get data into the DB. Specifically I like the the flexible table schema, which caters to the need for constantly evolving data columns. The web UI is nice (though could be more polished). The InfluxDB line protocol supports very simple python code to upload pandas dataframes. Review collected by and hosted on G2.com.

It took me quite some time to figure out some initial performance issues. It turns out that I need to do quite some adjustments to the configurations and linux kernel settings. QuestDB website has some sections dedicated to performance tuning. Maybe the doc would present some typically setup configs that cover most common use cases. After reading through the docs and made the changes, the DB sprang to full charge.

Another issue I bumped into was how to recover the table after the linux box crashed. I couldn't figure out to why the inserts no longer works after the box is rebooted. In the end I joined the slack channel to ask the question. Thankfully Nicolas showed me the command to resume WAL, which eventually saved my table. So basically I need to read the doc to understand the WAL.

I think my efforts so far has paid off well. The doc could add more examples to highlight some tricky but still quite common cases. Review collected by and hosted on G2.com.

- We have been using QuestDB Cloud continuously for months to store weather data from sensors, and the price/ performance/DX ratio is hard to beat. Compared to well-known time series databases, QuestDB Cloud is by far the best tool for our needs.

- Thanks to the open source Docker image, we were able to add QuestDB to our local development environment in a matter of minutes.

- It's easy to use, it's so fast and it just works!

- The developer experience is wonderful: everyone in the team has a great time working with it, and QuestDB appears in the "what went well" in every sprint review.

- Really clever extension of the SQL language to make working with time series data much easier.

- It's flexible: we can pause the instance, and we can easily increase/decrease instance resources as needed from our account, which helps control the cost of dev/staging instances.

- The UI is responsive and well thought out, and the monitoring tool is very useful.

- Documentation is clear and detailed.

- The support is fantastic: very responsive and really helpful, with detailed explanations each time that have helped us a lot! And unlike other managed solutions, support is included in the price.

- New features are released regularly and the roadmap shows exciting things to come. For example, cold storage support for old data is coming soon, with the ability to query this old data. This feature will be a big plus for us. Review collected by and hosted on G2.com.

Some features are still missing (like row deletion or full join), but we're waiting for these features to come in the future. Review collected by and hosted on G2.com.

We have been working with the QuestDb Team for a couple of years now and the level of support the Team provides is outstanding. The features that were critical for us got implemented and the quality has always been at top level.

Balance between performance and features is always a challenge and we have not yet experienced loss of performance even though the list of features have grown considerably. Review collected by and hosted on G2.com.

Would like to have all features in the open source version. Review collected by and hosted on G2.com.

- Easy to explore and get started using the demo and open-source version

- Highly performant, with concurrent writes over different flavours of data API.

- Column-store storage model, aiding prototyping and flexibility to modify the schema of large datasets.

- Provides a relational model and query language which simplifies migration of existing domain models.

- CSV import/export, useful for integration with existing database infrastructure.

- Good set of key primitives for maintenance and data lifecycle management.

- Roadmap brings key improvements around replication, data sharding, and aggregation functions.

- Support for some OLTP use cases, with UPDATE and PUT-style de-duplication.

- Approachable maintainers with a growing and supportive community.

- Supports a variety of third-party integrations, helping to integrate the database as a storage layer within larger systems.

- Overall, a fast and flexible database that can support a variety of use cases. Review collected by and hosted on G2.com.

- Error handling could improve (particularly for ILP)

- Some inconsistency in how well some tools integrate with the database over Postgres database connectors.

- Limited support for data sharding/partitioning

The issues above are on the roadmap for improvement and would increase the review score. Review collected by and hosted on G2.com.

QuestDB is so easy that a one person can handle a database with millions of rows.

Nice Dashboard

Very very fast (50million rows in less than 100ms)

Easy to manage with docker and kamal.

Easy to learn

Easy to install and implement

My Daily usage routing is to check QuestDB

The support team from Slack is fantastic Review collected by and hosted on G2.com.

Window function

Percentiles and Distributions

Compression and database size could be better, but I guess that's coming soon.

Backups could be stored directly in S3 or any compatible alternative. Review collected by and hosted on G2.com.