InfluxDB vs. kdb+ vs. QuestDB

InfluxDB is very good at storing monitoring metrics (e.g. performance data). InfluxDB is not the right choice if you need to store other data types (like plain text, data relations etc.).

Incentivized

kdb is well suited for real time tick data and time series analytics.

Incentivized

QuestDB is well suited for any use case where you need to store large amount of data and the performance is the key factor - for both reads and writes. So use cases like market data storage in financial industry, any kind of telemetry, etc.

• Perfect handling telemetry data.
• Low latency, near real time.
• SQL-like language makes it easier to query.

Incentivized

• Time series analysis. The built-in vector operations are extremely fast. Also with the q language you can code up any customized analytical ideas quickly.
• The database are all file based, very easy to maintain.
• Very solid and fast interface to websocket, so you can interface with javascript easily.

Incentivized

• Extreme performance.
• Super easy to use.
• Compatibility with Influx line protocol.
• PostgreSQL compatibility.
• Out of order timestamps.
• Support for multiple records with same timestamp.
• Integration with Grafana.
• Team responsiveness.

• GUI based administrator console

Incentivized

• Run time error message readability, particularly for new users.
• Backwards compatibility between versions.

Incentivized

• New project so needs a bit polishing.

InfluxDB is a near perfect product for time series database engines. The relatively small list of cons are heavily outweighed by it's ability to just work and be a very flexible and powerful database engine. The community and support provided by the corporation are the only areas I have little experience.

Incentivized

switching costs

Incentivized

its ok

Incentivized

We have worked with the InfluxDB support team a few times so far and it has been positive. Issues submitted are worked on promptly and we have good feedback.

Incentivized

We don't use it.

Incentivized

To be honest, I didn't look at alternatives since InfluxDB performs very well if you can oversee the lack of security and HA features. But for all challenges, there is an easy solution which brings you forward (e.g. read load balancing can be achieved by using a common HTTPS load balancer).

Incentivized

Python is very commonly used for large data analysis and in general is much easier to pickup than kdb+. The biggest drawback of kdb+ is the learning curve.

Incentivized

We were looking for time series database that will be able to handle L2 market data and came across QuestDB. From the beginning we were impressed how well the QuestDB performs and that it actually significantly outperforms all other open source TSDB on market like InfluxDB, ClickHouse, Timescale, etc. Apart from the excellent performance it is also super easy to use and deploy which makes the experience of using the database very pleasant - we were able to be up and running and storing data within few hours. Topic itself is the QuestDB team that is super responsive on their slack channel and always ready to help with any query. They are constantly improving the product and if there is some missing feature that is blocking you from usage they always try the best to implement such feature asap and release a new version - one of the best support I have ever seen so far in open source community.

• Provided us a time series DB.
• With the SQL-like language, it is very easy to learn.
• Empowered us to keep track of our events.

Incentivized

• It perfectly solves most of our real time tick data needs.
• Finding good kdb resources is slightly difficult. Also new people trying to learn kdb experience a relatively longer learning curve.

Incentivized

• Reduced cost.
• Increased efficiency.
• Faster time to market.