Amazon Athena vs. InfluxDB

If you are looking to take a lot of the traditional "database administration" work off someone's plate, going with Amazon Athena certainly has "no code" options to optimize lots of database tasks. I would say this option is less appropriate if you have other Microsoft things at play, such as Power BI.

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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.).

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• Nested Schemas like JSON data structure
• Ability to adapt the data model to fit your queries better
• Performance Improvement

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

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• Response caching can be improved.
• Data Partitioning is tricky and understanding of the same could be improved.

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• GUI based administrator console

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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.

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Easy to use. Scalable. Gets the job of data warehousing setup done. Using the datalake on S3 has become super convenient.

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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.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

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).

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• The query speeds help us make more decisions in a day (speed).
• If you need more horsepower for specific times in the day this option helps scale.
• The security of your environment is well protected too.

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• 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.

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