What is TimescaleDB?
Who uses TimescaleDB?
Here are some stack decisions, common use cases and reviews by companies and developers who chose TimescaleDB in their tech stack.
As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.
We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.
PostgreSQL plus TimescaleDB allow us to concentrate the business effort on how to analyze valuable data instead of manage them on IT side. We are now able to ingest thousand of social shares "managed" data without compromise the scalability of the system or the time query. TimescaleDB is transparent to PostgreSQL , so we continue to use the same SQL syntax without any changes. At the same time, because we need to manage few document objects we dismissed the MongoDB cluster.
Hi, I need advice on which Database tool to use in the following scenario:
I work with Cesium, and I need to save and load CZML snapshot and update objects for a recording program that saves files containing several entities (along with the time of the snapshot or update). I need to be able to easily load the files according to the corresponding timeline point (for example, if the update was recorded at 13:15, I should be able to easily load the update file when I click on the 13:15 point on the timeline). I should also be able to make geo-queries relatively easily.
I am currently thinking about Elasticsearch or PostgreSQL, but I am open to suggestions. I tried looking into Time Series Databases like TimescaleDB but found that it is unnecessarily powerful than my needs since the update time is a simple variable.
Thanks for your advice in advance!
Python Sanic PostgreSQL TimescaleDB Redis
Simple, yet, astonishingly fast and powerful stack to handle huge load of data feed from cryptocurrency exchanges across the globe.
- Packaged as a PostgreSQL extension
- Full ANSI SQL
- JOINs (e.g., across PostgreSQL tables)
- Complex queries
- Secondary indexes
- Composite indexes
- Support for very high cardinality data
- Ability to ingest out of order data
- Ability to perform accurate rollups
- Data retention policies
- Fast deletes
- Integration with PostGIS and the rest of the PostgreSQL ecosystem