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.
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!
Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.
My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.
Jobs that mention TimescaleDB as a desired skillset
- 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