Re:Building a distributed time-series database on PostgreSQL
by valyala on Thursday August 22, 2019 @12:53PM
(#20770073)
TimescaleDB could fit your workload if PostgreSQL fits you. The main issue with PostgreSQL and TimescaleDB is big amounts of storage space required for huge time series data volumes. There are reports that storing data on ZSF can reduce the required storage space.
Probably, ClickHouse [1] would fit better your needs. It can write millions of rows per second [2]. It can scan billions of rows per second on a single node and it scales to multiple nodes.
Also I'd recommend taking a look at other open-source TSDBs with cluster support:
- M3DB [3]
- Cortex [4]
- VictoriaMetrics [5]
These TSDBs speak PromQL instead of SQL. PromQL is specially optimized query language for typical time series queries [6].
Probably, ClickHouse [1] would fit better your needs. It can write millions of rows per second [2]. It can scan billions of rows per second on a single node and it scales to multiple nodes.
Also I'd recommend taking a look at other open-source TSDBs with cluster support:
- M3DB [3]
- Cortex [4]
- VictoriaMetrics [5]
These TSDBs speak PromQL instead of SQL. PromQL is specially optimized query language for typical time series queries [6].
[1] https://clickhouse.yandex
[2] https://blog.cloudflare.com/http-analytics-for-6m-requests-p...
[3] https://www.m3db.io/
[4] https://github.com/cortexproject/cortex
[5] https://github.com/VictoriaMetrics/VictoriaMetrics/
[6] https://medium.com/@valyala/promql-tutorial-for-beginners-9a...