Re:Scaling Relational SQL Databases (2020)
by CharlesW on Wednesday June 16, 2021 @04:18PM
(#27532998)
> The only big thing (which the article does call out) is that this is about scaling _traditional_ SQL databases. Traditional SQL databases don't have builtin horizontal scaling.
FWIW, the use of the word "traditional" here may need an asterisk, as some OG relational SQL databases like Teradata (born 1979, still used for ultra-high-scale applications) were designed for and depend on horizontal scaling.
Re:Scaling Relational SQL Databases (2020)
by nivertech on Wednesday June 16, 2021 @10:26AM
(#27528862)
Do you mean that TimescaleDB 2.0 can be used instead of Citus to scale general purpose (non just timeseries) workloads?
For example a multitenant workloads where you shard by org_id, etc.?
I actually thought about it, but wasn't aware about v2.0
Re:Scaling Relational SQL Databases (2020)
by ryanbooz on Wednesday June 16, 2021 @02:12PM
(#27531649)
Horizontal scaling within TimescaleDB is still geared around time-series data and (distributed) hypertables.
https://docs.timescale.com/timescaledb/latest/how-to-guides/...
https://docs.timescale.com/timescaledb/latest/how-to-guides/...
Re:Scaling Relational SQL Databases (2020)
by eatonphil on Wednesday June 16, 2021 @10:30AM
(#27528909)
Our use case was OLAP workload and IIRC I don't think it's transaction support is great for horizontally scaling OLTP workloads. I wanted to call it out since the author mentioned timeseries data but didn't mention this aspect of Timescale. (Though to be fair, this feature of Timescale may have came out after the post was written.)
Re:Scaling Relational SQL Databases (2020)
by petr25102018 on Wednesday June 16, 2021 @01:02PM
(#27530801)
Thanks for the information. I wasn't aware of such feature at the time of writing the post.
The only big thing (which the article does call out) is that this is about scaling _traditional_ SQL databases. Traditional SQL databases don't have builtin horizontal scaling.
The article is a little hazy about "specialized extensions":
> When we need to store and work with geospatial, time series and other specialized data, we can sometimes use a database extension like TimescaleDb or PostGIS to make the data processing and storage more efficient.
The point I'd call out is that specifically TimescaleDB allows you to horizontally scale PostgreSQL which is a pretty radical improvement on vanilla Postgres.
https://blog.timescale.com/blog/timescaledb-2-0-a-multi-node...