4 ms·

Most of the time-series queries (almost all of them) are aggregated queries. Why not leverage or build top-notch Columnarstore for the same. Everything seems t

Most of the time-series queries (almost all of them) are aggregated queries. Why not leverage or build top-notch Columnarstore for the same. Everything seems to be there and why there's not first class product like ClickHouse on PG.

paulryanrogers 2y ago
Citus, Persona, TimescaleDB?
- nitinreddy88 2y ago
  Looking at the comparison with Click Benchmark, they are almost pathetic in terms of performance. They cant even handle sub-second aggregation queries for 10M records. Compared that too even duckdb reading from parquet files.
  - nikita 2y ago
    Postgres is missing a proper columnstore implementation. It's a big gap and it's not easy to build. One solution could be integrating duckdb in a similar way as pgvector. You need to map duckdb storage to Postgres storage and reuse duckdb query processor. I believe it's the fastest way to get Postgres to have competitive columnstores.
    - smythe123 2y ago
      Olo, CEO of https://www.tablespace.io https://www.tablespace.io here. We've built a columnstore extension for Postgres that is faster than ClikcHouse for real-time analytics in their own ClickBench Benchmarks. Feel free to check it out - https://www.tablespace.io/blog/postgres-columnstore-index-vs-clickhouse https://www.tablespace.io/blog/postgres-columnstore-index-vs...
    - tarasglek 2y ago
      This sounds interesting. I don't see duck db as a supported extension or mentioned anywhere in your code yet ;) Is this foreshadowing?
    - anentropic 2y ago
      Hydra?
- bloopernova 2y ago
  That was very "Klaatu, Barada, Nikto".
- applied_heat 2y ago
  Victoria metrics as well, they say based on similar structures used in clickhouse
netik 2y ago
The gold standard for this Druid at very large scale, or ClickhouseDB. Clickhouse has a lot of problems as far as modifying/scaling shards after the fact, while Druid handles this with ease (and the penalty of not being able to update after the fact.)
- anentropic 2y ago
  Doris?

paulryanrogers 2y ago

Citus, Persona, TimescaleDB?

nitinreddy88 2y ago
Looking at the comparison with Click Benchmark, they are almost pathetic in terms of performance. They cant even handle sub-second aggregation queries for 10M records. Compared that too even duckdb reading from parquet files.
- nikita 2y ago
  Postgres is missing a proper columnstore implementation. It's a big gap and it's not easy to build. One solution could be integrating duckdb in a similar way as pgvector. You need to map duckdb storage to Postgres storage and reuse duckdb query processor. I believe it's the fastest way to get Postgres to have competitive columnstores.
  - smythe123 2y ago
    Olo, CEO of https://www.tablespace.io https://www.tablespace.io here. We've built a columnstore extension for Postgres that is faster than ClikcHouse for real-time analytics in their own ClickBench Benchmarks. Feel free to check it out - https://www.tablespace.io/blog/postgres-columnstore-index-vs-clickhouse https://www.tablespace.io/blog/postgres-columnstore-index-vs...
  - tarasglek 2y ago
    This sounds interesting. I don't see duck db as a supported extension or mentioned anywhere in your code yet ;) Is this foreshadowing?
  - anentropic 2y ago
    Hydra?
bloopernova 2y ago
That was very "Klaatu, Barada, Nikto".
applied_heat 2y ago
Victoria metrics as well, they say based on similar structures used in clickhouse

netik 2y ago

The gold standard for this Druid at very large scale, or ClickhouseDB. Clickhouse has a lot of problems as far as modifying/scaling shards after the fact, while Druid handles this with ease (and the penalty of not being able to update after the fact.)

anentropic 2y ago
Doris?