cstore_fdw
hydra
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cstore_fdw | hydra | |
---|---|---|
6 | 26 | |
1,738 | 2,620 | |
0.4% | 5.7% | |
2.6 | 8.5 | |
about 3 years ago | 8 days ago | |
C | C | |
Apache License 2.0 | Apache License 2.0 |
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cstore_fdw
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Moving a Billion Postgres Rows on a $100 Budget
Columnar store PostgreSQL extension exists, here are two but I think I’m missing at least another one:
https://github.com/citusdata/cstore_fdw
https://github.com/hydradatabase/hydra
You can also connect other stores using the foreign data wrappers, like parquet files stored on an object store, duckdb, clickhouse… though the joins aren’t optimised as PostgreSQL would do full scan on the external table when joining.
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Anything can be a message queue if you use it wrongly enough
I'm definitely not from Citus data -- just a pg zealot fighting the culture war.
If you want to reach people who can actually help, you probably want to check this link:
https://github.com/citusdata/cstore_fdw/issues
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Pg_squeeze: An extension to fix table bloat
That appears to be the case:
https://github.com/citusdata/cstore_fdw
>Important notice: Columnar storage is now part of Citus
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Ingesting an S3 file into an RDS PostgreSQL table
either we go for RDS, but we stick to the AWS handpicked extensions (exit timescale, citus or their columnar storage, ... ),
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Postgres and Parquet in the Data Lke
Re: performance overhead, with FDWs we have to re-munge the data into PostgreSQL's internal row-oriented TupleSlot format again. Postgres also doesn't run aggregations that can take advantage of the columnar format (e.g. CPU vectorization). Citus had some experimental code to get that working [2], but that was before FDWs supported aggregation pushdown. Nowadays it might be possible to basically have an FDW that hooks into the GROUP BY execution and runs a faster version of the aggregation that's optimized for columnar storage. We have a blog post series [3] about how we added agg pushdown support to Multicorn -- similar idea.
There's also DuckDB which obliterates both of these options when it comes to performance. In my (again limited, not very scientific) benchmarking of on a customer's 3M row table [4] (278MB in cstore_fdw, 140MB in Parquet), I see a 10-20x (1/2s -> 0.1/0.2s) speedup on some basic aggregation queries when querying a Parquet file with DuckDB as opposed to using cstore_fdw/parquet_fdw.
I think the dream is being able to use DuckDB from within a FDW as an OLAP query engine for PostgreSQL. duckdb_fdw [5] exists, but it basically took sqlite_fdw and connected it to DuckDB's SQLite interface, which means that a lot of operations get lost in translation and aren't pushed down to DuckDB, so it's not much better than plain parquet_fdw.
This comment is already getting too long, but FDWs can indeed participate in partitions! There's this blog post that I keep meaning to implement where the setup is, a "coordinator" PG instance has a partitioned table, where each partition is a postgres_fdw foreign table that proxies to a "data" PG instance. The "coordinator" node doesn't store any data and only gathers execution results from the "data" nodes. In the article, the "data" nodes store plain old PG tables, but I don't think there's anything preventing them from being parquet_fdw/cstore_fdw tables instead.
[0] https://github.com/citusdata/cstore_fdw
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Creating a simple data pipeline
The citus extension for postgresql. https://github.com/citusdata/cstore_fdw
hydra
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Using ClickHouse to scale an events engine
Don't feel bad, lots of people get bitten by not reading all the way down to the bottom of their readme: https://github.com/hydradatabase/hydra/blob/v1.1.2/README.md... While Hydra may very well license their own code Apache 2, they ship the AGPLv3 columnar which to my very best IANAL understanding taints the whole stack and AGPLv3's everything all the way through https://github.com/hydradatabase/hydra/blob/v1.1.2/columnar/...
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Moving a Billion Postgres Rows on a $100 Budget
Columnar store PostgreSQL extension exists, here are two but I think I’m missing at least another one:
https://github.com/citusdata/cstore_fdw
https://github.com/hydradatabase/hydra
You can also connect other stores using the foreign data wrappers, like parquet files stored on an object store, duckdb, clickhouse… though the joins aren’t optimised as PostgreSQL would do full scan on the external table when joining.
- Hydra (YC W22) adds upsert to columnar Postgres
- Hydra
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Is ClickHouse Moving Away from Open Source?
New column store alternative : https://github.com/hydradatabase/hydra
HN: https://news.ycombinator.com/item?id=37571974
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Show HN: Hydra - Open-Source Columnar Postgres
some previous discussions:
https://news.ycombinator.com/item?id=37247945
https://news.ycombinator.com/item?id=36987920
and a relevant observation is that there are actually multiple license files in the repo so the consumer should read their explicit licensing section of the readme <https://github.com/hydradatabase/hydra#license> since the GitHub sidebar is misleading
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CDC from postgres to postgres.
Hydra DB Link to Github -> Worked well for aggregated query usecases but not for queries that build reports. Also, data insertion and updation is abyssmal on columnar dbs.
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How Query Engines Work
There's a lot of experience about db operation and how to approach MVCC encoded in PostgreSQL that shouldn't be underestimated.
[0]: https://github.com/hydradatabase/hydra
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Hydra: Column-Oriented Postgres
And just like last time, watch out for the misleading GitHub license detector because it's not entirely Apache as the GitHub summary claims but rather *some* is Apache and buried in the interior is some AGPL stuff: https://github.com/hydradatabase/hydra#license
What are some alternatives?
ZLib - A massively spiffy yet delicately unobtrusive compression library.
duckdb - DuckDB is an in-process SQL OLAP Database Management System
odbc2parquet - A command line tool to query an ODBC data source and write the result into a parquet file.
citus - Distributed PostgreSQL as an extension
zstd - Zstandard - Fast real-time compression algorithm
ClickHouse - ClickHouse® is a free analytics DBMS for big data
cute_headers - Collection of cross-platform one-file C/C++ libraries with no dependencies, primarily used for games
postgres - PostgreSQL in Neon
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Udacity-Data-Engineering-Projects - Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
parquet_fdw - Parquet foreign data wrapper for PostgreSQL
vasco - vasco: MIC & MINE statistics for Postgres