Hi there, leading DuckPGQ developer here :) Thanks for the shoutout! I've been busy working on an internship at DuckDB labs so DuckPGQ has gotten less attention, but I'll get back to it soon (December most likely) and will update the extension to support DuckDB v1.4.0 and v1.4.1 this week hopefully.
PGQ requires you to write using SQL and read using a graph query language. GQL is a standalone language that supports reads/writes. But much of the community is still using cypher.
As far as I can tell, this has nothing to do with CAP theorem or distributed systems. It's just being used as an analogy.
> [CAP theorem] states that any distributed storage system can provide only two of these three guarantees: Consistency, Availability and Partition safety.
> In the realm of graph databases, we observe a similar “two out three” situation. You can either have scalable systems that are not fully open source or you can have open source systems designed for small graphs. Details below.
(the article follows)
> This is one solution to the CAP theorem for graphs. We can store a billion scale graph using this method in parquet files and use a free, cheap and open source solution to traverse them, perform joins without storage costs that are prohibitively high.
The real question being raised in the blog post is - should the next generation graph databases pursue a local-only embedded strategy or build on top of object storage like many non-graph and vector embedded databases are doing.
Specifically, DuckLake (using system catalog for metadata instead of JSON/YAML) is interesting. I became aware of Apache GraphAr (incubating) after writing the blog post. But it seems to be designed for data interchange between graph databases instead of designing for primary storage.
DuckPGQ is an interesting option, but unfortunately, that project hasn't been touched in a few months and does not currently work with the latest version of DuckDB.
Hi there, leading DuckPGQ developer here :) Thanks for the shoutout! I've been busy working on an internship at DuckDB labs so DuckPGQ has gotten less attention, but I'll get back to it soon (December most likely) and will update the extension to support DuckDB v1.4.0 and v1.4.1 this week hopefully.
PGQ requires you to write using SQL and read using a graph query language. GQL is a standalone language that supports reads/writes. But much of the community is still using cypher.
More on this here:
https://adsharma.github.io/beating-the-CAP-theorem-for-graph...
As far as I can tell, this has nothing to do with CAP theorem or distributed systems. It's just being used as an analogy.
> [CAP theorem] states that any distributed storage system can provide only two of these three guarantees: Consistency, Availability and Partition safety.
> In the realm of graph databases, we observe a similar “two out three” situation. You can either have scalable systems that are not fully open source or you can have open source systems designed for small graphs. Details below.
(the article follows)
> This is one solution to the CAP theorem for graphs. We can store a billion scale graph using this method in parquet files and use a free, cheap and open source solution to traverse them, perform joins without storage costs that are prohibitively high.
That's right - it was a fun 2 out of 3 analogy.
The real question being raised in the blog post is - should the next generation graph databases pursue a local-only embedded strategy or build on top of object storage like many non-graph and vector embedded databases are doing.
Specifically, DuckLake (using system catalog for metadata instead of JSON/YAML) is interesting. I became aware of Apache GraphAr (incubating) after writing the blog post. But it seems to be designed for data interchange between graph databases instead of designing for primary storage.
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DuckPGQ is an interesting option, but unfortunately, that project hasn't been touched in a few months and does not currently work with the latest version of DuckDB.
Hi there, leading DuckPGQ developer here. I've been busy with other projects but will get back to it soon enough :)