hypopg VS noria

It works particularly well with pg_stat_statements[0] which tracks execution statistics of all SQL statements executed on your Postgres database.

It leans heavily on HypoPG[1], an excellent extension to determine if PostgreSQL will use a given index without spending resources to create them.

[0] pg_stat_statements: https://www.postgresql.org/docs/current/pgstatstatements.htm...

[1] https://github.com/HypoPG/hypopg

This is an introduction to the hypopg PostgreSQL extension for YugabyteDB 2.15.3.0. Hypopg allows the creation of hypothetical indexes, so indexes that do not really exist. This means this allows you to see what an index would do if it were created, without it actually being created, and therefore not influencing anything on the database. YugabyteDB 2.15.3.0 is a preview version of the YugabyteDB database.

There's a lot of good ecosystem stuff around this:

https://github.com/HypoPG/hypopg

HypoPG is a PostgreSQL extension adding support for hypothetical indexes.

An hypothetical -- or virtual -- index is an index that doesn't really exists, and thus doesn't cost CPU, disk or any resource to create. They're useful to know if specific indexes can increase performance for problematic queries, since you can know if PostgreSQL will use these indexes or not without having to spend resources to create them.

With one approach to using it here: https://www.percona.com/blog/2019/07/22/automatic-index-reco...

> Automatically managed, application-transparent, physical denormalisation entirely managed by the database is something I am very, very interested in.

Sounds a bit like Noria: https://github.com/mit-pdos/noria

It feels more than a little bit coincidental to call it Noria when https://github.com/mit-pdos/noria exists (and has been posted about here on HN)... especially with the whole bit about incrementally computing changes.

Is this similar in spirit to Noria?

https://github.com/mit-pdos/noria

I assume you have studied Noria? https://github.com/mit-pdos/noria

If you want to look how databases are implemented in rust try https://github.com/mit-pdos/noria

Only tangentially related, but I wondered what were the difference between ReadySet and Noria, and they address this exact question in their repository I'm really glad to know that the ideas behind Noria didn't die when Noria was abandoned after /u/jonhoo graduated.

:wave: Author of the paper this work is based on here.

I'm so excited to see dynamic, partially-stateful data-flow for incremental materialized view maintenance becoming more wide-spread! I continue to think it's a _great_ idea, and the speed-ups (and complexity reduction) it can yield are pretty immense, so seeing more folks building on the idea makes me very happy.

The PlanetScale blog post references my original "Noria" OSDI paper (https://pdos.csail.mit.edu/papers/noria:osdi18.pdf), but I'd actually recommend my PhD thesis instead (https://jon.thesquareplanet.com/papers/phd-thesis.pdf), as it goes much deeper about some of the technical challenges and solutions involved. It also has a chapter (Appendix A) that covers how it all works by analogy, which the less-technical among the audience may appreciate :) A recording of my thesis defense on this, which may be more digestible than the thesis itself, is also online at https://www.youtube.com/watch?v=GctxvSPIfr8, as well as a shorter talk from a few years earlier at https://www.youtube.com/watch?v=s19G6n0UjsM. And the Noria research prototype (written in Rust) is on GitHub: https://github.com/mit-pdos/noria.

As others have already mentioned in the comments, I co-founded ReadySet (https://readyset.io/) shortly after graduating specifically to build off of Noria, and they're doing amazing work to provide these kinds of speed-ups for general-purpose relational databases. If you're using one of those, it's worth giving ReadySet a look to get these kinds of speedups there! It's also source-available @ https://github.com/readysettech/readyset if you're curious.

It seems similar to MIT's Noria [1]

> Noria is a new streaming data-flow system designed to act as a fast storage backend for read-heavy web applications based on Jon Gjengset's Phd Thesis, as well as this paper from OSDI'18. It acts like a database, but precomputes and caches relational query results so that reads are blazingly fast. Noria automatically keeps cached results up-to-date as the underlying data, stored in persistent base tables, change. Noria uses partially-stateful data-flow to reduce memory overhead, and supports dynamic, runtime data-flow and query change.

[1] https://github.com/mit-pdos/noria

Materialize is really neat, also checkout https://github.com/mit-pdos/noria. It inverts the query problem and processes the data on insert. Exactly like what most applications end up doing using a no-sql solution.