paradedb VS prism

Elasticsearch is good, and it does scale, but it is much more cumbersome and expensive to scale and operate than Postgres. If you use the managed service, you'll pay for the operational pain in the form of higher pricing.

The Postgres movement is strong and extensions like ParadeDB https://github.com/paradedb/paradedb are designed specifically to solve this pain point (Disclaimer: I work for ParadeDB)

No timeline yet, but we know it's a high-priority feature and are working hard on it. Best way would be to join our Slack (link here: https://github.com/paradedb/paradedb/blob/dev/README.md) to follow along. It will be in the coming weeks/months, though.

You're right. We're working on this currently. You can track the issue here: https://github.com/paradedb/paradedb/issues/717

There are definitely ways to cleanly make Postgres scale for analytics. We didn't discuss in this blog, but we will be writing about them in the future. For example, check out what the folks at ParadeDB are doing. https://github.com/paradedb/paradedb. Neon is doing an awesome job separating compute from storage. Supabase contributed foreign data wrappers make it super easy to read from S3 into Postgres. Lots of great work going out there :)

Check out https://github.com/paradedb/paradedb/tree/dev/pg_analytics, we're shipping this week

Shameless plug, but I'm one of the makers of `pg_bm25` (https://github.com/paradedb/paradedb). We're making a faster tsvector/tsrank as a Postgres extension. Maybe it can help, our benchmarks show much faster performance especially as row count increases

🔗 Website: https://runprism.com/

By joining our Alpha testing phase, you have the unique opportunity to be among the first users to experience Prism in action. Your invaluable feedback will directly impact the development of this platform, helping us make it even better, more stable, and tailored to your needs. Visit our website https://runprism.com to learn more about the platform and its features. In addition, check out our documentation at https://docs.runprism.com to get started right away! Access the GitHub repository https://github.com/runprism/prism to view the source code, report issues, and contribute to the project. Try out Prism in your own workflow environment and let us know what you think! We highly encourage you to share your thoughts, suggestions, and bug reports with us. Feel free to post your feedback directly in this thread, or if you prefer, you can raise issues on GitHub. Your input is invaluable to us, and together, we can shape Prism into the go-to tool for data workflow orchestration.