pg_similarity
supabase
pg_similarity | supabase | |
---|---|---|
3 | 768 | |
352 | 66,167 | |
- | 2.4% | |
0.0 | 10.0 | |
8 months ago | 5 days ago | |
C | TypeScript | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pg_similarity
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Data Cleaning in SQL
For Postgres, there is an extension that provides that.
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Show HN: Supabase Clippy – ChatGPT for Supabase Docs
Note that pgvector isn't supported on any of the large cloud providers' hosted Postgres offerings, other than Supabase. https://github.com/pgvector/pgvector#hosted-postgres has instructions on how to add your voice to request it to be added!
(It does seem that the ancient https://github.com/eulerto/pg_similarity is supported by RDS and Google Cloud - but it's hard to tell whether attention was paid to its performance characteristics with nearly the rigor that pgvector seems to have been designed.)
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Official Elasticsearch Python library no longer works with open-source forks
While I don't doubt that you know your usecase and weighed/tried the option.
> Postgres search is essentially an easier to use regex engine.
I'm not sure exactly what you meant to convey here, but if you're searching with LIKE or `~` you're not doing Postgres's proper Full Text Search. You should be dealing with tsvectors[0]
> As soon as you need multiple languages
Postgres FTS supports multiple languages and you can create your own configurations[1]
> advanced autocomplete
I'm not sure what "advanced" autocomplete is but you can get pretty fast trigram searches going[2] (back to LIKE/ILIKE here but obviously this is an isolated usecase). In the end I'd expect auto complete results to actually not hit your DB most of the time (maybe I'm naive but that feels like a caching > cache invalidation > cache pushdown problem to me)
> misspelling detection
pg_similarity_extension[3] might be of some help here, but it may require some wrangling.
> large documents, large datasets,
PG has TOAST[4], and obviously can scale (maybe not necessarily great at it) -- see pg_partman/Timescale/Citus/etc.
> custom scoring
Postgres only has basic ranking features[5], but you can write your own functions and extend it of course.
Solr/ES are definitely the right tools for the job (tm) when the job is search, but you can get surprisingly far with Postgres. I'd argue that many usecases actually don't want/need a perfect full text search solution -- it's often minor features that turn into overkill fests and ops people learning/figuring out how to properly manage and scale an ES cluster and falling into pitfalls along the way.
[0]: https://www.postgresql.org/docs/current/textsearch-intro.htm...
[1]: https://www.postgresql.org/docs/current/textsearch-intro.htm...
[2]: https://about.gitlab.com/blog/2016/03/18/fast-search-using-p...
[3]: https://github.com/eulerto/pg_similarity
[4]: https://www.postgresql.org/docs/current/storage-toast.html
[5]: https://www.postgresql.org/docs/9.5/textsearch-controls.html...
supabase
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How I migrated from Firebase to Supabase
I didn't really give much thought as to which backend I would use. I already had 2 projects in Supabase (BOXCUT & MineWork), but also a few projects in Firebase too. I was more concerned at the time at actually building the product.
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How to get free Postgres
Sign up for SupaBase: Head over to SupaBase and sign up. Create a new workspace and project with your preferred names.
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Creating a Pokémon guessing game using Supabase, Drizzle, and Next.js in just 2 hours!
Setting up Supabase Create a new Supabase project, and get the connection string for the database from settings > database.
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How To Make An Insanely Fast AI App (Supabase, LLAMA 3 and Groq)
Supabase (start for free)
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Building a self-creating website with Supabase and AI
Built with Supabase, Astro, Unreal Speech, Stable Diffusion, Replicate, Metropolitan Museum of Art
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How I built a Markdown Rendered Blog using Supabase and Chakra UI
Supabase will be used for storing article data in the database and the cover image of the article in storage. Chakra UI will be used to provide style to the elements. By using both, we can build the blog with ease.
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I got #1 Product of the Day on Product Hunt without Spending a Dollar
For AutoRepurpose, I opted for Supabase as the backbone of the backend. It has reliably supported Penelope AI, which garnered over 15k users in 2022 without any issues.
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AI Inference now available in Supabase Edge Functions
Semantic search demo
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Creating an OG image using React and Netlify Edge Functions
1. Create a new Supabase project: Visit Supabase and create a new project.
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11 Planetscale alternatives with free tiers
Supabase positions itself as the "open source Firebase alternative." It was founded in 2020 and is a developer-friendly serverless database platform that supports over 20 frameworks, including popular tools like Next.js, React, Nuxt, Svelte, Flutter, and Vue.
What are some alternatives?
git-imerge - Incremental merge for git
Appwrite - Your backend, minus the hassle.
elasticsearch-py - Official Python client for Elasticsearch
pocketbase - Open Source realtime backend in 1 file
pgsentinel - postgresql extension providing Active session history
nhost - The Open Source Firebase Alternative with GraphQL.
mergify - Merge git changes on commit at a time.
neon - Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, branching, and bottomless storage.
git-mergify-rebase - Merge git changes one commit at a time.
next-auth - Authentication for the Web.
vasco - vasco: MIC & MINE statistics for Postgres
Hasura - Blazing fast, instant realtime GraphQL APIs on your DB with fine grained access control, also trigger webhooks on database events.