🔊 New blog post: Part 2 of the “Creating a full-text search engine using PostgreSQL” series. In this one we are comparing the Postgres search functionality to Elasticsearch.
https://t.co/8k9vY2WSsT
🔊New blog post: Creating an advanced search engine with PostgreSQL.
https://t.co/aPHTh2412q
Here is the tl;dr:
PostgreSQL’s approach to full-text search is to offer the building blocks that you can use to create your own search engine. It provides functions to parse and analyze documents, a data type to represent user queries, and a match operator. You can make it fast using GIN (Generalized Inverted Index) and sort the results using ranking functions based on term frequency.
For more advanced search capabilities, like those found in search engines such as @elastic , @typesense , or @meilisearch, you can combine the above primitives with other Postgres functionality: computed columns, sorting options, functions, materialized views.
This blog post shows how to implement column weights, relevancy boosters, typo tolerance, and faceted search. Suggesters/autocomplete, exact phrase matching, and semantic or hybrid search are also possible.
In part 2, we’ll make a comparison to Elasticsearch and dive into when it's best to use only Postgres and when to sync data to a search engine.
🎉 Full house! Join us in welcoming the newest members of Team Weaviate!
🤝 Ara - People & Culture, People Operations Manager
🎯 Emma - Customer Success, Head of Customer Success
🚀 @helloiamleonie - DevGrowth, Developer Advocate
💻 @Asdine_ - Applied Research Software Engineer
Postgres schema changes are still a PITA.
There, we said it. Navigating between table locking, downtime risk, and manual steps is difficult and time consuming.
This blog post lists the gotchas, the workarounds, and a wild idea on how to fix it all.
https://t.co/JQmYDgNsO4
At Xata, we are building the #database for the next generation of builders and applications. Our latest blog dives into what we believe the builder of tomorrow will look like, and the type of database they'll expect 🦋
https://t.co/h7AE407OrN
New blog post: How we implemented database renaming
Read about our DynamoDB data migration story, which we needed to support database renames.
https://t.co/yi9Qavyxgm
Introducing the new Xata developer workflow, featuring integrations with @GitHub, @Vercel & @Netlify 🎉
→ git-like branching in the CLI
→ A database branch for each PR
→ Status comments and checks in GitHub
→ DB migrations applied on merge
https://t.co/eus3Bfi9od
Ruby serenaded me into a career as a programmer. Before Ruby, code was a means to an end. After Ruby, code was flow, growth, and the greatest intellectual endeavor I’ve ever found. I love Ruby as much today as when we first met in ‘03. Thank you @yukihiro_matz. Happy #ruby30th ❤️
Say hello to our new, overhauled code search ranking for OSS repos on https://t.co/4J5rrvuJbX.
This new search ranking uses the Google PageRank algorithm on source code, helping you find the most relevant answers and the most reusable code. https://t.co/ltEGm3jvd4
We now use PageRank for better code search relevance: https://t.co/igGKfzovJA (via @Steve_Yegge). Early results are awesome.
PageRank on the web models a random surfer.
PageRank on code models code reuse.
PageRank on the web uses links.
PageRank on code needs the code graph.
Something fun we hacked together recently at @sourcegraph: supporting precise code nav for untyped Ruby code.
Have you ever wanted to dive into the @MacHomebrew codebase but found it a bit overwhelming? Now you can do so directly from your browser. :)
https://t.co/fuBv88VTWh