val-town-mirror
paradedb
| val-town-mirror | paradedb | |
|---|---|---|
| 2 | 20 | |
| 3 | 4,428 | |
| - | 12.8% | |
| 9.9 | 9.8 | |
| 14 days ago | 2 days ago | |
| TypeScript | Rust | |
| - | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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.
val-town-mirror
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Code Search Is Hard
Well this is fun...
git clone https://github.com/pomdtr/val-town-mirror
paradedb
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Tantivy – full-text search engine library inspired by Apache Lucene
Postgres's FTS is actually quite solid! You can get very far with just the built-in tsvector. The ranking could be improved, though, which was one of the reasons for creating pg_search in the first place: https://github.com/paradedb/paradedb/tree/dev/pg_search (disclaimer: I work on pg_search @ ParadeDB)
- Pg_lakehouse: Query Any Data Lake from Postgres
- Using ClickHouse to scale an events engine
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Code Search Is Hard
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)
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Ask HN: Best way to mirror a Postgres database to parquet?
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.
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Transforming Postgres into a Fast OLAP Database
You're right. We're working on this currently. You can track the issue here: https://github.com/paradedb/paradedb/issues/717
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We built our customer data warehouse all on Postgres
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 :)
- Show HN: Pg_analytics – Speed Up Postgres Analytical Queries by 94x
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Multi-Database Support in DuckDB
Check out https://github.com/paradedb/paradedb/tree/dev/pg_analytics, we're shipping this week
What are some alternatives?
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
tantivy - Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
prism - Prism is the easiest way to develop, orchestrate, and execute data pipelines in Python.
retake - PostgreSQL for Search [Moved to: https://github.com/paradedb/paradedb]
bionicgpt - BionicGPT is an on-premise replacement for ChatGPT, offering the advantages of Generative AI while maintaining strict data confidentiality [Moved to: https://github.com/bionic-gpt/bionic-gpt]
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
pgrx - Build Postgres Extensions with Rust!
Nuclia DB - NucliaDB, The AI Search database for RAG
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
tinyvector - A tiny embedding database in pure Rust.
lnx - ⚡ Insanely fast, 🌟 Feature-rich searching. lnx is the adaptable, typo tollerant deployment of the tantivy search engine.
NeumAI - Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.