Timescale

?? ?????????? ?????????????????? ???? ?????? ???? ???? ?????????????????? -??????????????????????? ???????? ???????????????????? No need for specialized tools or vector databases—pgai Vectorizer lets you create, sync, and manage embeddings with just one SQL command. ?? ???????????????????? ???? ????????????????: Build, store, and sync embeddings alongside your relational data—no extra infrastructure needed. ?? ????????-???????? ????????, ?????????? ??????????????: Keep embeddings fresh as your data changes. Test models instantly. ?? ?????? ???? ????????????????: Everything you need—embeddings, model access, and AI workflows—all with the SQL you already know. #Postgres #pgaiVectorizer #Postgres #Data #AI #SQL #DevTools #AIDevelopment #PostgresExtensions #AIinSQL

? Compression is your next move, here is why: If you’re managing large datasets and not leveraging compression, you’re missing out on a powerful optimization tool. As someone who’s seen firsthand how compression transforms database management, I can confidently say it’s a must-have for anyone dealing with time-series or large-scale data workloads. Compression doesn’t just save storage space—it dramatically reduces costs and can even improve query performance by minimizing I/O bottlenecks. With Timescale’s advanced lossless compression algorithms, you can achieve up to 97% compression rates without losing any data integrity. Seeing this live across my book of business! The result? A leaner, faster, and more cost-efficient database that’s ready to handle your growing needs. Whether you’re scaling a critical application or optimizing costs in the cloud, compression makes it possible to do more with less. If you haven’t enabled compression yet, now’s the time to explore its benefits. Let me know if you’d like guidance on implementing it effectively—your data (and your budget) will thank you! https://lnkd.in/g_SVmVW2 #DataCompression #OptimizeYourDatabase #TimescaleDB

Hello #Ruby friends, this is part of my open source work at Timescale. Improving the Ruby integration to make it very very easy to build statistics from your Rails app directly from the database. In this blog, I explain how to use a new macro I introduced to the timescaledb gem. Making it easy to build dashboards for your Ruby On Rails application with the performance that Timescaledb offers ?? Enjoy, and happy coding ??

We had a killer friendsgiving last week with Timescale at the betaworks Studio. We had ?? Avthar Sewrathan present his talk, Vector Databases are the Wrong Abstraction. We got to dive into the turkey and stuffing a week early! In addition we had the pleasure of having Jason Gardner and Kent G. give talks on how they are using databases in their projects. Thanks to the whole Timescale team for making this evening possible, as well as always to betaworks for being an awesome space/partner for our events. Applications are open for Betawork's next cohort of Camp, their thematic investment and in-residence program. They're focusing on the AI App-Layer, if you're building check it out! https://lnkd.in/ep4SMkEh Speaking of turkey, I hope everyone on my feed has a great Thanksgiving, enjoy the time with your families and see you for more events in December. Nicole Ripka Isabel M.

I love it when stuff like this happens, my INSERT...UNNEST performance post seems to have stirred up the #django community and they are getting a patch ready to optimize #PostgreSQL batch inserts!

I've been benchmarking again, this time zooming out to #PostgreSQL batch ingest performance (the many permutations of INSERT vs COPY). I even made a custom #rust CLI to do it. I'd love to hear your thoughts!

?????????????????? ???????????? ???????????????? ???? ???????? ????????????????????: https://lnkd.in/g4Fa9Z7q "While specialized vector databases or bolted-on systems require complex setups and specialized expertise, pgai Vectorizer delivers a seamless, high-performance experience that goes beyond vector search, built entirely on PostgreSQL." #timescale #enterprise #ai #postgresql

Worked with J?natas Paganini this morning on getting Timescale into postgres.pm, the universal package manager for Postgres. We are both excited about fixing the state of the extension installation for Postgres, and I am happy that the TimescaleDB extension is now in! https://lnkd.in/gRuwDjna

I originally wrote this blog and now Hervé Ishimwe brought an update to simplify the process with vectorizer. Amazing to see how seamless is becoming integration between data and vector! Little building blocks that makes dev life easier ??

The best AI engineers know that stale embeddings kill RAG apps. Here's how to never worry about managing and syncing embeddings again. With pgai Vectorizer, you can power your RAG app with just Posgres, and your embeddings stay in sync with source data automatically - just like a database index. No more stale embeddings. No more complex pipelines. Just SQL.