Sarah Conway

Tech Evangelist, Developer Advocate, Tech Writer, & Marketing Consultant || Owner @ Talk to Me About Tech 🤖 || Follow for tips using tech for success ✨

[Sarah Conway @xenophenes]

For a look into what I'm up to these days (all things #community and #PostgreSQL, as always - and now throwing a #rabbitrescue into the mix!), check out the latest from Doug Ortiz of TechBits - what a fun #podcast episode this was to record!

https://t.co/TmJsID4msL

[Ajay Kulkarni @acoustik]

🔥 𝗘𝘃𝗲𝗿𝘆 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗶𝘀 𝗻𝗼𝘄 𝗮𝗻 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿: 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗽𝗴𝗮𝗶 𝗩𝗲𝗰𝘁𝗼𝗿𝗶𝘇𝗲𝗿 🔥

𝗽𝗴𝗮𝗶 𝗩𝗲𝗰𝘁𝗼𝗿𝗶𝘇𝗲𝗿 is a developer tool that automatically creates and syncs embeddings right in your PostgreSQL database.

In other words: 𝗽𝗴𝗮𝗶 𝗩𝗲𝗰𝘁𝗼𝗿𝗶𝘇𝗲𝗿 𝗺𝗮𝗸𝗲𝘀 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗮𝘀 𝗲𝗮𝘀𝘆 𝗮𝘀 𝗰𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝗮𝗻 𝗶𝗻𝗱𝗲𝘅 𝗶𝗻 𝗣𝗼𝘀𝘁𝗴𝗿𝗲𝗦𝗤𝗟.

Available 100% open source (PostgreSQL license) and via our Cloud offering.

With pgai, we are building the first and only developer suite 𝘪𝘯𝘴𝘪𝘥𝘦 𝘵𝘩𝘦 𝘥𝘢𝘵𝘢𝘣𝘢𝘴𝘦 for building AI applications.

Why are we doing this? To make every engineer an AI engineer, by embracing and extending PostgreSQL, the most loved database by developers.

Serve every developer, power the future of computing, and advance the human frontier.

Let's go!! 🤖 🐘 🚀

[Avthar @avthar]

VECTOR DATABASES ARE THE WRONG ABSTRACTION. Here’s a better way: introducing pgai Vectorizer, a new open-source PostgreSQL tool that automatically creates and syncs embeddings with source data, just like a database index.

❌ Why vector databases fail
Vector databases treat embeddings as independent data, divorced from the source data from which embeddings are created, rather than what they truly are: derived data.

This pitfall means that many AI projects that start out as simple vector search implementations inevitably evolve into a complex orchestra of monitoring, synchronization, and firefighting.

😓 Keeping embeddings in-sync is hard
In an attempt to avoid stale embeddings, engineering teams have to build and maintain a maze of ETL pipelines, juggle multiple databases (vector DB, metadata store, lexical search), and manage complex queuing systems for updates.

Add monitoring for data drift, alert systems for stale results, and validation checks across systems - and you have a brittle infrastructure that inevitably breaks down, leading to stale embeddings and wasted engineering hours.

What if you could just use Postgres instead?

✅ Pgai Vectorizer: Vector embeddings as database indexes
Pgai Vectorizer treats embeddings like database indexes. It automatically creates, updates, and maintains embeddings as your data changes. Just like an index, the database handles all the complexity: syncing, versioning, and cleanup happen automatically.

This means no manual tracking, zero maintenance burden, and the freedom to rapidly experiment with different embedding models and chunking strategies without building new pipelines.

🤔Why did we build pgai Vectorizer?
Our team at @timescaledb built pgai Vectorizer because many developers regard PostgreSQL as the “Swiss army knife” of databases, as it can handle everything from vectors and text data to JSON documents.

We think an “everything database” like PostgreSQL is the solution to eliminate the nightmare of managing multiple databases, making it the ideal home for vectorizers and the foundation for AI applications.

⚙️How does pgai Vectorizer work?
Check out the code snippet below –  it takes just 6 lines of SQL to put your embedding creation pipeline on autopilot with pgai Vectorizer!

Under the hood, pgai Vectorizer checks for modifications to the source table (inserts, updates, and deletes) and asynchronously creates and updates vector embeddings in an external worker.

🧑‍💻 Sounds exciting! How can I get started?
Pgai Vectorizer is open-source under the PostgreSQL license and available for free to use on any PostgreSQL database. You can find installation instructions on the pgai GitHub repository (see end of post). It’s also available as a managed service in Timescale’s PostgreSQL cloud platform.

📚Learn more
[1] Pgai github repo: https://t.co/hut1MxuwPZ
[1] Technical explainer post: https://t.co/A9hOz482Rg

Share this post with your followers to let them know about pgai Vectorizer and comment your reactions and questions.

[TimescaleDB (by Tiger Data) @TimescaleDB]

🛑 Vector Databases Are the Wrong Abstraction. Here’s Why.

They treat embeddings as standalone data, disconnected from their source, leading to outdated embeddings, constant sync issues, and endless maintenance.

That’s why we built pgai Vectorizer for Postgres—so every engineer can build AI applications without the headache of managing embedding pipelines. Creating an embedding pipeline is as easy as building an index. It stays synced with your data automatically—no extra tools, no stale embeddings.

👉 Whether you’re a busy AI engineer or just getting started, check out the blog to see how pgai Vectorizer lets you focus on building killer AI apps. 🔗👇

#Postgres #pgaiVectorizer #Postgres #Data #AI #SQL #DevTools #AIDevelopment #PostgresExtensions #AIinSQL

[TimescaleDB (by Tiger Data) @TimescaleDB]

🎙️ "What I really like about it is the consistency; that people really managed to build something great over 30 years." - Hans Jürgen Schönig, CEO of Cybertec.

In this interview, Hans shares what makes PostgreSQL special, but also what could improve—review bandwidth. Have thoughts? Take the State of PostgreSQL survey before October 31st!

👉 https://t.co/DqFoQEdS2d

#PostgreSQL #CommunitySurvey #Timescale
@postgresql_007

[Data Egret | PostgreSQL support @dataegret]

We are thrilled to announce our partnership with @TimescaleDB for the 2024 State of Postgres Survey that aims to gain insights into usage of PostgreSQL provide ideas to how we can collaboratively enhance it. Shape the future of PostgreSQL, take the survey https://t.co/CLrwuNhBmO

[Sarah Conway @xenophenes]

Calling all #PostgreSQL users - if you haven't taken the 2024 State of Postgres survey yet, *please* take a moment to do so before Sept 30! All feedback - whether you're inexperienced or have been working with #Postgres for a very long time - helps. https://t.co/HtFGrIYM21

[Gülçin Yıldırım Jelínek 🪩 @apatheticmagpie]

📝 I’ve just submitted my response to the State of PostgreSQL 2024 survey! 🎉 🐘 It was super easy to fill out, and I loved how the questions balanced everything from Postgres use cases and features to community and extensions. The final focus on AI was a nice touch! 1/5

[Data Egret | PostgreSQL support @dataegret]

The 2024 State of Postgres is now open for voting until the end of September! Curious about how #Postgres is being used? Take part in the survey—it only takes 15 minutes! #StateofPostgres #survey #opensource #database @TimescaleDB https://t.co/CLrwuNh3xg

[Sarah Conway @xenophenes]

Introducing pg_duckdb: an #OpenSource project (MIT licensed) that will bring #DuckDB to #PostgreSQL - backed by @DuckDB/@DuckDBLabs, @Microsoft, @HydraDatabase, @NeonDatabase, & more. A powerful new #extension being added to #Postgres' bountiful ecosystem. https://t.co/rPjwpQAwG4

[Sarah Conway @xenophenes]

#PostgreSQL engineers, devs, DBAs, consultants, experts: here's a latest job posting for you, courtesy of the Hive Collective. #Remote work supported within the US.

#dev #dba #jobhunt #jobsearch #postgres #opensource #workfromhome #remotejobs #workremotely

[Sarah Conway @xenophenes]

"...it’s easy to think of databases like a black box where you make sure your tables are indexed sensibly and your queries aren’t doing anything silly, and the rest just happens." So how does it work, really?

https://t.co/yHAWGegbzX

#data #datamanagement #postgres #postgresql

[Sarah Conway @xenophenes]

Missed the original announcement, but seems major changes are coming about now in Google's Android app store in consequence of them engineering their Play Store as an illegal monopoly.

https://t.co/K7GlrLC4Ck

#technews #business #businessnews #google #android

[Sarah Conway @xenophenes]

Learning more about #RDBMS vs #NoSQL database types (or related)? This should help:

https://t.co/eOMwAMdXL6

#learntech #database #dev #data #datamanagement

[Sarah Conway @xenophenes]

Been a long time coming, but glad it's finally been made official! (Though, the fines should be higher.)

https://t.co/uXxgT9o8md

#technews #ai #legal #ecommerce #business #businessnews

[Sarah Conway @xenophenes]

#CockroachDB (distributed transactional system) plans to retire its open source "Core" product in favor of a new Enterprise licensing structure for self-hosted users after the introduction of version 24.3 in November: https://t.co/UmU3m08OYA

#opensource #foss #technews

[David Rowley @davidrowley_pg]

One of the things I'm working on for PostgreSQL 18 is executor performance. Today I pushed a patch to add JIT support to increase the performance of generating hash values for Hash Join. Thanks to @AndresFreundTec for letting me know this needed attention. https://t.co/CEyKebKC25

[Jeremy Schneider @jer_s]

Everybody can support Postgres today.

Take 5 minutes and pop a quick email to your Microsoft and AWS sales reps, telling them that their company's support of open source postgres development matters to you.

Its good for field teams to hear this feedback; don't assume they know!

[Felt @felt]

Join geospatial expert, @michalmigurski, for a 30 minute webinar on building a modern GIS stack with @SnowflakeDB and Felt this Wednesday, Aug 21. Reserve your spot now!
https://t.co/Qd6Rd28NtO

[Sarah Conway @xenophenes]

The GitOps template for #ArgoCD went #OpenSource:
https://t.co/Y1t8mhYII6

👏 #foss #dev #gitops

[Felt @felt]

Using @SnowflakeDB for your cloud data warehousing needs? You can now combine #SnowflakeDB with #Felt for a modern approach to geospatial data management, visualization, & collaboration. Learn more at our upcoming free webinar this Weds, Aug 21: https://t.co/oyv0IPneRg

#geospatial #gis #snowflake #datalake #webinar