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Pgvectorscale Alternatives
Similar projects and alternatives to pgvectorscale
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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ollama
Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, Mistral Small 3.1 and other large language models.
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shadcn/ui
A set of beautifully-designed, accessible components and a code distribution platform. Works with your favorite frameworks. Open Source. Open Code.
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TimescaleDB
A time-series database for high-performance real-time analytics packaged as a Postgres extension
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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paradedb
ParadeDB is a modern Elasticsearch alternative built on Postgres. Built for real-time, update-heavy workloads.
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ai
The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents
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pgai
A suite of tools to develop RAG, semantic search, and other AI applications more easily with PostgreSQL
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pgaidocs
Discontinued [GET https://api.github.com/repos/timescale/pgaidocs: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository]
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DiskANN
Graph-structured Indices for Scalable, Fast, Fresh and Filtered Approximate Nearest Neighbor Search
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testcontainers-node
Testcontainers is a NodeJS library that supports tests, providing lightweight, throwaway instances of common databases, Selenium web browsers, or anything else that can run in a Docker container.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better pgvectorscale alternative or higher similarity.
pgvectorscale discussion
pgvectorscale reviews and mentions
Posts with mentions or reviews of pgvectorscale.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2025-05-01.
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Connecting S3 and Postgres: Automatic Synchronization Without ETL Pipelines
AI applications using RAG (retrieval-augmented generation) can help businesses unlock insights from mountains of unstructured data. Today, that unstructured data’s natural home is Amazon S3. On the other hand, Postgres has become the default vector database for developers, thanks to extensions like pgvector and pgvectorscale. These extensions enable them to build intelligent applications with vector search capabilities without needing to use a separate database just for vectors.
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Postgres vs. Qdrant: Why Postgres Wins for AI and Vector Workloads
We’re releasing a new benchmark that challenges the assumption that you can only scale with a specialized vector database. We compared Postgres (with pgvector and pgvectorscale) to Qdrant on a massive dataset of 50 million embeddings. The results show that Postgres not only holds its own but also delivers standout throughput and latency, even at production scale.
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Reliably Replicating Data Between PostgreSQL and ClickHouse
I've been very confused by the timeseries branding - I had always thought timescale was purely about adding time series features to PostgreSQL. I didn't know the extension had other applications.
Looks like you've expanded into vector indexing - https://github.com/timescale/pgvectorscale - and an extension which bakes RAG patterns (including running prompts from SQL queries) into PostgreSQL: https://github.com/timescale/pgai
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TimescaleDB in 2024: Making Postgres Faster
If I had to summarize 2024 for Timescale, I’d call it the year of Postgres for AI. From game-changing open-source launches like pgvectorscale (a performance booster for large production vector workloads with PostgreSQL + pgvector) to pgai (which integrates Postgres with LLMs for AI app development), we pushed the boundaries of what developers can achieve with Postgres. But AI wasn’t the only story. TimescaleDB’s time-series capabilities also evolved dramatically during 2024, making Postgres even faster for real-time analytics.
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Tutorial: How We Built a Reverse Video Search System Directly in PostgreSQL
The pgvectorscale extension builds on top of pgvector, enabling PostgreSQL to efficiently store and query vector embeddings. You might wonder why you should upgrade from PostgreSQL with pgvector to Timescale Cloud’s AI stack (pgai, pgvectorscale, and pgai Vectorizer). Here’s why:
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Local AI Knowledge Base with Next.js, Ollama, and PostgreSQL
pgvectorscale for scaling vector similarity search Query embeddings for RAG
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Join us for the Open Source AI Challenge with pgai and Ollama: $3,000 in Prizes!
Your mandate is to build an AI application using open-source tools and the open-source database PostgreSQL as your vector database, using two or more of the following related tools: pgvector, pgvectorscale, pgai, and pgai Vectorizer.
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PGVector's Missing Features
This is probably the most fair point in the post. But there exists projects like pg_search from ParadeDB which bring bm_25 to Postgres and help solve this [2]
Lastly, I respect companies trying to provide real-world examples of the trade-offs of different systems, and so thank the authors for sharing their experience and spurring discussion.
Disclaimer: I work at Timescale, where we offer pgvector, and also made other extensions for AI/ vector workloads on PostgreSQL, namely pgvectorscale, and pgai. I've tried to be as even in my analysis as possible but as with everything on the internet, you can make up your own mind and decide for yourself.
[0]: https://github.com/timescale/pgvectorscale/
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Implementing a RAG system inside an RDBMS: Sqlite and Postgres with Sqlite-vec, PGVector.
PG-Vector-scale is a super fast iteration on PGVector, intended for really large deployments where the PGVector might hit performance or scale limitations. It is also addresses scalability for large datasets, distributed indexing and querying and handling billions of vectors with efficiency. As I write this, it's not clear whether there are circumstances where it makes sense to use PGVector at all, hopefully as I dig into it, it will become clear.
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SpringAI, llama3 and pgvector: bRAGging rights!
While writing this post pgvectorscale got released. It's an interesting new project that makes pgvector much more performant and cost-effective. Planning to try it out!
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A note from our sponsor - InfluxDB
www.influxdata.com | 21 May 2025
Stats
Basic pgvectorscale repo stats
13
1,976
8.6
2 days ago
timescale/pgvectorscale is an open source project licensed under PostgreSQL License which is an OSI approved license.
The primary programming language of pgvectorscale is Rust.
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InfluxDB – Built for High-Performance Time Series Workloads
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