Introducing Crunchy Data Warehouse: A next-generation Postgres-native data warehouse. Crunchy Data Warehouse Learn more
Elizabeth Christensen
I can’t get through a zoom call, a conference talk, or an afternoon scroll through LinkedIn without hearing about vectors. Do you feel like the term vector is everywhere this year? It is. Vector actually means several different things and it's confusing. Vector means AI data, GIS locations, digital graphics, and a type of query optimization, and more. The terms and uses are related, sure. They all stem from the same original concept. However their practical applications are quite different. So...
Read MorePaul Ramsey
Paul Ramsey
"Retrieval Augmented Generation" (RAG) is a useful technique in working with large language models (LLM) to improve accuracy when dealing with facts in a restricted domain of interest. Asking an LLM about Shakespeare: works pretty good. The model was probably fed a lot of Shakespeare in training. Asking it about holiday time off rules from the company employee manual: works pretty bad. The model may have ingested a few manuals in training, but not yours ! Is there a way around this LLM limi...
Read MorePaul Ramsey
Paul Ramsey
Large language models (LLM) provide some truly unique capacities that no other software does, but they are notoriously finicky to run, requiring large amounts of RAM and compute. That means that mere mortals are reduced to two possible paths for experimenting with LLMs: • Use a cloud-hosted service like OpenAI . You get the latest models and best servers, at the price of a few micro-pennies per token. • Use a small locally hosted small model. You get the joy of using your own hardware, and on...
Read MoreChristopher Winslett
Christopher Winslett
Over the past 12 months, AI has taken over budgets and initiatives. Postgres is a popular store for AI embedding data because it can store, calculate, optimize, and scale using the pgvector extension . A recently introduced gem to the Ruby on Rails ecosystem, the neighbor gem, makes working with pgvector and Rails even better. An “embedding” is a set of floating point values that represent the characteristics of a thing (nothing new, we’ve had these since the 70s). Using the OpenAI API or any o...
Read MoreChristopher Winslett
Christopher Winslett
Postgres’ pgvector extension recently added HNSW as a new index type for vector data. This levels up the database for vector-based embeddings output by AI models. A few months ago, we had written about approximate nearest neighbor pgvector performance using the available list-based indexes . Now, with the addition of HNSW, pgvector can use the latest graph based algorithms to approximate nearest neighbor queries. As with all things databases, there are trade-offs, so don’t throw away the list...
Read MoreChristopher Winslett
Christopher Winslett
Note: We have additional articles in this Postgres AI series . Vector data has made its way into Postgres and I’m seeing more and more folks using it by the day. As I’ve seen use cases trickle in, I have been thinking a lot about scaling data and how to set yourself up for performance success from the beginning. The two primary trade-offs are performance versus accuracy. When seeking performance with vector data, we are using nearest neighbor algorithms, and those algorithms are built around p...
Read MoreCraig Kerstiens
Craig Kerstiens
We are happy to unveil the newest release of Crunchy Postgres for Kubernetes version 5.4. This update brings an array of features set to improve your experience including: • Support for ARM • Native vector search via pgvector • Comprehensive support for huge pages • Native support for Postgres tablespaces • Documentation enhancements Support for ARM Native vector search via pgvector Comprehensive support for huge pages Native support for Postgres tablespaces Documentation enhancements To explo...
Read MoreCraig Kerstiens
Craig Kerstiens
There's a lot of excitement around AI, and even more discussion than excitement. The question of Postgres and AI isn't a single question, there are a ton of paths you can take under that heading... • Can I use Postgres for building AI related apps? Absolutely . • Can Postgres become an autonomous database with AI? Maybe. • Should you use AI to help you troubleshoot issues? Perhaps, but better left to experts. • Should I avoid AI when working with my database? Not at all! Can I use Postgres for...
Read MoreChristopher Winslett
Christopher Winslett
Note: pgvector 0.5 released HNSW indexes which improved performance significantly. Read more about it HNSW Indexes with Postgres and pgvector . We have additional articles in this Postgres AI series . As we've been helping people get started with AI in Postgres with , there have been few questions around performance. At a basic level, pgvector performance relies on 3 things: 1. Are your queries using indexes? 2. Are you setting your size appropriately for your data set? 3. Do you have enoug...
Read MoreChristopher Winslett
Christopher Winslett
Note: We have additional articles in this Postgres AI series . In the past month at Crunchy Data , we have talked to a steady stream of customers & community folks wanting to know how to augment their data platforms for AI. Fortunately, Postgres is equipped, nearly out of the box, and ready for the task of storing and querying this data. Through the magic of OpenAI’s API we can easily send data for classification and return the values. Alongside this post, I created a sample code-base and dat...
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