Co-founder of TensorChord and original co-author of pgvecto.rs and vchord. Follow on GitHub (@gaocegege).
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Do we really need a specialized vector database? (2023)
Notice: This article, originally published in 2023, discusses the relevance and necessity of specialized vector databases, particularly in relation to Postgres and its capabilities. For further insights and discussions on this topic, please refer to …
Notice: This article, originally published in 2023, discusses the relevance and necessity of specialized vector databases, particularly in relation to Postgres and its capabilities. For further insights and discussions on this topic, please refer to …
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VectorChord: Store 400k Vectors for $1 in PostgreSQL
We’re pleased to announce our new vector search extension for PostgreSQL, providing a highly cost-effective way to manage large vectors. Using VectorChord, you can achieve a QPS of 131 with 0.95 precision on 100 million 768-dimensional vectors for …
We’re pleased to announce our new vector search extension for PostgreSQL, providing a highly cost-effective way to manage large vectors. Using VectorChord, you can achieve a QPS of 131 with 0.95 precision on 100 million 768-dimensional vectors for …
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Introducing PGVecto.rs Cloud - Scalable Vector Search in PostgreSQL, Now in the Cloud
In an exciting development, we are thrilled to announce the launch of PGVecto.rs Cloud - bringing the power of scalable vector search to your PostgreSQL databases, now available as a fully managed cloud service. PGVecto.rs is a pioneering Postgres …
In an exciting development, we are thrilled to announce the launch of PGVecto.rs Cloud - bringing the power of scalable vector search to your PostgreSQL databases, now available as a fully managed cloud service. PGVecto.rs is a pioneering Postgres …
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My binary vector search is better than your FP32 vectors
Within the field of vector search, an intriguing development has arisen: binary vector search. This approach shows promise in tackling the long-standing issue of memory consumption by achieving a remarkable 30x reduction. However, a critical aspect …
Within the field of vector search, an intriguing development has arisen: binary vector search. This approach shows promise in tackling the long-standing issue of memory consumption by achieving a remarkable 30x reduction. However, a critical aspect …
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pgvector vs. pgvecto.rs in 2024: A Comprehensive Comparison for Vector Search in PostgreSQL
pgvector and pgvecto.rs are both vector search extensions designed to enhance the capabilities of PostgreSQL. These extensions revolutionize the way vector search is performed within the database, providing scalable, low-latency, and hybrid-enabled …
pgvector and pgvecto.rs are both vector search extensions designed to enhance the capabilities of PostgreSQL. These extensions revolutionize the way vector search is performed within the database, providing scalable, low-latency, and hybrid-enabled …
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Do we really need a specialized vector database?
With the popularity of LLM (Large Language Model), vector databases have also become a hot topic. With just a few lines of simple Python code, a vector database can act as a cheap but highly effective “external brain” for your LLM. But do we really …
With the popularity of LLM (Large Language Model), vector databases have also become a hot topic. With just a few lines of simple Python code, a vector database can act as a cheap but highly effective “external brain” for your LLM. But do we really …
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Building the RAG pipeline with LlamaIndex and pgvecto.rs
LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs). pgvecto.rs provides a LlamaIndex integration that allows you to retrieve the most similar vectors. In this blog post, we will show you …
LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs). pgvecto.rs provides a LlamaIndex integration that allows you to retrieve the most similar vectors. In this blog post, we will show you …
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Building LLM Applications in LangChain using pgvecto.rs
LangChain is a framework for developing applications powered by language models. It enables applications that: Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response …
LangChain is a framework for developing applications powered by language models. It enables applications that: Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response …
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pgvecto.rs 0.2: Unifying Relational Queries and Vector Search in PostgreSQL
We are excited to announce the release of pgvecto.rs 0.2, a significant milestone in the journey of bridging the gap between relational queries and vector search in PostgreSQL. This update brings together the power of both worlds, offering enhanced …
We are excited to announce the release of pgvecto.rs 0.2, a significant milestone in the journey of bridging the gap between relational queries and vector search in PostgreSQL. This update brings together the power of both worlds, offering enhanced …