Usage

VectorChord’s index type vchordrq divides vectors into lists and searches only a subset of lists closest to the query vector. It provides fast build time and lo

Multi-Vector Retrieval is an advanced technique used in Retrieval-Augmented Generation (RAG) systems to enhance document retrieval by leveraging multiple vector

VectorChord’s index type vchordg is a disk-based graph index. It has low memory consumption.

Quantization can be applied not only to indexes but also directly to vectors. To this end, VectorChord provides data types for quantized vectors.

Usually, ORDER BY and LIMIT clauses are used to perform vector search. In some cases, you may want to use a WHERE clause to filter out vectors that are far from

Indexing may be parallelized. Parallelism increases server load and is therefore not enabled by default in PostgreSQL. To enable it, refer to the following SQL.

You can monitor the progress of building a PostgreSQL index by querying the pgstatprogresscreateindex view.

Search parameters are typically configured via GUCs. VectorChord also offers an alternative method, allowing these parameters to be attached directly to an inde

In the context of vector search, recall is the ratio of true nearest neighbors to approximate nearest neighbors returned by the index. For example, if the index

After PostgreSQL starts, tables and indexes are loaded from storage into the buffer pool only when they are accessed for the first time. As queries are executed

In a filtered index scan, the index performs the scan first and then PostgreSQL checks whether the filter conditions are satisfied. On this page, “filter” refer

Prefetch dramatically accelerates queries that involve I/O operations. It works by proactively reading buffers into operating system page cache or PostgreSQL’s

PostgreSQL indexes store row identifiers and the values of the indexed columns. Typically, indexed columns have simple data types, for example, integers or stri

For large tables, the partitioning phase dominates both build time and memory consumption.

In addition to using the methods in Partitioning Tuning to achieve shorter build time and lower memory consumption at the cost of QPS and recall, you can also c