docs: Refine readme (#274)

* update readme Signed-off-by: Jinjing.Zhou <[email protected]> * Refined pgvecto.rs features and documentation Signed-off-by: Jinjing.Zhou <[email protected]> * Fix formatting in README.md Signed-off-by: Jinjing.Zhou <[email protected]> * Update pgvecto.rs capabilities Signed-off-by: Jinjing.Zhou <[email protected]> --------- Signed-off-by: Jinjing.Zhou <[email protected]>
tensorchord · Jan 16, 2024 · 0e5fb8b · 0e5fb8b
1 parent 30a0f70
commit 0e5fb8b
Showing 1 changed file with 10 additions and 21 deletions.
diff --git a/README.md b/README.md
@@ -13,25 +13,14 @@ pgvecto.rs is a Postgres extension that provides vector similarity search functi
 
 ## Why use pgvecto.rs
 
-- 💃 **Easy to use**: pgvecto.rs is a Postgres extension, which means that you can use it directly within your existing database. This makes it easy to integrate into your existing workflows and applications.
-- 🔗 **Async indexing**: pgvecto.rs's index is asynchronously constructed by the background threads and does not block insertions and always ready for new queries.
-- 🥅 **Filtering**: pgvecto.rs supports filtering. You can set conditions when searching or retrieving points. This is the missing feature of other postgres extensions.
-- 🧮 **Quantization**: pgvecto.rs supports scalar quantization and product qutization up to 64x.
-- 🦀 **Rewrite in Rust**: Rust's strict compile-time checks ensure memory safety, reducing the risk of bugs and security issues commonly associated with C extensions.
-
-## Comparison with pgvector
-
-|                                             | pgvecto.rs                                             | pgvector                |
-| ------------------------------------------- | ------------------------------------------------------ | ----------------------- |
-| Transaction support                         | ✅                                                      | ⚠️                       |
-| Sufficient Result with Delete/Update/Filter | ✅                                                      | ⚠️                       |
-| Vector Dimension Limit                      | 65535                                                  | 2000                    |
-| Prefilter on HNSW                           | ✅                                                      | ❌                       |
-| Parallel HNSW Index build                   | ⚡️ Linearly faster with more cores                      | 🐌 Only single core used |
-| Async Index build                           | Ready for queries anytime and do not block insertions. | ❌                       |
-| Quantization                                | Scalar/Product Quantization                            | ❌                       |
-
-More details at [pgvecto.rs vs. pgvector](https://docs.pgvecto.rs/faqs/comparison-pgvector.html)
+- 💃 **User-Friendly**: Effortlessly incorporate pgvecto.rs into your existing database as a Postgres extension, streamlining integration with your current workflows and applications.
+- 🥅 **Join and Filter without Limitation**: Elevate your search capabilities in pgvecto.rs with VBASE filtering. Apply any filter conditions and join with other tables, achieving high recall and low latency, a distinctive edge over other vector databases.
+- 🌓 **Efficient FP16 Support**: Optimize your data storage with pgvecto.rs, supporting FP16 vector type to cut memory and storage usage by half, and boosting throughput.
+- 🧮 **Advanced Quantization**: Utilize scalar and product quantization in pgvecto.rs for up to 64x compression. Achieve up to 4x memory savings with less than 2% recall loss with scalar quantization.
+- 🔍 **Hybrid Search**: Leverage the full-text search functionality in PostgreSQL with pgvecto.rs to search text and vector data within a single query.
+- 🔗 **Async indexing**: The pgvecto.rs index is built asynchronously by background threads, allowing non-blocking inserts and always ready for new queries.
+- ⬆️ **Extended Vector Length**: pgvecto.rs supports vector length up to 65535, suitable for the latest models.
+- 🦀 **Rust-Powered Reliability**: Rust's strict compile-time checks ensure memory safety, reducing the risk of bugs and security issues commonly associated with C extensions.
 
 ## [Documentation](https://docs.pgvecto.rs/getting-started/overview.html)
 
@@ -56,7 +45,7 @@ docker run \
   --name pgvecto-rs-demo \
   -e POSTGRES_PASSWORD=mysecretpassword \
   -p 5432:5432 \
-  -d tensorchord/pgvecto-rs:pg16-v0.1.13
+  -d tensorchord/pgvecto-rs:pg16-v0.1.14-beta
 ```
 
 Then you can connect to the database using the `psql` command line tool. The default username is `postgres`, and the default password is `mysecretpassword`.
@@ -74,7 +63,7 @@ CREATE EXTENSION vectors;
 
 pgvecto.rs introduces a new data type `vector(n)` denoting an n-dimensional vector. The `n` within the brackets signifies the dimensions of the vector.
 
-You could create a table with the following SQL. 
+You could create a table with the following SQL.
 
 ```sql
 -- create table with a vector column