ParadeDB

Overview

ParadeDB is an Elasticsearch alternative built on Postgres. Built for real-time, update-heavy workloads.

Getting Started

Visit the Official ParadeDB documentation for an in-depth and complete guide on ParadeDB. See also the ParadeDB Changelog for the latest updates!

ParadeDB comes with a helpful procedure that creates a table populated with mock data to help you get started. Once connected with psql, run the following commands to create and inspect this table.

CALL paradedb.create_bm25_test_table(
  schema_name => 'public',
  table_name => 'mock_items'
);

SELECT description, rating, category
FROM mock_items
LIMIT 3;

       description        | rating |  category
--------------------------+--------+-------------
 Ergonomic metal keyboard |      4 | Electronics
 Plastic Keyboard         |      4 | Electronics
 Sleek running shoes      |      5 | Footwear
(3 rows)

Next, let’s create a BM25 index called search_idx on this table. A BM25 index is a covering index, which means that multiple columns can be included in the same index. The following code block demonstrates the various Postgres types that can be combined inside a single index.

CREATE INDEX search_idx ON mock_items
USING bm25 (id, description, category, rating, in_stock, created_at, metadata, weight_range)
WITH (key_field='id');

Note the mandatory key_field option in the WITH code. Every bm25 index needs a key_field, which should be the name of a column that will function as a row’s unique identifier within the index. Usually, the key_field can just be the name of your table’s primary key column.

Once the indexing is complete, you can run various search functions on it.

Basic Search

Execute a search query on your indexed table:

SELECT description, rating, category
FROM mock_items
WHERE (description @@@ 'shoes' OR category @@@ 'footwear') AND rating @@@ '>2'
ORDER BY description
LIMIT 5;

This will return:

     description      | rating | category 
----------------------+--------+----------
 Comfortable slippers |      3 | Footwear
 Generic shoes        |      4 | Footwear
 Sleek running shoes  |      5 | Footwear
 Sturdy hiking boots  |      4 | Footwear
 White jogging shoes  |      3 | Footwear
(5 rows)

Note the usage of limit_rows instead of the SQL LIMIT clause. For optimal performance, we recommend always using limit_rows and offset_rows instead of LIMIT and OFFSET.