Couchbase

This is the implementation of the Couchbase Vector store data handler for MindsDB.

Couchbase is an open-source, distributed multi-model NoSQL document-oriented database software package optimized for interactive applications. These applications may serve many concurrent users by creating, storing, retrieving, aggregating, manipulating, and presenting data.

​

Prerequisites

Before proceeding, ensure the following prerequisites are met:

1. Install MindsDB locally via Docker or Docker Desktop.
2. To connect Couchbase to MindsDB, install the required dependencies following this instruction.
3. Install or ensure access to Couchbase.

​

Implementation

In order to make use of this handler and connect to a Couchbase server in MindsDB, the following syntax can be used. Note, that the example uses the default travel-sample bucket which can be enabled from the couchbase UI with pre-defined scope and documents.

CREATE DATABASE couchbase_vectorsource
WITH
engine='couchbase',
parameters={
    "connection_string": "couchbase://localhost",
    "bucket": "travel-sample",
    "user": "admin",
    "password": "password",
    "scope": "inventory"
};

This handler is implemented using the couchbase library, the Python driver for Couchbase.

The required arguments to establish a connection are as follows:

• connection_string: the connection string for the endpoint of the Couchbase server
• bucket: the bucket name to use when connecting with the Couchbase server
• user: the user to authenticate with the Couchbase server
• password: the password to authenticate the user with the Couchbase server
• scope: scopes are a level of data organization within a bucket. If omitted, will default to _default

Note: The connection string expects either the couchbases:// or couchbase:// protocol.

​

Usage

Now, you can use the established connection to create a collection (or table in the context of MindsDB) in Couchbase and insert data into it:

​

Creating tables

Now, you can use the established connection to create a collection (or table in the context of MindsDB) in Couchbase and insert data into it:

CREATE TABLE couchbase_vectorsource.test_embeddings (
    SELECT embeddings
    FROM mysql_datasource.test_embeddings
);

​

Querying and searching

You can query your collection (table) as shown below:

SELECT * 
FROM couchbase_vectorsource.test_embeddings;

To filter the data in your collection (table) by metadata, you can use the following query:

SELECT * 
FROM couchbase_vectorsource.test_embeddings
WHERE id = "some_id";

To perform a vector search, the following query can be used:

SELECT *
FROM couchbase_vectorsource.test_embeddings
WHERE embeddings = (
    SELECT embeddings
    FROM mysql_datasource.test_embeddings
    LIMIT 1
);

​

Deleting records

You can delete documents using DELETE just like in SQL.

DELETE FROM couchbase_vectorsource.test_embeddings
WHERE `metadata.test` = 'test1';

​

Dropping connection

To drop the connection, use this command

DROP DATABASE couchbase_vectorsource;