Skip to main content

Cassandra

Compatibility

Only available on Node.js.

Apache Cassandra® is a NoSQL, row-oriented, highly scalable and highly available database.

The latest version of Apache Cassandra natively supports Vector Similarity Search.

Setup​

First, install the Cassandra Node.js driver:

tip

See this section for general instructions on installing integration packages.

npm install cassandra-driver @langchain/community @langchain/openai @langchain/core

Depending on your database providers, the specifics of how to connect to the database will vary. We will create a document configConnection which will be used as part of the vector store configuration.

Apache Cassandra®​

Vector search is supported in Apache Cassandra® 5.0 and above. You can use a standard connection document, for example:

const configConnection = {
  contactPoints: ['h1', 'h2'],
  localDataCenter: 'datacenter1',
  credentials: {
    username: <...> as string,
    password: <...> as string,
  },
};

Astra DB​

Astra DB is a cloud-native Cassandra-as-a-Service platform.

  1. Create an Astra DB account.
  2. Create a vector enabled database.
  3. Create a token for your database.
const configConnection = {
  serviceProviderArgs: {
    astra: {
      token: <...> as string,
      endpoint: <...> as string,
    },
  },
};

Instead of endpoint:, you many provide property datacenterID: and optionally regionName:.

Indexing docs​

import { CassandraStore } from "langchain/vectorstores/cassandra";
import { OpenAIEmbeddings } from "@langchain/openai";

// The configConnection document is defined above
const config = {
  ...configConnection,
  keyspace: "test",
  dimensions: 1536,
  table: "test",
  indices: [{ name: "name", value: "(name)" }],
  primaryKey: {
    name: "id",
    type: "int",
  },
  metadataColumns: [
    {
      name: "name",
      type: "text",
    },
  ],
};

const vectorStore = await CassandraStore.fromTexts(
  ["I am blue", "Green yellow purple", "Hello there hello"],
  [
    { id: 2, name: "2" },
    { id: 1, name: "1" },
    { id: 3, name: "3" },
  ],
  new OpenAIEmbeddings(),
  cassandraConfig
);

Querying docs​

const results = await vectorStore.similaritySearch("Green yellow purple", 1);

or filtered query:

const results = await vectorStore.similaritySearch("B", 1, { name: "Bubba" });

Vector Types​

Cassandra supports cosine (the default), dot_product, and euclidean similarity search; this is defined when the vector store is first created, and specifed in the constructor parameter vectorType, for example:

  ...,
  vectorType: "dot_product",
  ...

Indices​

With Version 5, Cassandra introduced Storage Attached Indexes, or SAIs. These allow WHERE filtering without specifying the partition key, and allow for additional operator types such as non-equalities. You can define these with the indices parameter, which accepts zero or more dictionaries each containing name and value entries.

Indices are optional, though required if using filtered queries on non-partition columns.

  • The name entry is part of the object name; on a table named test_table an index with name: "some_column" would be idx_test_table_some_column.
  • The value entry is the column on which the index is created, surrounded by ( and ). With the above column some_column it would be specified as value: "(some_column)".
  • An optional options entry is a map passed to the WITH OPTIONS = clause of the CREATE CUSTOM INDEX statement. The specific entries on this map are index type specific.
  indices: [{ name: "some_column", value: "(some_column)" }],

Advanced Filtering​

By default, filters are applied with an equality =. For those fields that have an indices entry, you may provide an operator with a string of a value supported by the index; in this case, you specify one or more filters, as either a singleton or in a list (which will be AND-ed together). For example:

   { name: "create_datetime", operator: ">", value: some_datetime_variable }

or

[
  { userid: userid_variable },
  { name: "create_datetime", operator: ">", value: some_date_variable },
];

value can be a single value or an array. If it is not an array, or there is only one element in value, the resulting query will be along the lines of ${name} ${operator} ? with value bound to the ?.

If there is more than one element in the value array, the number of unquoted ? in name are counted and subtracted from the length of value, and this number of ? is put on the right side of the operator; if there are more than one ? then they will be encapsulated in ( and ), e.g. (?, ?, ?).

This faciliates bind values on the left of the operator, which is useful for some functions; for example a geo-distance filter:

{
  name: "GEO_DISTANCE(coord, ?)",
  operator: "<",
  value: [new Float32Array([53.3730617,-6.3000515]), 10000],
},

Data Partitioning and Composite Keys​

In some systems, you may wish to partition the data for various reasons, perhaps by user or by session. Data in Cassandra is always partitioned; by default this library will partition by the first primary key field. You may specify multiple columns which comprise the primary (unique) key of a record, and optionally indicate those fields which should be part of the partition key. For example, the vector store could be partitioned by both userid and collectionid, with additional fields docid and docpart making an individual entry unique:

  ...,
  primaryKey: [
    {name: "userid", type: "text", partition: true},
    {name: "collectionid", type: "text", partition: true},
    {name: "docid", type: "text"},
    {name: "docpart", type: "int"},
  ],
  ...

When searching, you may include partition keys on the filter without defining indices for these columns; you do not need to specify all partition keys, but must specify those in the key first. In the above example, you could specify a filter of {userid: userid_variable} and {userid: userid_variable, collectionid: collectionid_variable}, but if you wanted to specify a filter of only {collectionid: collectionid_variable} you would have to include collectionid on the indices list.

Additional Configuration Options​

In the configuration document, further optional parameters are provided; their defaults are:

  ...,
  maxConcurrency: 25,
  batchSize: 1,
  withClause: "",
  ...
ParameterUsage
maxConcurrencyHow many concurrent requests will be sent to Cassandra at a given time.
batchSizeHow many documents will be sent on a single request to Cassandra. When using a value > 1, you should ensure your batch size will not exceed the Cassandra parameter batch_size_fail_threshold_in_kb. Batches are unlogged.
withClauseCassandra tables may be created with an optional WITH clause; this is generally not needed but provided for completeness.

Was this page helpful?


You can also leave detailed feedback on GitHub.