go-redis guide (Go) on Docs

Connect to the server

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Basic connection

The following example shows the simplest way to connect to a Redis server:

Connect to Azure Managed Redis

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The go-redis-entraid package lets you authenticate your app to Azure Managed Redis (AMR) using Microsoft Entra ID. You can authenticate using a system-assigned or user-assigned managed identity or a service principal, letting go-redis-entraid fetch and renew the authentication tokens for you automatically.

Install

Install go-redis if you have not already done so. Note that go-redis-entraid requires go-redis v9.9.0 or above, so you should upgrade if you are using an earlier version.

Index and query documents

Mon, 01 Jan 0001 00:00:00 +0000

This example shows how to create a search index for JSON documents and run queries against the index. It then goes on to show the slight differences in the equivalent code for hash documents.

Note:

From v9.8.0 onwards, go-redis uses query dialect 2 by default. Redis query engine methods such as FTSearch() will explicitly request this dialect, overriding the default set for the server. See Query dialects for more information.

Initialize

Make sure that you have Redis Open Source or another Redis server available. Also install the go-redis client library if you haven't already done so.

Index and query vectors

Mon, 01 Jan 0001 00:00:00 +0000

Redis Query Engine lets you index vector fields in hash or JSON objects (see the Vectors reference page for more information). Among other things, vector fields can store text embeddings, which are AI-generated vector representations of the semantic information in pieces of text. The vector distance between two embeddings indicates how similar they are semantically. By comparing the similarity of an embedding generated from some query text with embeddings stored in hash or JSON fields, Redis can retrieve documents that closely match the query in terms of their meaning.

Vector set embeddings

Mon, 01 Jan 0001 00:00:00 +0000

A Redis vector set lets you store a set of unique keys, each with its own associated vector. You can then retrieve keys from the set according to the similarity between their stored vectors and a query vector that you specify.

You can use vector sets to store any type of numeric vector but they are particularly optimized to work with text embedding vectors (see Redis for AI to learn more about text embeddings). The example below shows how to use the Hugot library to generate vector embeddings and then store and retrieve them using a vector set with go-redis.

Pipelines and transactions

Mon, 01 Jan 0001 00:00:00 +0000

Redis lets you send a sequence of commands to the server together in a batch. There are two types of batch that you can use:

Pipelines avoid network and processing overhead by sending several commands to the server together in a single communication. The server then sends back a single communication with all the responses. See the Pipelining page for more information.
Transactions guarantee that all the included commands will execute to completion without being interrupted by commands from other clients. See the Transactions page for more information.

Execute a pipeline

To execute commands in a pipeline, you first create a pipeline object and then add commands to it using methods that resemble the standard command methods (for example, Set() and Get()). The commands are buffered in the pipeline and only execute when you call the Exec() method on the pipeline object.

Probabilistic data types

Mon, 01 Jan 0001 00:00:00 +0000

Redis supports several probabilistic data types that let you calculate values approximately rather than exactly. The types fall into two basic categories:

Set operations: These types let you calculate (approximately) the number of items in a set of distinct values, and whether or not a given value is a member of a set.
Statistics: These types give you an approximation of statistics such as the quantiles, ranks, and frequencies of numeric data points in a list.

To see why these approximate calculations would be useful, consider the task of counting the number of distinct IP addresses that access a website in one day.

Error handling

Mon, 01 Jan 0001 00:00:00 +0000

go-redis uses explicit error returns following Go's idiomatic error handling pattern. Code examples in the documentation often omit error handling for brevity, but it is essential in production code. This page explains how go-redis's error handling works and how to apply some common error handling patterns. For an overview of error types and handling strategies, see Error handling. See also Production usage for more information on connection management, timeouts, and other aspects of app reliability.

Production usage

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This guide offers recommendations to get the best reliability and performance in your production environment.

Checklist

Each item in the checklist below links to the section for a recommendation. Use the checklist icons to record your progress in implementing the recommendations.