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High performance

Purpose-built using in-memory data structures implemented
in C to give performance,
and scalability.


Built with performance in mind
using in-memory data structures implemented in C, RediSearch supports fast indexing and ingestion.

Horizontally scalable

Scale out and partition indexes over several shards and nodes for greater speed and memory capacity.


Enjoy continued operations in any scenario with five-nines availability and Active-Active failover.

“At HackerRank we use Redis Pub/Sub as a pipeline to help all developers practicing on HackerRank to see the results of their code submission in near real-time. We use JSON heavily in this pipeline to detect the status of all submissions and inform our users so they can better compete in our programming challenges. This has worked very well for us for several years without any issues at an extremely large scale to meet our need to process thousands of code submissions per minute.”

Swapnil Talekar
Engineering Manager, HackerRank

Main capabilities

In-memory JSON store

Store and process scheme-free JSON in-memory, supporting millions of operations per second with sub-millisecond response times. Allows atomic operations on JSON sub-elements in-memory.

Indexing & querying

JSON allows you to quickly create indexes on JSON documents, and uses real-time indexing that allows you to instantly query documents that have been indexed. The indexes let you query your data at lightning speed, perform complex aggregations, and filter by properties, numeric ranges, and geographical distance.

Full-text & fuzzy search

JSON supports full-text indexing and stemming-based query expansion in multiple languages. It provides a rich query language that can perform text searches, as well as complex structured queries. Furthermore, you can enrich search experiences by implementing auto-complete suggestions using ‘fuzzy’ searches.

Available on-prem & as a managed-service

JSON’s Enterprise and Enterprise Cloud offering lets you effortlessly scale RedisJSON across an entire cluster, allowing you to grow your indexes to billions of documents on hundreds of servers.

Find your use case

Customer 360°

Search, find, and store critical information on customers for a product/service, profile and history to match specific profiles and behaviors for better support.

Mobile app development

Build responsive mobile apps while keeping your data in sync across client apps.

Content management

Manage blogs and videos where each entity the content application tracks is stored as a single document and updated when the data model changes without having to update the schema.

Product catalogs

Manage and search thousands of products with different SKUs and attributes.

> Cache plus-white minus-white

Use JSON as a high-speed cache to store frequently accessed JSON data and manipulate sub-elements using atomic operations.

/ Query accelerator plus-white minus-white

Use JSON as an in-memory data fabric on top of one or more data stores to accelerate queries while offloading production systems.

[ Primary database plus-white minus-white

Distributed, in-memory JSON document database.

Related resources



Indexing, Querying, and Full-Text Search of JSON Documents with Redis

Related Resource: Click to download RedisJSON module. RedisJSON and RediSearch are by far the most popular Redis modules in our cloud. (See Fig. 1) The docker images of…