JSON

A high-performance document store for modern applications

JSON is a high-performance NoSQL document store that allows developers to build modern applications. It provides native APIs to ingest, index, query, and run full-text search on JSON documents both on-premises and as a managed service in the cloud.

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Benefits

High performance

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

Developer-friendly

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.

Enterprise-grade

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

We previously used MongoDB as the document store for our security service, but migrated to JSON, improving slow writes and high read latencies by up to 4 times; in addition to reducing the number of platforms we use in development. We are in the process of migrating our primary database for Electronic Medical Records from MySQL 8 to Redis Cloud with RediSearch and JSON to enable highly available, real-time access to medical data and records.

Alfarisi

Director of Technology at Global Inovasi Cahaya

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.

Building a fast product catalog with JSON

Indexing and 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.

Aggregation features in Redis

Full-text and 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.

Powering search autocomplete in Redis

Available on-premises and 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.

Redis Cloud overview

Unlocking the Cloud-Native data layer

Use cases

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.

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.

Mobile app development

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

Product catalogs

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

Usage patterns

JSON makes it possible to undertake non-disruptive modernization of RDBMSes and slow document stores by using the principles of caching. Customers deploy RedisJSON using different usage patterns across their data stack.