RedisJSON 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.
Purpose-built using in-memory data structures implemented
in C to give performance,
Built with performance in mind
using in-memory data structures implemented in C, RediSearch supports fast indexing and ingestion.
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.
We previously used MongoDB as the document store for our security service, but migrated to RedisJSON, 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 Enterprise Cloud with RediSearch and RedisJSON to enable highly available, real-time access to medical data and records.
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 RedisJSON 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.
Engineering Manager, HackerRank
Our on-board diagnostics device, GoConnect, plugs into a customer’s car and transmits diagnostics to the GoMechanic app. Our goal is to deliver P99 latency for the more than 5,000 devices currently deployed across India. Since deploying RedisJSON as a front-end database to MongoDB we’ve reduced our turnaround time (TAT) 70% and achieved 99.99% availability for the service. We have plans for further optimization with the new RedisJSON to enable synchronous indexing to deliver a true real-time service.
Software Developer, GoMechanic
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.
RedisJSON 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.
RedisJSON 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.
RedisJSON’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.
Search, find, and store critical information on customers for a product/service, profile and history to match specific profiles and behaviors for better support.
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.
Manage and search thousands of products with different SKUs and attributes.
RedisJSON 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.
Use RedisJSON as a high-speed cache to store frequently accessed JSON data and manipulate sub-elements using atomic operations.
Use RedisJSON as an in-memory data fabric on top of one or more data stores to accelerate queries while offloading production systems.
Distributed, in-memory JSON document database.
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