Achieve Sub-millisecond Performance on MongoDB with Redis Enterprise
Redis Enterprise is an in-memory real-time data platform that provides sub-millisecond performance by holding the working data set in DRAM instead of slower storage, thereby dramatically improving response times. Developers use Redis Enterprise to cache their MongoDB queries to meet customer expectations for a real-time response. MongoDB provides sub-millisecond performance with Redis Enterprise.
If the data is not found in Redis Enterprise, the application gets the data from MongoDB and puts it into the Redis Enterprise for subsequent reads. Data is loaded to Redis Enterprise only when necessary. Read-heavy applications can significantly benefit from implementing a cache-aside approach.
Data is first written to Redis Enterprise and then asynchronously updates MongoDB. This approach improves write performance and eases application development since the developer writes to only one place – Redis Enterprise. RedisGears processes events and streams, providing write-behind capabilities.
Redis Enterprise sits between the application and MongoDB, except the updates are done synchronously. The write-through pattern favors data consistency between Redis Enterprise and MongoDB. RedisGears processes events and streams, providing write-through capabilities.
MongoDB was designed for functionality rather than speed at scale. Redis Enterprise is often used to store copies of the replies to costly queries from MongoDB to reduce latency and significantly increase throughput. Redis Enterprise enables MongoDB to be always available and easily scale.
Caching user session data is integral to building scalable and responsive applications. Because every user interaction requires access to the session’s data, keeping that data in Redis Enterprise increases the response time to the application user. Redis Enterprise enables real-time response at scale to compliment MongoDB’s flexible schema and development speed.
Using Redis Enterprise with MongoDB as the primary data store can address data ingestion challenges in the Internet of Things (IoT), e-commerce, retail, and financial services. To manage extreme data velocity and gain insights faster with MongoDB, you need a data ingest buffer, such as Redis Enterprise, to streamline the input process.
There are situations when you need better performance from your document storage than the levels MongoDB can provide you with. This is when you should use Redis Enterprise as opposed to MongoDB. Redis Enterprise natively supports high-performance JSON access and manipulation, enabling you to build modern real-time applications for gaming, financial services, e-commerce, and other areas using a hierarchical JSON document model. For the use cases where it is required, RedisJSON offers superior performance compared to MongoDB.
With RedisJSON, you can search, find, and store critical customer information for a product/service, profile, and history to match specific profiles and behaviors for better support.
Fast Healthcare Interoperability Resources (FHIR) is the standard for data formats in exchanging electronic health records and natively supports the JSON format. Power your digital claims processing with RedisJSON.
RedisJSON allows you to manage and search thousands of products with different SKUs and attributes.
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
RedisJSON* (powered by RediSearch) is now available as a public preview. See its performance benchmarks against MongoDB and ElasticSearch.
By continuing to use this site, you consent to our updated privacy agreement. You can change your cookie settings at any time but parts of our site will not function correctly without them.