Redis Labs Establishes New Standard for Instant Multi-Model Databases

By on

According to a new press release, “Redis Labs, the home of Redis and provider of Redis Enterprise, broke new ground in the database industry today, at RedisConf19, with the introduction of two new data models and a novel data programmability paradigm for multi-model operation. RedisTimeSeries is designed to collect and store high volume and velocity data, to the scale of billions of data points, and organize it by time intervals. RedisTimeSeries enables organizations to easily distill useful data points with built-in capabilities for downsampling, aggregation, and compression. This provides organizations the ability to query and extract data in real-time for rapid analytics.”

The release goes on, “RedisAI eliminates the need to migrate data to/from different environments and allows developers to apply state-of-the-art AI models to where the data lives, in Redis, dramatically improving the speed with which analytics can be conducted and actions are taken. By integrating with common deep learning frameworks including TensorFlow, PyTorch, and TorchScript, and by utilizing Redis Cluster capabilities over GPU-based servers, RedisAI reduces processing overhead and dramatically accelerates the time to insights… RedisGears, an in-database serverless engine, is based on the efficient Redis Cluster distributed architecture to enable infinite programmability options supporting event-driven (asynchronously) or transaction-based (synchronously) operations. With these innovations, Redis can now manage multiple data models driven by a single trigger or application’s request, including native data structures, search, graph, streams, AI, time series, document, and probabilistic data structures.”

Read more at redislabs.com.

Image used under license from Shutterstock.com

We use technologies such as cookies to understand how you use our site and to provide a better user experience. This includes personalizing content, using analytics and improving site operations. We may share your information about your use of our site with third parties in accordance with our Privacy Policy. You can change your cookie settings as described here at any time, but parts of our site may not function correctly without them. By continuing to use our site, you agree that we can save cookies on your device, unless you have disabled cookies.
I Accept