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Redis Lab announced the release of RediSearch 2.0, which enables customers to build modern applications with interactive search experiences.
The latest version allows users to automatically index (and then query) their Redis datasets without changing their application, has support for Redis Enterprise’s Active-Active technology, and brings a 2.4x increase in performance.
RediSearch represents one of the fastest-growing capabilities Redis Labs customers are adopting because of its powerful indexing, querying, full-text search, and other supported use cases across various deployments—on-premises, cloud, multi-cloud, and hybrid cloud.
Organizations are storing more and more data in Redis to guarantee real-time performance for their applications. RediSearch now allows them to unlock this data by creating secondary indexes to support their queries—instead of writing manual indexes.
Built with performance in mind, RediSearch uses in-memory data structures and powerful indexing algorithms so customers can get virtually instant results on a wide variety of queries, from real-time transactional data to relevance-based search and analytical queries on their data.
RediSearch’s rich query language enables structured queries as well as full-text searches. Data can be filtered by properties, numeric ranges, and geographical distances.
Furthermore, developers can run “fuzzy” searches to implement autocomplete search experiences. All of this is done at the speed of Redis. This unified search engine also greatly simplifies the data infrastructure.
Developers no longer need to deal with flipping back and forth between query languages, data models, and bolt-on search engines.
The latest release also allows customers to scale RediSearch easily. Customers can now quickly grow to query and index billions of documents on hundreds of servers—and cost-effectively using Redis on Flash.
RediSearch also can be deployed in a globally distributed manner by leveraging Redis Enterprise’s Active-Active technology to deliver five-nines (99.999%) availability and across numerous geo distributed read replicas, making it ideal for searching frequently updated datasets.
“As customers increasingly rely on Redis Enterprise as their real-time data platform, they want to dynamically query and search their data residing in Redis. RediSearch now enables organizations to quickly build indexes which require low latency querying and full-text search.
“All of this is delivered with the familiar ease of scaling and speed of Redis,” said Pieter Cailliau, Director of Product Management at Redis Labs.
“GoMechanic needed a fast data layer to search across 10 million spare parts and power its customer service chats. RediSearch on Google Cloud was not only four times faster than our existing database but also extremely robust, easy to scale, and inexpensive,” said Prasenjit Singh, Vice President of Engineering at GoMechanic.
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