By Harish Kathpalia
Today, companies capture and store large amounts of data, normally in disk-based databases. These disk-based databases are slow and are unable to match the real-time experiences needed by modern applications. RediSearch 2.0 overcomes these limitations by giving applications the ability to index their datasets and then query the data in real-time, boosting performance.
In this session, we explain the high level architecture of RediSearch 2.0 and how it enables developers to query across large data sets, enabling faster retrieval. We discuss several indexing strategies provided by RediSearch, some important features like querying, secondary indexing, and full-text search, and the multiple use cases these features support. You’ll see the results of a performance comparison between Elasticsearch and RediSearch, and a short demo showing how to query data using RediSearch.