Use SQL to query data in maps, Kafka topics, or a variety of file systems. Results can be sent directly to the client or inserted into maps or Kafka topics.
Use an Industry Standard for Querying Data
Hazelcast supports SQL querying to allow anyone familiar with the industry-standard language to interact with in-memory data. Leveraging the sophisticated query engine built into Hazelcast, the SQL support adds a well-known interface to run queries and offers:
- The ability to query large amounts of data in an industry-standard way, with the same query specificity of the existing Hazelcast Predicate-based design
- The option to make use of a new, high-performance concurrent off-heap B+ tree indexes
- More advanced query optimization
Take advantage of in-memory speeds, and also gain further performance via indexes and advanced query optimization.
Initial support entails “select” queries; the roadmap includes the goal of extensive, standard SQL support for create/read/update/delete (CRUD) operations.
Query fields (“attributes”) for more granular results, instead of only querying on the primary key.
Leverage Hazelcast advantages around business continuity, scale, and security that have been a core part of Hazelcast IMDG.
Maintaining an Online Edge in Today’s Highly Competitive Banking World
BNP Paribas Bank Polska, which has been listed on the Warsaw Stock Exchange since 2011 is a member of the BNP Paribas banking group whose footprint spans 71 countries.
Hazelcast In-Memory Computing Datasheet
The Hazelcast in-memory data store can be used as a high-speed data store for reference data to enrich streaming data, or it can be used with other applications to accelerate data accesses.