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Hazelcast Platform Enables Faster Recovery, Unifies SQL Support

Hazelcast Platform Enables Faster Recovery, Unifies SQL Support

Hazelcast Platform Provides A Simple, Unified Software Architecture For Compute And Data

Hazelcast, the provider of the real-time intelligent applications platform, is announcing the addition of disk-based persistence and enhanced SQL support for the company’s new solution, Hazelcast Platform. In addition to new capabilities, the Hazelcast Platform provides a seamless, zero-downtime upgrade path for customers using Hazelcast 3.x and 4.x products.

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Announced , the Hazelcast Platform enables enterprises to unify event streams with the context of traditional data sources, such as databases and data lakes, to accelerate revenue growth, significantly lower risk or drive cost efficiencies.

“While the Hazelcast Platform is new, it carries the same DNA as its predecessors when it comes to performance, enrichment, scale and reliability,” said John DesJardins, CTO of Hazelcast. “The addition of persistence and production-ready unified SQL support directly correlates to the desire of our customers to merge multiple workloads, while gaining the performance and reliability of in-memory technologies.”

Advancing SQL Support
Announced in beta earlier this year, enhanced ANSI SQL support moves into production-ready status with the general availability of the Hazelcast Platform. With the unification of the Hazelcast real-time stream processing engine and a high-performance data store, enterprises can now combine historical data, event data and file-based data with a single query with microsecond latency. In this approach, the streaming engine is able to pre-process data as it is ingested while the in-memory compute can analyze and act upon the insights in real-time. The unified data can also be fed by the streaming engine into machine learning code for real-time inference.

The SQL engine in the Hazelcast Platform now supports basic data manipulation language (DML) functionality to enable INSERT, UPDATE and DELETE on data in Hazelcast. The platform also adds sorting, aggregations and new SQL expressions. Additionally, customers can leverage SQL to declaratively ingest data from messaging systems like Kafka, as well as files and object storage such as S3, and insert it into an IMap and execute streaming queries and computations via SQL.

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Persistence
Already known for its proven reliability, Hazelcast adds a disk-based persistence capability to enable greater uptime for any individual cluster member. With persistence, customers can safely restore data after an unexpected crash, as well as reduce maintenance and migration windows to improve availability.

For maintenance, Hazelcast also provides improved flexibility as the customer can now control the recovery time window as needed. For example, if a member of the cluster is shut down for maintenance with the intention of restoring it near-term, Hazelcast can be requested to hold off the cluster rebalancing process. The persistence capability then allows fast recovery of the member after maintenance is performed. Similarly, if a member is being transferred to another hardware server, the persistence files let customers quickly restart the member at the new location using the existing data without the need for full data shuffling.

Additional Enhancements
Among the other features introduced in this release of the Hazelcast Platform are fine-grain security controls for the stream processing engine and Management Center has been unified to manage and monitor streaming and data store jobs, while also receiving an upgraded user interface for simplified management of Hazelcast clusters.

Finally, users will be able to seamlessly upgrade from 3.x and 4.x versions of Hazelcast to take advantage of the new platform.

Availability
Hazelcast Platform 5.0 is available in beta with general availability expected in August 2021.

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