Overview Distributed systems have grown increasingly complex, requiring more advanced methods to manage synchronization between nodes and processes. One such tool that simplifies this task in distributed environments is the Hazelcast Data Structure ISemaphore. If you’re familiar with semaphores in Java or other languages, you’ll know they provide a way to control access to shared […]
Overview When building distributed applications, efficient data management is crucial to maintaining performance at scale. Hazelcast, a leading in-memory data grid, offers numerous tools to optimize how you store and query your data across distributed systems. One such tool is data indexing, which significantly enhances query performance. In this blog, we’ll explore Hazelcast data indexes,
Overview In today’s data-driven world, managing large datasets efficiently is crucial for any application. Hazelcast, a powerful in-memory data grid, provides developers with a robust solution for handling distributed data effectively. Among its many features, Hazelcast Paging Predicates play a pivotal role in efficiently retrieving and processing data subsets. This article delves deep into the
Overview In distributed systems, synchronization and locking mechanisms are crucial to ensure data consistency and proper coordination between different nodes. Hazelcast, a well-known in-memory computing platform, offers several solutions for distributed locking, including Hazelcast FencedLock, which is a robust lock designed to ensure higher reliability in partitioned or multi-node environments. This article explores the ins
Overview In distributed systems and modern applications, JSON has become the go-to format for data interchange due to its flexibility and simplicity. Hazelcast, a leading in-memory data grid, supports handling JSON data through the HazelcastJsonValue class. When working with large-scale JSON data stored in Hazelcast’s distributed IMap, you often need to perform queries to filter
Overview Hazelcast is a powerful in-memory data grid that provides distributed data structures and services, enabling the building of scalable applications. Hazelcast Predicate Functions one of its key features is its ability to perform queries on distributed data using Predicate Functions. Hazelcast predicates offer a flexible, SQL-like approach to filter and retrieve data from Hazelcast’s
Overview Hazelcast SQL stands out as a robust tool for querying distributed data structures like maps using SQL-like syntax. For developers looking to maximize the efficiency of their distributed systems, understanding how to use SQL predicates in Hazelcast is crucial. In this article, we delve deep into Hazelcast SQL predicates, explaining their significance, how to
Overview Hazelcast, a powerful in-memory data grid, offers a robust platform for distributed computing, scaling across clusters, and managing large datasets in real-time. One of Hazelcast’s core strengths is its distributed data structures, which allow developers to scale their applications while maintaining performance, resilience, and availability. In this article, we explore the most important Hazelcast
Overview Hazelcast SQL Expressions provides a powerful and flexible way to interact with data stored in Hazelcast clusters using SQL syntax. This feature allows developers to leverage familiar SQL expressions to manipulate data, making it easier to perform complex queries and analyses. This guide will explore Hazelcast SQL expressions, covering key concepts, syntax, and practical
Overview Hazelcast has in-memory data platform, it offers distributed data structures and stream data processing capabilities. One of its important features is the ability to perform SQL queries over distributed data. Hazelcast SQL makes it easier to interact with distributed data structures, such as maps, in a manner similar to relational databases. Understanding Hazelcast SQL
