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
Overview Hazelcast, a leading in-memory data grid, offers seamless integration with SQL queries, making it a powerful tool for developers who need both scalability and performance. The Hazelcast SQL Query Example provides a structured way to query data stored within Hazelcast clusters, combining the flexibility of SQL with the speed of in-memory computing. In this
Overview In modern software development, managing date and time effectively is crucial, especially when working with distributed systems or APIs. Two common representations for date and time are Google’s Protocol Buffers (com.google.protobuf.Timestamp) and Java’s Date-Time API (java.time.LocalDateTime), also work on Convert protobuf Tiimestamp and LocalDateTime. To Convert protobuf Tiimestamp and LocalDateTime, you’ll need to handle
Overview gRPC is a high-performance RPC framework developed by Google, enabling efficient communication between services in different programming languages. One of its standout features is bidirectional streaming, allowing both the client and server to send a sequence of messages to each other. This guide will help you set up and implement gRPC bidirectional streaming in
