Introduction In a modern application that interacts with different database and app services, handling the distributed transactions are very efficient and crucial. To manage the data consistency across the multiple resources XA transaction(eXtended Architecture) is a standard way. In this article, we will explore how to use the XA Transactions in Java using Hazelcast data […]
Introduction In a distributed system, maintaining data integrity and consistency is very challenging. To implement Hazelcast transaction Management, Hazelcast provides features that make it easy to manage transactions and data consistency. Hazelcast is a high-performance, in-memory data grid(IMDG) which supports distributed caching, computation, and messaging. In this article, we will explore the features of Hazelcast
Introduction In modern applications, building a data pipeline with Hazelcast is important and data pipelines are one of the most critical systems in the whole applications architecture. Data pipelines are responsible for processing and transforming raw data into a format that can be used for analysis. However, it is not that simple to build a useful data
1. Introduction In today’s time, efficient querying and management of complex data structures is a necessity for data-driven applications. Hazelcast, a powerful in-memory data grid, is known for handling large-scale distributed data and provides robust querying features. One unique feature of Hazelcast JSON SQL JOIN Query is HazelcastJsonValue, which natively supports JSON data. SQL (Structured
1. Introduction to Hazelcast and JSON Support Hazelcast is one of the in-memory data grid and computing platform, which is designed to process the large volume of data into quickly and reliably. Hazelcast distribute the data into multiple clusters of nodes, which enables to access the data significantly faster and with low latency, compared to
Overview Hazelcast work with distributed cluster with nodes. If you need to implement counter which need to shared accross the distributed nodes for the testing and fundamental. Hazelcast gives a few incredible assets to deal with these difficulties. Among them is the Hazelcast PN Counter, a profoundly helpful design for overseeing dispersed information in a
Overview As distributed systems and applications are gaining traction, the role of unique identifiers across numerous nodes becomes essential. This issue is relevant when working with a distributed data platform. A popular in-memory data grid, Hazelcast has a perfect remedy for this problem in the form of the Hazelcast Flake ID Generator. In essence, the
Overview Hazelcast, a leading in-memory data grid, offers various serialization mechanisms to boost performance and efficiency in distributed systems. Among these, Hazelcast Compact Serialization is a standout feature designed to minimize memory footprint and reduce network bandwidth consumption. As systems scale, efficient serialization becomes critical, and Hazelcast’s compact format offers a modern and optimized solution.
Overview Distributed systems have grown increasingly complex, necessitating 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 recognize that they control access to shared resources. Hazelcast enhances
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,
