In-memory data grids (IMDG) such as Pivotal GemFire, which is powered by Apache Geode, are key to making today’s modern high-speed, data-intensive applications work. By keeping data in the RAM of a horizontally scalable cluster of servers, IMDG solutions enable apps to achieve consistently low latency for data access at any scale.
Many in the application development community, however, aren’t aware of IMDG’s benefits, use cases, or underlying technology. This report brings you up to speed by providing GemFire basics, including use cases and easily understood examples. You’ll determine whether GemFire can benefit your application, and learn how to install a simple test environment and build a small proof of concept.
- Explore GemFire use cases for Java applications—including microservices, high-speed data ingest, and transaction and event processing
- Get an architectural overview of GemFire, and learn installation requirements for both hardware/VM and cloud
- Dive into GemFire’s capabilities with continuous queries, server-side functions, and Apache Lucene integration
- Learn how GemFire works with the persistence model, off-heap memory, and WAN replication
Table of contents
1. Introduction to Pivotal GemFire In-Memory Data Grid and Apache Geode
- Memory Is the New Disk
- What Is Pivotal GemFire?
- What Is Apache Geode?
- What Problems Are Solved by an IMDG?
- Real GemFire Use Cases
- IMDG Architectural Issues and How GemFire Addresses Them
- 2. Cluster Design and Distributed Concepts
- 3. Quickstart Example
- 4. Spring Data GemFire
- 5. Designing Data Objects in GemFire
- 6. Multisite Topologies Using the WAN Gateway
- 7. Querying, Events, and Searching
- 8. Authentication and Role-Based Access Control
- 9. Pivotal GemFire Extensions
- 10. More Than Just a Cache
- Title: Scaling Data Services with Pivotal GemFire
- Release date: January 2018
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492027577
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