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GridGain In-Memory Data Fabric vs Payara Server

Professional comparison and analysis to help you choose the right software solution for your needs.

GridGain In-Memory Data Fabric icon
GridGain In-Memory Data Fabric
Payara Server icon
Payara Server

GridGain In-Memory Data Fabric vs Payara Server: The Verdict

⚡ Summary:

GridGain In-Memory Data Fabric: GridGain In-Memory Data Fabric is an in-memory computing platform that provides in-memory speed and massive scalability for data-intensive applications. It allows organizations to process transactions and analyze data in real-time.

Payara Server: Payara Server is an open source application server derived from GlassFish Server Open Source Edition. It adds patches, bug fixes and enhancements on top of the GlassFish codebase. Key features include production-ready clustering, simplified troubleshooting and administration.

Both tools serve their respective audiences. Compare the features, pricing, and user ratings above to determine which best fits your needs.

Last updated: May 2026 · Comparison by Sugggest Editorial Team

Feature GridGain In-Memory Data Fabric Payara Server
Sugggest Score — —
Category Development Development
Pricing — Open Source

Product Overview

GridGain In-Memory Data Fabric
GridGain In-Memory Data Fabric

Description: GridGain In-Memory Data Fabric is an in-memory computing platform that provides in-memory speed and massive scalability for data-intensive applications. It allows organizations to process transactions and analyze data in real-time.

Type: software

Payara Server
Payara Server

Description: Payara Server is an open source application server derived from GlassFish Server Open Source Edition. It adds patches, bug fixes and enhancements on top of the GlassFish codebase. Key features include production-ready clustering, simplified troubleshooting and administration.

Type: software

Pricing: Open Source

Key Features Comparison

GridGain In-Memory Data Fabric
GridGain In-Memory Data Fabric Features
  • In-memory data storage and processing
  • Distributed caching
  • In-memory SQL queries
  • In-memory compute grid
  • High availability through data replication
  • Horizontal scalability
  • ACID transactions
  • ANSI SQL support
  • Streaming and CEP
  • Machine learning and predictive analytics
Payara Server
Payara Server Features
  • Full compatibility with Java EE 8
  • Production-ready clustering
  • 24/7 Mission Control monitoring
  • Enhanced security with Payara MicroProfile JWT
  • Simplified troubleshooting and administration
  • Fast application deployment

Pros & Cons Analysis

GridGain In-Memory Data Fabric
GridGain In-Memory Data Fabric

Pros

  • Very fast performance for data-intensive workloads
  • Low latency for real-time applications
  • Scales horizontally
  • Supports both SQL and key-value APIs
  • Open source and commercially supported options available

Cons

  • Can require large amounts of RAM to store data in-memory
  • Not ideal for storing large amounts of infrequently accessed data
  • Complexity of distributed system configuration and management
Payara Server
Payara Server

Pros

  • Open source and free to use
  • Very stable and reliable
  • Great performance
  • Easy clustering setup
  • User-friendly admin console
  • Active community support

Cons

  • Steep learning curve for beginners
  • Not as lightweight as Tomcat
  • Lacks some advanced features of proprietary app servers
  • Documentation could be more extensive

Pricing Comparison

GridGain In-Memory Data Fabric
GridGain In-Memory Data Fabric
  • Not listed
Payara Server
Payara Server
  • Open Source

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Learn More About Each Product

GridGain In-Memory Data Fabric
GridGain In-Memory Data Fabric
Reviews, pricing & alternatives →
Payara Server
Payara Server
Reviews, pricing & alternatives →

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