GridGain In-Memory Data Fabric vs Infinispan

Struggling to choose between GridGain In-Memory Data Fabric and Infinispan? Both products offer unique advantages, making it a tough decision.

GridGain In-Memory Data Fabric is a Development solution with tags like inmemory, database, data-grid, distributed-computing.

It boasts features such as 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 and pros including 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.

On the other hand, Infinispan is a Development product tagged with caching, distributed-cache, inmemory-data-grid.

Its standout features include Distributed in-memory key/value data store, Supports transactions, Data partitioning, Data replication, Persistence to disk or database, Querying and indexing, Caching for databases, Clustering and high availability, and it shines with pros like Very fast data access, Scalable and elastic, Fault tolerant, Supports many data structures, Integrates with many frameworks/platforms, Open source with large community.

Feature	GridGain In-Memory Data Fabric	Infinispan
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

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.

Infinispan

Description: Infinispan is an open source in-memory data grid and distributed cache. It is used to store and retrieve data with microsecond response times, while providing data reliability and availability.

Key Features Comparison

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

Infinispan Features

• Distributed in-memory key/value data store
• Supports transactions
• Data partitioning
• Data replication
• Persistence to disk or database
• Querying and indexing
• Caching for databases
• Clustering and high availability

Pros & Cons Analysis

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

Infinispan

Pros

• Very fast data access
• Scalable and elastic
• Fault tolerant
• Supports many data structures
• Integrates with many frameworks/platforms
• Open source with large community

Cons

• Complex to configure and operate
• Not ideal for durable long-term storage
• Can be resource intensive
• Not as fully featured as some proprietary options

Pricing Comparison

GridGain In-Memory Data Fabric

• Open Source
• Freemium
• Subscription-Based

Infinispan

• Open Source