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InfiniSpan

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About InfiniSpan

InfiniSpan is a data grid software from Red Hat that provides distributed in-memory caching and data storage capabilities. It combines AI inference built for enterprise workloads, a reliable foundation for applications, and support for cloud-native environments so organizations can take their applications anywhere. InfiniSpan is designed to meet the demands of high-performance data processing and offers flexibility for developers working on complex applications. It supports distributed architectures, ensuring consistent performance across diverse workloads and scalability as business needs grow. Key capabilities: distributed caching fault tolerance data partitioning transactional data access support for various programming models Best for: enterprise organizations that need reliable data storage solutions for high-performance applications.

InfiniSpan Details

Vendor
Red Hat
Year Launched
2008
Location
100 E. Davie St., Raleigh, NC 27601, US
Deployment
cloud, on premise, windows, linux
Training Options
demo, account manager, community
Countries Served
All Countries
Languages
English, Spanish, French, German, Italian, Japanese, Korean, Chinese, Russian, Portuguese
Users
Java Developers, System Architects, Application Developers, DevOps Engineers, Open-source Contributors, Middleware Developers
Industries Served
Finance, E-commerce, Telecommunications, Government, Cloud Services, Healthcare, Software Development, Education, Enterprise IT, Retail
Tags
Database, NoSQL, Distributed, Caching, Clustering, Scalability, High Availability, Performance, Java, Red Hat

InfiniSpan's In-App Market Place

Does InfiniSpan have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
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Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD ($), CAD ($), CNY (¥), INR (₹), RUB (₽), BRL (R$).

Pros & Cons

  • Blazing Fast (In-Memory): Stores data in RAM for extremely low latency and high throughput, ideal for real-time applications.
  • Highly Scalable & Available: Distributes data across clusters, allowing elastic scaling and ensuring data is always accessible, even with failures.
  • Fault Tolerant & Resilient: Designed to prevent data loss and ensure continuity, with cross-site replication for disaster recovery.
  • Versatile Access: Supports native Java embedding, remote server mode, and compatibility with Redis/Memcached clients.
  • Memory-Bound: Being in-memory, the amount of data it can hold is limited by available RAM (though it can overflow to disk).
  • Operational Complexity: Setting up, configuring, and managing a distributed cluster can be complex, especially for large deployments.
  • Resource Intensive: Requires careful allocation of CPU and RAM for optimal performance, which can increase infrastructure costs.
  • Learning Curve: While easy for basic caching, mastering its advanced features (e.g., distributed transactions, custom marshalling) requires a deeper understanding.

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