Delight customers and make better decisions
With ActiveSpaces, contextual, reference, and operational data normally housed in back-end applications can be stored in-memory for lightning fast performance that leads to delighting customers and beating the other guys. Any data store anywhere can now be included in real-time processing and decision-making.
Cost effectively use your big data
ActiveSpaces is built to handle large data volumes. You can dynamically add or drop nodes without requiring a system restart. Persistence is distributed across multiple commodity servers—and it's often possible to remove the database and associated failure points from traditional implementations and reduce reliance on costly transactional systems. You're left with a highly scalable, high-availability powerhouse that is a fraction of the cost of other methods.
Get on with the important stuff NOW
Instead of costly and time-consuming attempts (server reconfiguration, network and database tuning, architecture redesign), you can just get on with the important business of transforming to digital business capabilities. It’s a far faster, more straight-forward, more future-proof digital business solution. ActiveSpaces is key to the business of digital business. A proprietary, state-of-the-art hashing algorithm ensures a single network hop for fetching data for identifying patterns in the big data, coding those patterns into rules, and automating real-time execution of those rules against new data and opportunities.
Experiment and innovate simply, easily
Available as a Community Edition offering free development, test, and limited production use, ActiveSpaces gives you the chance to experiment and innovate without having to make upfront investments.
분산형 기록 시스템
ACID-compliant NoSQL Data Grid
Introducing TIBCO ActiveSpaces Community Edition, a free version of ActiveSpaces for development test and initial production use.
- Zero cost for development and entry-level production
- Registration-free access to software
- Strong community support for initial/small users