Connectivity is core to a data management tool and it should be highly broad-based. Ideally it should be 'any-to-any' in terms of platforms, data structure and data-types (apart from the ones which is technically not possible). There is a separate set of criteria list for the connectivity capabilities as it is relevant to may tool categories. Please refer connectivity tool feature.
- Universal capability to connect to any platform and data source: As already mentioned, it should be any source to any destination.
- Ability to handle unstructured and semi-structured data: This has not started happening recently where you can access unstructured data.
- Ability to access the static data and streaming data for sending and receiving data through web services: This is more to do with the mode of connectivity. A good DI tool will be able to access static and streaming data (as you get from a web service) and apply transformations and synchronization.
- Ability to handle streaming data especially for the real-time data and data picked from websites.
Grid Computing
Grid computing is a form of distributed computing whereby a "super and virtual computer" is composed of a cluster of networked, loosely-coupled computers, acting in concert to perform very large tasks.
Load-balancing
This is a typical computing capability for any kind of system. If your computing is done through multiple servers, a load balancing layer will assign tasks to ensure that servers are optimally loaded
Cluster implementations
A computer cluster is a group of linked computers, working together closely so that in many respects they form a single computer. The components of a cluster are commonly, but not always, connected to each other through fast local area networks.
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