Data storage products can differ and be specialised for different purposes. For example, datasets undergoing analysis and processing will require a different data storage product than a completed dataset requiring long-term preservation and dissemination. We have attempted to define four main data storage types to help researchers understand the options that are available. Defining each storage product by these categories is an over-simplification for the purpose of clarity, as many storage products do not neatly fit into a single category. Please get in contact with your Node to discuss your data storage requirements with a local expert in research data storage.
This table gives a brief overview of the features of the four defined data storage types.
| Data Storage Type | Scale | Term | Speed (I/O) | Security | Typical Use | Other |
|---|---|---|---|---|---|---|
| Archival | Large - Very Large | Long-term | Medium - Slow | Replicated, may include encryption | Infrequent changes, sharing, publication and preservation | Storage can be cheaper and replicated less frequently |
| Working | Large | Short - Medium | Medium - Fast | Replicated, may include encryption | Frequent changes, collaboration and development of research data | General active data storage |
| Computational | Small - Medium | Short-term | Fast | Not replicated | High speed connection to compute resources | Linked to HPC and Cloud Computing |
| Hosted | Small - Large | varies | varies | varies | Web access to search and read data | Data servers with web portals for access |
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