Main Definition
Hot Data vs. Cold Data is a classification framework that separates frequently accessed files from inactive data to guide storage tiering and cost optimization. Every file in a storage environment falls somewhere on a spectrum of activity. Hot data is actively used, accessed regularly for ongoing workflows, analysis, or collaboration, and needs to live on responsive storage tiers. Cold data sits untouched for months or years and can move to more economical archives without affecting day-to-day operations.
The challenge in building your framework is first defining what constitutes hot and cold for distinct projects, and then accurately categorizing your data based on these definitions. Data that is more than 5 years old might still need to be kept within reach fast (medical imaging data, seismic data in oil and gas exploration), whereas in other environments, data can become obsolete in less than 6 months. The first step is to match the data with its owners and usage.
Starfish offers up to date and comprehensive file analytics, tagging, and classification features to help an organizations identify and label their hot and cold data. Once this analysis is completed, many organizations find there is substantial “cold data” sitting on expensive primary storage which can be systematically moved to archive. Starfish also enables data owners to classify and manage their data which takes the burden off of IT to come up with one size fits all definitions of hot and cold data.
Related links
- Cold vs Hot Data Storage: What’s the Difference? | Dataversity
- Hot vs. Cold Storage | Scality
- What’s the Diff: Hot and Cold Data Storage | Backblaze
- How ASU scratch storage went from instability to control | Starfish
