Hierarchical storage management
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Hierarchical storage management (HSM) is a data storage technique that automatically moves data between high-cost and low-cost storage media. HSM systems exist because high-speed storage devices, such as solid state drive arrays, are more expensive (per byte stored) than slower devices, such as hard disk drives, optical discs and magnetic tape drives. While it would be ideal to have all data available on high-speed devices all the time, this is prohibitively expensive for many organizations. Instead, HSM systems store the bulk of the enterprise's data on slower devices, and then copy data to faster disk drives when needed. In effect, HSM turns the fast disk drives into caches for the slower mass storage devices. The HSM system monitors the way data is used and makes best guesses as to which data can safely be moved to slower devices and which data should stay on the fast devices.
HSM may also be used where more robust storage is available for long-term archiving, but this is slow to access. This may be as simple as an off-site backup, for protection against a building fire.
HSM is a long-established concept, dating back to the beginnings of commercial data processing. The techniques used though have changed significantly as new technology becomes available, for both storage and for long-distance communication of large data sets. The scale of measures such as 'size' and 'access time' have changed dramatically. Despite this, many of the underlying concepts keep returning to favour years later, although at much larger or faster scales.
In a typical HSM scenario,[i] data files which are frequently used are stored on disk drives, but are eventually migrated to tape if they are not used for a certain period of time, typically a few months. If a user does reuse a file which is on tape, it is automatically moved back to disk storage. The advantage is that the total amount of stored data can be much larger than the capacity of the disk storage available, but since only rarely used files are on tape, most users will usually not notice any slowdown.
HSM (originally DFHSM, now DFSMShsm) was first implemented by IBM on their mainframe computers to reduce the cost of data storage, and to simplify the retrieval of data from slower media. The user would not need to know where the data was stored and how to get it back; the computer would retrieve the data automatically. The only difference to the user was the speed at which data was returned.
CSIRO Australia's Division of Computing Research implemented an HSM in its DAD (Drums and Display) operating system with its Document Region in the 1960s, with copies of documents being written to 7-track tape and automatic retrieval upon access to the documents.
HSM in the shape of the IBM 3850 Mass Storage Facility was (according to IBM) announced in 1974.[disputed (for: the 3850 is not HSM and IBM announced HSM later than the 3850.) ]
HSM was also implemented on the DEC VAX/VMS systems and the Alpha/VMS systems. The first implementation date should be readily determined from the VMS System Implementation Manuals or the VMS Product Description Brochures.
Recently, the development of Serial ATA (SATA) disks has created a significant market for three-stage HSM: files are migrated from high-performance Fibre Channel storage area network devices to somewhat slower but much cheaper SATA disk arrays totaling several terabytes or more, and then eventually from the SATA disks to tape.
Conceptually, HSM is analogous to the cache found in most computer CPUs, where small amounts of expensive SRAM memory running at very high speeds is used to store frequently used data, but the least recently used data is evicted to the slower but much larger main DRAM memory when new data has to be loaded.
In practice, HSM is typically performed by dedicated software, such as IBM Tivoli Storage Manager, Oracle's SAM-QFS, Versity Storage Manager, Quantum, Novell's Dynamic Storage Technology (DST) on Open Enterprise Server (OES) Linux Platform, HPE Data Management Framework (DMF, formerly SGI Data Migration Facility), StorNext, or EMC Legato OTG DiskXtender.
The deletion of files from a higher level of the hierarchy (e.g. magnetic disk) after they have been moved to a lower level (e.g. optical media) is sometimes called file grooming.
HSM is often used for deep archival storage of data to be held long term at low cost. Automated tape robots can silo large quantities of data efficiently with low power consumption.
Some HSM software products allow the user to place portions of data files on high-speed disk cache and the rest on tape. This is used in applications that stream video over the internet—the initial portion of a video is delivered immediately from disk while a robot finds, mounts and streams the rest of the file to the end user. Such a system greatly reduces disk cost for large content provision systems.
The key factor behind HSM is a Data migration policy that controls the file transfers in the system. More precisely, the policy decides which tier a file should be stored in, so that the entire storage system can be well-organized and have a shortest response time to requests. There are several algorithms realizing this process, such as Least Recently Used replacement(LRU), Size-Temperature Replacement(STP), Heuristic Threshold(STEP) and etc. In research of recent years, there are also some intelligent policies coming up by using machine learning technologies.
Tiered storage is a data storage environment consisting of two or more kinds of storage delineated by differences in at least one of these four attributes: price, performance, capacity and function.
Any significant difference in one or more of the four defining attributes can be sufficient to justify a separate storage tier.
- Disk and tape: two separate storage tiers identified by differences in all four defining attributes.
- Old technology disk and new technology disk: two separate storage tiers identified by differences in one or more of the attributes.
- High performing disk storage and less expensive, slower disk of the same capacity and function: two separate tiers.
- Identical enterprise class disk configured to utilize different functions such as RAID level or replication: a separate storage tier for each set of unique functions.
Note: Storage Tiers are not delineated by differences in vendor, architecture, or geometry except where those differences result in clear changes to price, performance, capacity and function.
- Amazon Glacier
- AMASS/DATAMGR from ADIC (Was available on SGI IRIX, Sun and HP-UX)
- IBM 3850 IBM 3850 Mass Storage Facility
- IBM DFSMS for z/VM
- IBM Tivoli Storage Manager for Space Management (HSM available on UNIX (IBM AIX, HP UX, Solaris) & Linux)
- IBM Tivoli Storage Manager HSM for Windows formerly OpenStore for File Servers (OS4FS) (HSM available on Microsoft Windows Server)
- HPSS by HPSS collaboration
- Infinite Disk, an early PC system (defunct)
- EMC DiskXtender, formerly Legato DiskXtender, formerly OTG DiskXtender
- Moonwalk for Windows, NetApp, OES Linux
- Oracle SAM-QFS (Open source under Opensolaris, then proprietary)
- Oracle HSM (Proprietary, renamed from SAM-QFS)
- Versity Storage Manager for Linux, open-core model license
- Dell Compellent Data Progression
- Zarafa Archiver (component of ZCP, application specific archiving solution marketed as a 'HSM' solution)
- HPE Data Management Framework (DMF, formerly SGI Data Migration Facility) for SLES and RHEL
- Quantum's StorNext
- Apple Fusion Drive for macOS
- Microsoft Storage Spaces since version shipped with Windows Server 2012 R2. An older Microsoft product was Remote Storage, included with Windows 2000 and Windows 2003.
- Active Archive Alliance
- Automated tiered storage
- Computer data storage
- Data proliferation
- Disk storage
- Information lifecycle management
- Information repository
- Magnetic tape data storage
- Memory hierarchy
- Repository (disambiguation)
- Storage virtualization
- Physical inventory
- An example from around 2000, which even now is looking dated as tape falls from favour.
- Larry Freeman. "What's Old Is New Again - Storage Tiering" (PDF).
- Patrick M. Dillon; David C. Leonard (1998). Multimedia and the Web from A to Z. ABC-CLIO. p. 116. ISBN 978-1-57356-132-7.
- O'Neil, Elizabeth J.; O'Neil, Patrick E.; Weikum, Gerhard (1993-06-01). "The LRU-K page replacement algorithm for database disk buffering". ACM SIGMOD Record. 22 (2): 297–306. doi:10.1145/170036.170081. ISSN 0163-5808.
- Verma, A.; Pease, D.; Sharma, U.; Kaplan, M.; Rubas, J.; Jain, R.; Devarakonda, M.; Beigi, M. (2005). "An Architecture for Lifecycle Management in Very Large File Systems". 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST'05). Monterey, CA, USA: IEEE: 160–168. doi:10.1109/MSST.2005.4. ISBN 978-0-7695-2318-7.
- IBM Corporation. "Abstract for DFSMS/VM Planning Guide". ibm.com. Retrieved Sep 16, 2021.
- [SAM/QFS at OpenSolaris.org 
- Rand Morimoto; Michael Noel; Omar Droubi; Ross Mistry; Chris Amaris (2008). Windows Server 2008 Unleashed. Sams Publishing. p. 938. ISBN 978-0-13-271563-8.