|
A new approach to data compression
Compression
is as old as personal computing, but up until recently it was used mainly
for backup and second tier storage. Many attempts to address
the challenges of primary storage compression have failed
because of degraded performance and lack of transparency.
| Introducing: Real-Time Compression |
Because
compression of primary storage data has been difficult to
address, most data capacity reduction efforts in recent years have been directed at
compression during remote transport. This type of compression
saves bandwidth but does nothing to reduce stored data volumes.
Attempts to compress primary storage data interfered with
user workflow and required running software on both storage
and end-user devices. These solutions were based on cumbersome
sequential access (decompress, update, recompress), work at
file-level granularity, or both.
They also wasted client resources and
introduced unacceptable latencies.
Storwize primary data compression solution process in real-time only the data required for a particular user or application, and supports multiple applications and data types. The Storwize data compression approach delivers real-time lossless data compression using a dedicated high-performance data compression appliance deployed between the organization’s network switch and storage and save space on primary storage and all related copies without compromising performance, functionality or data integrity.
| |
Full
transparency for |
| |
Client
OS
Applications
Storage unit
|
| |
Real-time
random access to compressed data |
| |
Read from any location in the
compressed data
Modify any location in the compressed
data
|
| |
Storage performance is not compromised |
| |
No CPU or memory penalty for clients or storage (compression process is performed in a sole-purpose appliance designed and optimized for this specific task)
Smaller datagram size on storage subsystem allows reducing storage
workload and frees potential bottlenecks (disks CPU, cache mechanisms
and more)
Data is handled in compressed form, leading to significant reductions
in storage systems’ CPU and disk utilization and improvement in the effective storage cache.
|
| |
Complementary
solution |
| |
Storwize compression is transparent and complementary to other
data footprint reduction solutions such as Virtualization, Deduplication
and Thin Provisioning.
|
|
 |
|