Data domain compression type

  • How does Data Domain deduplication work?

    Data deduplication looks for redundancy of sequences of bytes across very large comparison windows.
    Sequences of data (over 8 KB long) are compared to the history of other such sequences.
    The first uniquely stored version of a sequence is referenced rather than stored again..

  • How does Data Domain work?

    Data Domain uses variable length deduplication, which takes a more intelligent approach to deduplication, varying the size of segments when looking for common data points.
    As data is ingested, Data Domain looks at this data and breaks it up into pieces or segments..

  • What is data domain used for?

    Here, a data domain is "a logical grouping of items of interest to the organization, or areas of interest within the organization".
    You can think of data domains as high-level categories of data for the purpose of assigning accountability and responsibility for the data..

  • What is the difference between Data Domain global compression and local compression?

    Data Domain compresses data at two levels: global and local.
    Global compression, or deduplication, is used to identify redundant data segments and store only the unique data segments by comparing received data to data already stored on disk, while local compression compresses the unique data segments..

  • What is the local compression algorithm used in Data Domain?

    Local compression compresses segments before writing them to disk.
    It uses common, industry standard algorithms (for example, Iz, gz, and gzfast).
    The default compression algorithm used by Data Domain systems is Iz..

  • Data Domain compresses data at two levels: global and local.
    Global compression, or deduplication, is used to identify redundant data segments and store only the unique data segments by comparing received data to data already stored on disk, while local compression compresses the unique data segments.
  • Deduplication removes redundant data blocks, whereas compression removes additional redundant data within each data block.
    These techniques work together to reduce the amount of space required to store the data. vSAN applies deduplication and then compression as it moves data from the cache tier to the capacity tier.
Apr 21, 2021Compression is a data reduction technology which aims to store a data set using less physical space. In Data Domain systems (DDOS), we do dedupe 
Local compression further compresses the unique data segments with certain compression algorithm(s), such as lz, gzfast, gz, etc. The overall user data compression in DDOS is the joint effort of dedupe and local compression. DDOS uses "compression ratio" to measure the effectiveness of its data compression.

What is NTFS compression?

NTFS compression is a feature of NTFS that you can optionally enable at the volume level.
With NTFS compression, each file is optimized individually via compression at write-time.
Unlike NTFS compression, Data Deduplication can get spacing savings across all the files on a volume.

What is local compression in DDoS?

Local compression further compresses the unique data segments with certain compression algorithm (s), such as lz, gzfast, gz, etc

The overall user data compression in DDOS is the joint effort of dedupe and local compression

DDOS uses " compression ratio " to measure the effectiveness of its data compression

String used for identify objects on Apple subsystems


A Uniform Type Identifier (UTI) is a text string used on software provided by Apple Inc. to uniquely identify a given class or type of item.
Apple provides built-in UTIs to identify common system objects – document or image file types, folders and application bundles, streaming data, clipping data, movie data – and allows third party developers to add their own UTIs for application-specific or proprietary uses.
Support for UTIs was added in the Mac OS X 10.4 operating system, integrated into the Spotlight desktop search technology, which uses UTIs to categorize documents.
One of the primary design goals of UTIs was to eliminate the ambiguities and problems associated with inferring a file's content from its MIME type, filename extension, or type or creator code.

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