Evaluate Pure Storage

FlashReduce Data Reduction

Essential for a cost-effective flash array.

5-10x reduction

graphic showing the strength of dedupe

  • Pattern RemovalPattern Removal
  • DeduplicationDeduplication
  • CompressionCompression
  • Deep ReductionDeep Reduction
  • Copy ReductionCopy Reduction

Purity FlashReduce employs five forms of high performance and inline data reduction techniques to reduce the data footprint by 5-10X, driving down storage costs.


Average Data Reduction Rate

(Deduplication + Compression Only)

5.54:1

5.54 = 2.71 (comp.) x 2.04 (dup.)
Useful for comparing vs. other storage
arrays with thin provisioning enabled.

  • 16.62
  • 7.88
  • 1.74
  • 7.50
  • 5.00
  • 3.67
  • 3.46
  • 5.72
  • 3.02
  • 3.01
  • 3.65
  • 6.14
  • 1.00
  • 6.38
  • 3.55
  • 6.75
  • 1.00
  • 5.65
  • 3.56
  • 13.93
  • 2.98
  • 3.74
  • 3.24
  • 3.34
  • 5.82
  • 3.60
  • 3.89
  • 8.48
  • 9.28
  • 4.19
  • 3.78
  • 5.48
  • 4.35
  • 4.38
  • 8.08
  • 5.37
  • 2.56
  • 5.22
  • 3.86
  • 3.68
  • 5.26
  • 1.00
  • 1.96
  • >20.00
  • 3.20
  • 7.32
  • 5.30
  • 5.27
  • 4.16
  • 4.84

FlashReduce Ticker

Real-time Data Reduction Results

  • >20.00
  • 1.00
  • 15.29
  • >20.00
  • >20.00
  • 9.72
  • >20.00
  • 7.22
  • 11.20
  • 14.72
  • >20.00
  • 6.59
  • 1.00
  • 8.08
  • >20.00
  • 9.59
  • 14.85
  • 17.66
  • 9.80
  • 8.48
  • 12.27
  • 6.26
  • 14.00
  • 1.00
  • >20.00
  • 12.66
  • >20.00
  • >20.00
  • 7.09
  • 4.60
  • 10.87
  • >20.00
  • 4.84
  • >20.00
  • 9.37
  • 6.18
  • 7.11
  • 18.96
  • 6.95
  • 8.84
  • 5.07
  • 15.31
  • 9.99
  • >20.00
  • 9.40
  • 9.24
  • >20.00
  • >20.00
  • 5.73
  • 5.96

Average Total Reduction

(Including Thin Provisioning)

12.33:1

Useful for comparing vs. other disk
arrays without thin provisioning,
including most other flash products.

Averaged across Pure Storage
FlashArrays, updated live 24x7.

How is data reduction calculated?

Last Updated: 03:30:54PM PDT

FlashReduce employs five different data reduction technologies.

We’ve got the data reduction you need for virtually any application.


Data
Reduction

CTO Deep Dive: Data Reduction

How much will my data reduce?

Data reduction works on a wide variety of applications and data types, but the only way to know how it functions on your data is to try it. The averages to the right are what we find typical for our most common use cases. If you want to analyze your data, try our PureSize tool, or request a trial deployment.

Virtual server environments

VMware or Hyper-V, consolidated virtual server environments with mixed applications.

4-6 to 1

Database environments

OLTP or OLAP, even databases get surprising amounts of data reduction.

2-4 to 1

Virtual desktop (VDI) environments

Virtual desktops (both persistent and non persistent) are one of the most reducible workloads in the datacenter.

5-10 to 1


How is Pure Storage data reduction different?

It's so fundamental to the FlashArray you can't even turn it off.

High performance.

Deduplication and compression in a flash array have to be fast. The FlashArray's core architecture was designed to support data reduction. All of our performance benchmarks are taken with data reduction turned–on.

Global and inline.

Other data reduction solutions dedupe as a post-process, and operate only inside a single SSD, LUN, card, or volume. Partitioning your data set dramatically reduces the savings from deduplication. Pure Storage dedupe is inline and global across the entire array.

Accelerates flash writes.

With flash storage, reading is easy; writing is the hard part. Inline deduplication and compression allow the FlashArray to avoid 70-90% of the writes it would otherwise do to flash, dramatically increasing the array's write bandwidth and extending the life of the underlying flash.


  • 512-byte granularity.

    8x smaller than the other guys.

    512-byte granularity

    In the world of deduplication, size matters. The smaller "chunk size" you use to look for duplicates, the more effective you will be at reducing data. But chunk size is a trade-off, as smaller chunks require more processing and metadata. Pure Storage detects duplicates down to a 512-byte chunk size, which has two advantages: substantially higher deduplication (typically 3-5X better than the coarse-grained alternatives), and that fine-grained geometry also offers better alignment with application data layouts.

  • Only possible with 100% flash.

    Enables high-performance dedupe
    and compression.

    At Pure Storage we realized early on that we couldn't deliver our breakthrough data deduplication algorithms if there was any mechanical disk in our array. Hear Pure Storage CTO and co-founder, John Colgrove, talk about how the FlashArray's architecture enables high-performance data reduction.

What about Thin Provisioning?

Of course it’s there. We just don’t brag about it like others do.

Pure Storage FlashArray is 100% thin provisioned. This means capacity for all volumes, all workloads is allocated dynamically on demand, thereby maximizing storing data (and not the storing of zeroes). While some vendors use thin provisioning as a way to boost data reduction savings, thin provisioning is not a data reduction technology. This is why the Dedupe Ticker on our website breaks out the average data reduction savings with deduplication and compression only as separate than average total reduction with thin provisioning included. Oh and granularity? It’s at the 512-byte level just like all Purity services, meaning that Purity thin provisioning delivers even more efficiency than the other guys.


Real customer results say a lot (and only store a little).

  • Logo Mattersight7.2 - to - 1
  • Logo Yodle6.2 - to - 1
  • Logo Siemens5.7 - to - 1
  • Logo City of Davenport6.5 - to - 1
  • Logo TripPak4.1 - to - 1