FlashArray

Data Reduction: essential for a cost-effective flash array.

5-10x reduction

graphic showing the strength of dedupe

Compression
Deduplication
Pattern Removal
Thin Provisioning

The FlashArray employs high-performance inline data reduction techniques including deduplication, compression, and thin provisioning to dramatically reduce the data footprint, allowing the logical size of the FlashArray to be 5-10X larger than its actual raw physical size, thereby driving down the $/GB usable. But don't take our word for it: check out the dedupe ticker below with real-time customer data reduction results.

Dedupe Ticker:

Real-time data
reduction results

Averaged across EVERY Pure Storage FlashArray, updated live 24x7.

5.75 : 1

Average Data Reduction Rate

(Deduplication + Compression Only)

Useful for comparing vs. other storage arrays with thin
provisioning enabled.

12.89 : 1

Average Total Reduction

(Including Thin Provisioning)

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

How is data reduction calculated?

Last Updated: 08:30:02PM

Averaged across EVERY Pure Storage FlashArray, updated live 24x7.

Think everyone’s got data reduction?

Not so fast, Jack. Here’s the skinny:

* As of May 2013

Flash Appliance/Array
Deduplication
Compression
Thin
Provisioning
Geometry
Inline
(vs. post-process)

Pure Storage FlashArray	Variable 512byte - 32K
Violin Memory	N/A	N/A
EMC XtremIO	Fixed 4 Kilobyte
IBM TMS+SVC	N/A

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.

Flasharray Demo Download the PureSize tool and
check your dedupe potential

Evaluate a FlashArray today.

How data
reduction works

Watch Now

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.

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.