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Competitor Comparison

Device Detection Comparisons

Since launching our device detection solutions we have redefined the market, not only in terms of performance and quality of detection but also the breadth of our device data. We are often asked how we compare to other device detection suppliers, so using industry defined key metrics; we have compiled the following comparison table. These figures are constantly updating, so be sure to refer to the footnotes.

Key Metrics 51Degrees DeviceAtlas ScientiaMobile /WURFL TM
Device Combinations 740,3051,2 Unpublished >50,0003
Hardware Device Profiles 43,5281,4 34,0005 Unpublished
Platform Performance
(detections per second)
4 Core Arm 0.5 Million4 Unpublished Unpublished
2 Core Intel 1 to 1.9 Million4 1.7 Million6 Unpublished
20 Core Intel 7 to 15 Million4 Unpublished Unpublished
Average Time for a Single Detection Up to 0.002ms4,7 Unpublished Unpublished
Start Up Time From 224ms8 Unpublished Unpublished
Accuracy >99.9%4,9 99.9%10 99%3
Memory Overhead From 26MB8 Unpublished11 Unpublished
Confidence Indicators (false positives) Yes No No
Secure. On Premise Yes Yes Yes
Open Source Yes12 No No
Regular Expressions No Yes Yes
Transparent On Premise Pricing Yes13 No No
File Format Binary JSON XML
Data Sources Vendors and optional anonymous global usage sharing14 goMobi10 Unpublished
Multiple Environments Indexed for web, native apps, and mobile operator environments10,15 Unpublished
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All competitor information accurate at 27th June 2017 unless otherwise stated.
1 Combinations of hardware, operating system and web browser.
2 See 51Degrees Device Explorer for a full list of devices.
3 Source: ScientiaMobile Accuracy of our Device Intelligence.
4 Read "Device Detection Performance Analysis" for more information about the hardware and the data used in these performance tests.
5 Source: DeviceAtlas About our data.
6 Source: DeviceAtlas API Performance.
7 On premise device detection using a single CPU thread.
8 See Java benchmarks for more information.
9 51Degrees data processing system contains more than 150,000,000 unique HTTP headers including crawlers, apps and web browsers. 1.75% of the total available headers are used with the Pattern method to achieve 99.9% or greater device detection accuracy when compared to the full data set.
10 Source: DeviceAtlas Why DeviceAtlas.
11 DeviceAtlas claim their file size is 15MB, however this is not an indication of the memory used. 51Degrees can function without the full data file being loaded into memory.
12 See the 51Degrees Github repository.
13 See the 51Degrees Licensing and Pricing for more information.
14 See "How Device Data is Maintained and Distributed" for more information.
15 Read "51Degrees Announces Native App Device Detection Capability" for more information.