Scandit vs. Scanbot

Comparison guide for evaluating barcode scanning SDKs, based on performance testing results from controlled tests of real barcode scanning workflow tasks.

Development teams who’ve already chosen Scandit

Scandit vs. Scanbot under real-world conditions

We tested Scandit and Scanbot on realistic scanning tasks with the mid-range devices your teams actually use. All tests were run in July 2026.

Scandit scanned barcodes from a median of 2.1X further away

Why this matters: Users don’t waste time moving closer to the barcodes they need to scan, and there is less need for ladders or crouching down.

  • Scandit could scan from further away than Scanbot for every barcode type tested, with a median of 2.1X further away across the 7 measured barcode types.
  • Results ranged from an average of 1.7X further away for Codabar to 2.5X further away for EAN-13 and Data Matrix.
  • Test devices were mounted to a sliding test harness that moved incrementally closer to the barcode until it could be scanned, over 5 test runs. Environmental light was constant, and barcodes were calibrated to specific mil-sizes.

Scandit scanned ESLs from up to 3.2X further away

Why this matters: Electronic shelf labels (ESLs) are particularly challenging to scan due to the small size of barcodes, additional glare, and acute angles. A longer scan range improves usability as retail associates do not have to repeatedly bend down, reach up awkwardly, or spend time repositioning themselves.

  • We tested the distance from which a human using Scandit and Scanbot could scan ESLs on top, middle, and bottom retail shelves.
  • For ESLs with regular barcodes, Scandit scanned from 1.9X further away for middle shelves, 2X further away for top shelves, and 3.2X further away for bottom shelves.

Scandit captured the correct grocery shelf label 7 out of 7 times

Why this matters: In the real world, the barcode users want to scan is typically surrounded by other barcodes. Unintended scans interrupt workflows and lead to costly and time-consuming error correction further down the line if they go unnoticed.

  • The user attempted to scan 7 ESL labels showing EAN-13/UPC-A barcodes, positioned on a standard shelf rail. To simulate a real-world retail environment, products were also placed on the shelf above with their barcodes visible.
  • Scandit scanned the correct label every time and the workflow was completed in an average of 6.6 seconds. Scanbot captured an average of 9 unintended scans (i.e. belonging to another product) per test run. As a result of this, the workflow was completed in an average of 51.6 seconds.
  • Labels scanned sequentially over 5 test runs.
Bar chart showing true positive rates across 23 barcode conditions: Scandit higher in 16, tied in 5, Scanbot higher in 2.

Scandit beat Scanbot in 70% of tough code conditions

Why this matters: Barcodes are scanned under imperfect conditions in the real world, e.g., damage, glare, occlusion. Scanning difficulties reduce efficiency, and false positives result in bad data entering your systems.

  • We measured the true positive rate for difficult-to-scan codes using a test sheet covering 13 common scenarios for EAN-13 and Code 128 barcodes.
  • Scandit beat Scanbot in 70% (16 out of 23) tough code conditions.
Bar chart comparing fashion receiving scan speeds: Scandit scans 23 items per minute vs Scanbot's 19 items per minute.

Scandit was 1.2X faster in fashion receiving tests

Why this matters: Faster receiving frees up labor time for other tasks.

  • It took a human an average of 25.8 seconds to scan 10 plastic-wrapped shirts using Scandit, compared to 30.8 seconds using Scanbot.
  • This means that in 1 minute, Scandit would scan an average of 23 items and Scanbot would scan an average of 19 items.
  • Products were scanned sequentially over 5 test runs.

All tests run in July 2026.

Test environment:

Software: Scandit SDK 8.4.0 running on demo app with default settings. Scanbot Barcode Demo Version 1.11.0.76 ("Scanbot SDK: Barcode Scanning"), full HD resolution.

Devices: Samsung Galaxy A56 (comparable to an iPhone 13/14).

Barcode types tested: EAN13, Code128, Codabar, UPC-E, EAN8, QR code, and Data Matrix

Tough code conditions tested:

Focus blur, motion blur, occlusion, quiet zone violation, poor printing quality, bent, curved, glare, worn-out/degraded, damaged, low contrast, warped, and low resolution. The test sheet included multiple instances of each condition across EAN-13 and Code 128 symbologies.

The Scandit Product Engineering team uses an extensive suite of tests to measure scan performance on a wide range of devices and reflect real use cases in data capture. They support customers daily in executing performance testing, from setting up environments to making development recommendations based on the results. Robot-based testing is used to extract in-depth performance metrics. Use-case-specific testing (with human scanning) is used for specific scenarios and environments. Note that robot-based testing is not practical for all scenarios when testing data capture.

Scandit vs. Scanbot feature comparison

Feature and guidance

Scandit

Scanbot 

Barcode selection 

Select and interact with scanned barcodes

✓ Yes
Supports one or more barcodes

✓ Yes
Supports one or more barcodes (Select Scan)

Multiple barcode scanning

Reliably scan multiple barcodes with one press

✓ Yes

Includes barcode tracking and out-of-the box AR overlays for batch scanning, counting, finding items, information display

⚠ Limited

No multi-code tracking and limited pre-built workflows

Gesture support

Improve barcode recognition with on-screen gestures

✓ Yes

Built into SDK

✓ Yes

Built into SDK

Wide symbology support

Scan the barcodes you need for your workflow

✓ Yes

✓ Yes


Improved image capture using AI

Decodes barcodes under a broader range of difficult conditions

✓ Yes

Scandit Vision AI Engine

(ensemble of machine learning, vision language models, OCR, and other technologies)

✓ Yes

SDK includes machine learning and computer vision

Context-aware barcode scanning using AI

Faster, more accurate identification of what users want to scan

✓ Yes

Scanner adapts dynamically to environmental conditions and user behavior

✕ No

Does not appear to be included

Augmented reality assistance

Overlay additional information to guide users

✓ Yes

Customizable color, text, font, size, position, and automatic tracking

⚠ Limited

Colored frames and text over barcodes only 

Turnkey app

No-code solution to integrate scanning instantly

✓ Yes

Via Scandit Express

✕ No

Does not appear to include a turnkey app option

Agent Skills

Autonomous SDK integration with AI coding agents

✓ Yes

✕ No

Does not appear to include Agent Skills

User interface/pre-built components

Integrate purpose-built capabilities fast

✓ Yes

Range of UI controls and job-specific workflows (count, find, batch scanning, information display, expiry dates, retail electronics, weighted items, VIN scanning, price checks, and more) with customization options

⚠ Limited

Ready-to-Use UI Components (RTU UI) for batch scanning and find & pick only

Security and compliance

Scandit

Scanbot

On-device processing

✓ Yes

✓ Yes

Scans offline

✓ Yes

✓ Yes

Data encryption (in-transit and at-rest)

✓ Yes

⚠ Limited

Appears to be off by default (customizable through the Scanbot SDK Crypto Persistence library)

Usage tracking

⚠ Limited

Customers can choose whether metadata is transferred to external servers or not. Data is only transmitted for debugging, statistical analysis, performance monitoring, improvements and/or license compliance purposes.

✕ No

Does not appear to track usage

GDPR

✓ Yes

✓ Yes

HIPAA

✓ Yes

No protected health data processed.*

✓ Yes

ISO 27001

✓ Yes

✓ Yes

Pricing and licensing

Scandit

Scanbot

Pricing

Fixed and flexible pricing

Flat annual fee and usage-based pricing both available

Fixed pricing

Flat annual fee with unlimited scans

Licensing model

Annual license

A Community Edition for Education is also available

Annual license

Free trial options

30-day free trial

7-day free trial

Enterprise support and SLAs

Full lifecycle support from trial to production; 24/7 support and SLA-driven support plans available

Appears to offer technical support only

Results derived from side-by-side feature comparison in June 2026. For more information, see the Scandit website and Scanbot’s product pages and developer documentation. Some information in this post is based on publicly available sources at the time of publication and is believed to be accurate to the best of our knowledge. If anything is out of date or incorrect, please let us know and we'll update it.

*Scandit supports customers' own HIPAA compliance rather than bringing Scandit itself within the ambit of the legislation. As the product neither handles protected health information nor operates as a business associate, HIPAA imposes no direct obligations on Scandit.

Not just logos, results

The Scandit context-aware AI engine helps eliminate unintentional scans, a result of the environments Yuka users usually scan products in ... where barcodes are heavily prevalent.

François Martin, CTO and co-founder | 200-person consumer health start-up

See case study

80 million

global users

8.3 billion

scans to date

Two issues were important to us ... guaranteeing high performance across multiple types of barcode ... [and] how well the product would be supported. Scandit outperformed alternative open-source and plug-in solutions on both fronts.

Stefan Graf, Product Owner | 37,000-person national railway

See case study

The ability to batch scan from Scandit MatrixScan Count was huge. I did a demo of the solution before we launched and I had boxes set up vertically, some horizontal, some at an angle, and you could still just take your phone and it just picked everything up.

Stephen Prichard, Manager of Application Development | 1,600-person medical device manufacturer

See case study

5 min

to first scan in warehouse

I was blown away by the speed and accuracy, we also saw examples of barcodes that were worn or damaged where regular scanning couldn’t capture them, but Scandit could.

Doug Anteau, Director of Logistics and Warehouse Operations | 500-person enterprise mobility specialist

See case study

50%

faster processing times

30-40%

total cost savings

Don't underestimate how much the quality of your scanning technology shapes everything downstream.

Yixin Zhu, VP of Engineering | 200-person consumer grocery start-up

See case study

33%

increase in number of items posted to the platform each week

Frequently asked questions

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