Benchling’s cloud platform is used by pharmaceutical and biotech companies to analyze complex datasets, streamline research workflows, design DNA using CRISPR gene-editing technology and more.
$0
per month
Mendix
Score 7.2 out of 10
Enterprise companies (1,001+ employees)
Mendix is a low code platform-as-a-service offering with mobile and social extensions. Mendix was acquired by Siemens August 2018.
$0
Pricing
Benchling
Mendix
Editions & Modules
Academic
$0
Professional
Contact Benchling for price
Enterprise
Contact Benchling for price
Free Edition
$0
Pro Edition
1,250
per month (billed annually)
Enterprise Edition
1,675
per month (billed annually)
Offerings
Pricing Offerings
Benchling
Mendix
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
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Community Pulse
Benchling
Mendix
Features
Benchling
Mendix
Low-Code Development
Comparison of Low-Code Development features of Product A and Product B
Benchling is especially well suited to groups or contexts where there are many users who do not have a coding background but need a seamless and structured approach to data. Benchling is particularly useful in cases where there are data flows from instruments and other devices where the data can be deposited in an automated fashion. It is likely less appropriate or useful to users who are just looking for a general data warehouse solution.
Mendix excels in scenarios involving Business Process Automation, making it a strong choice for applications requiring workflow automation, including processes like request approvals, document management, and other business workflows.Conversely, Mendix may be less suitable for projects that demand highly customized solutions with extensive custom coding. Its primary focus on low-code development may not align well with the requirements of projects that heavily rely on intricate and specialized coding.
We're able to really easily develop different views that are very specific to a customer's needs or customer's different types of user needs. So for example, the production managers can have a certain view that's relevant to them and then certain line managers can have views that are specific to them that allow them to run different scenarios which they define. So it allows us to easily build customized apps for each different type of user.
Some of the integrations can be a bit spotty so it depends on what kind of data source you are integrating
Sometimes new users are not always aware of all the various functionality that Benchling has - can do better to provide more user awareness of more complex features
A 10 would say I have nothing to wish for. A 9 means I haven't seen anything better.This tool really helps you in the whole creation and maintenace cycle, so from requirements to building/modeling to testing to deploying to capturing feedback.
Response times are quick and you will get updates regularly about the status of your request. Even with very technical questions they have specialists that can help you with your problems it will give you an answer or help you with a work around.
Benchling was much more of a full stack solution and provide much more features that were relevant to the group. Airtable was more of a generic way to manage large amounts of data, but the complexity was still high for the types of data that would be need to be managed and there would need to be some workarounds. Overall Benchling was selected since it also had an electronic lab notebook feature which was very useful to associates in addition to its data workflows.
Mendix would be my preferred system all the way. The system is designed for these kinds of works. I've worked with WP and DNN but they should be used just for websites. To create an app for a business value, I would suggest Mendix. Also, the offline capabilities of Mendix have greatly improved since the deployment of Mendix 7.13.
It had a positive ROI in terms of reducing the amount of time spent on data movement and curation by associates
It had a positive ROI in terms of increasing the number of insights from structured data
It reduced the number of data entry and analysis errors by associates which led to a positive ROI in terms of efficiency and reducing time wasted by tracking down errors in data
It helps to speed up application development because of its low code by the fact that it's low code. It allows professional developers to focus more on specialized application development rather than the more routine application development that business IT and super users can do for themselves with some coaching from the IT department. So it's just allowing the more specialist professional developers.net, for example, Java in our organization to focus on more complex engineering application developments.
