Benchling vs. SAP Datasphere

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.

Incentivized

SAP is best suited for large global corporations. It is a very complex software and is difficult to come by individuals who have sufficient enough knowledge to master the product. Globally our company only has 1 person to support us in IT for SAP. It is great if you use a more complex web host such as SFCC as you can make connections to SAP for returns, inventory, price updates, etc.

Incentivized

• Excellent easy to use and beautiful UI
• Great customer support and training
• Has no code ways of retrieving and depositing data

Incentivized

• SAP Data Warehouse Cloud offers free trial for 90 days with free 128 GB of storage and 64 GB memory.
• Availability of self-service data modeling and analytics on SAP Data Warehouse Cloud enables users to access and analyze data without getting support from the IT team.
• Without zero coding while collecting, connecting, analyzing and modeling data, it saves us time and operational costs of partnering with external IT support experts.

Incentivized

• 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

Incentivized

• SAP Data Warehouse Cloud is quite complex, therefore, some extra orientation or training might be essential, more so on cloud.
• Secondly, SAP Data installation fee, and the monthly subscription amounts is slightly demanding, and the developer should refocus on changing them.
• Nonetheless, SAP Data rectified other challenges like flexibility and customization, making us happy clients.

Incentivized

It is one of the best tools and a boon to Logistics teams across the globe. One tends to actually process warehousing data so smoothly and the way demonstration is made while in programs it makes it user friendly. The Inventory touch points that one identify is simply awesome and is best part.

Incentivized

I would greatly acknowledge the services of Sap Data [warehouse Cloud] because we were struggling before its arrival where we used to get manual data connections and this used to consume a lot of time but after its use, we now are able to connect data easily saving a lot of time and finances.

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.

Incentivized

Each of these listed software has its own unique strength and capacity that scales well. SAP Datasphere on its end up against them with more suitability for large establishments with complex data ecosystems with scalability support. Also, it avails a pay-as-you-go pricing for users, and it is widely up for data quality, data governance, and data discovery.

Incentivized

• 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

Incentivized

• Enhanced our report generation process due to presence of holistic data.
• Centralized data from all our platforms. This has helped us visualize and analyze all data much more efficiently.
• It is more on the expensive side from both cost and training perspective.

Incentivized