Alibaba Cloud Data Lake Analytics vs. Hashboard (discontinued)

For the scenario, we used Glean.io which we used the software to establish a database connection and build live dashboards on the data on this database. This was a very simple use case to explore the capabilities of the software. In this use case, it works very smoothly and well. Further, we looked into similar use cases using the data ops features to achieve data provisioning with code to have more control. This was a nice way to support data engineers for sure. I would say that - for our use cases - the UI-based set up does the job. It is nice to have more advanced options with data ops. But they are probably over the top for our use cases. I would say it is worth it though to explore and figure out which degree of control fits your use case best.

Incentivized

• Workflow is easy and clear due to clean and state of the art interface
• Model creation is easy
• Possibility for custom SQL code for database connection is very helpful

Incentivized

• Querying has to be done by users only. There can be ways to automate querying using templates
• Not able to clearly check the query run time
• The customer support team can be little more proactive while communicating any changes and resolving any queries

Incentivized

Glean.io provided the customisable packages as per the user licences and data storage required. We are a growing organisation and this flexibility helped arrive at decision to use Glean.io The user onboarding is very easy with Glean.io. There were no extra resources required to integrate with our system and it was done in couple of days only.

Incentivized

• Optimised the DB management team by 30%
• Reduce in data visualisation dashboards TAT by 50%
• Increase in revenues and savings by 20%

Incentivized