Coginiti vs. Hashboard (discontinued)

Aginity is well suited for writing ad-hoc queries and data analysis, having all of the features that data analysts come to expect in a database querying tool. Aginity is also great for basic operation and management allowing an engineer or DBA to store multiple databases and credentials, see how tables are distributed or sorted, and see table sizes and row counts. However, for more advanced database management another tool or the RedShift console is still required

Incentivized

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

• Explore, model and analyze data across all company platforms.
• With Aginity, we improve team engagements where we can access and re-use colleagues' SQL.
• Make faster data-driven decisions with BI capabilities.

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

• with Hortonworks, you have to modify manually some settings in order to correctly see the metadata (HCAT properties)
• with reclaim, the generate only express statistics and "limit 100" on the select is a little risky if you do not pay attention.
• Saved views cannot be retrieved with the same [syntax] you wrote them, but they become really hard to read

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

Aginity learning curve was smooth and we didn't need to hire a specialist to teach us the system. it also offers free trials and a free version which enabled us to use and test the system's compatibility with our organisation's needs before fully investing in one. moreover, its ability to drag and drop tabs has made our work easier.

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

• I think Aginity really allows us to quickly dive into the data, by providing easy and quick access to our database. This allowed us to solve our business problems on an efficient and timely manner. But since it is not a critical component of our department, (a lot of people also use Toad for the same thing, since Netezza is retiring soon, and Aginity, which belongs to IBM, has had legal issues, and is no longer available to new hires of our department. It is sort of our legacy software.)

Incentivized

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

Incentivized