Coginiti

Formerly Aginity

Big data analytic, it's able analyze large data warehouse.

Very easy to use especially connecting to various database.

Productivity tracking.

Navigation something is about tedious.

We had installation issues ,it would be great to have easier installation option.

The system freezes when I press execute.

Accessing data scattered in relational datbases.

Creating sophisticated analytics with SQL interface.

Reusing and sharing past projects with colleagues.

Aginity do not offer capabilities for large enterprise organizations.

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.

The vendor hasn't offered enough tutorials inform of documentations and articles for all Aginity features.

Aginitu Amp gives both data scientists and business users the capabilities to build, reuse and share advanced analytics easily.

The Intuitive user interface allows data scientists and business analysts to build, reuse, and share analytics without SQL or coding.

Error message windows and closes before the user can read them, hence leaving the user in suspension mood, and hovering my finger over the print screen capturing them.

Navigation sometimes its a little bit buggy.

See the list of tables, views, procedures

help preparing some queries, such as select top 100, reclaims, etc

run many queries all together and monitor the execution of each of them

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

Transactions isolation

Queries

Schema visualization

Performance

It would be nice to have more performance features

Query auto-completion

Database exploration including schemas, tables, columns, distribution keys, sort keys, etc.

Common scenario query samples, and easy access to table DDL

Table size operational report

Free community edition

It would be helpful if the table size report could make it more obvious which tables need to be vacuumed. You can figure it out with the report, but can't just glance down a list.

Error message windows often auto close before you can read them leaving me hovering my finger over the print screen trying to capture them.

The auto-complete feature is a bit finicky. Many common scenarios which happen while writing a query by hand such as an unclosed parenthesis can cause the auto-complete not to trigger.

Cleaner than most GUI's.

Easy to read.

Drag in table names instead of writing them.

Would not sort fields alphabetically!

Hard to tell when it was running and locked.

Navigating can be a pain and can be buggy (click one table, and another table is selected).

Transparent database -> table information. The columns for a specific table/view is listed out within the object browser, and the object browser is easy to navigate, for providing a clear picture of the tables/views, and what it's made up of. Including column data types, data length, and space usage. The object browser follows a collapsible format, breaking down databases by schema names, following with the table/view names, and then the columns specific to that table/view. This in my opinion, is easier than the object browser that Toad provides, where you have to select into a specific table in order to see it's contents and details, rather than being able to compare and have everything on one page.

The output window is easy for further data extraction, one can simply copy the data out onto an email, into an excel spreadsheet, or other places as necessary. Data could also be exported from the output window, into either excel spreadsheets, or CSV format files, without the need to convert between one or the other. A special area is reserved for dragging column headers into, and what it does is it groups information by that column. This allows flexible user grouping, without the need of writing SQL queries to group on columns. Often times, in my experience, I find the need to group columns on a to-go basis, where I review the data output, and find the need to group on certain columns for further research and analysis, this option allow me to manipulate the result I currently have, without the need to rerun a query for grouping inclusions.

Able to cascade query windows between different environments. I often need to cascade query windows between an UAT environment, a RESEARCH environment, and a PRODUCTION environment. To be able to cascade between them, and to reference queries and its results, is a huge plus, that I didn't find in some of the other products I've used. This allow me to reference information in between different environments, without the need to connect back and forth.

For one, I don't like how the parenthesis are automatically created as a set. Often times I only need to type one part of the parenthesis, but it creates a set of ( and ), forcing me to delete them because I didn't need the other half at where my cursor was. Same goes with any other sort of characters, such as ' '. I understand that it's suppose to be smart, but more often than not, it's causing more inconvenience and wasting more time, than actually saving time simply because it types an extra ) or ' for me.

The error message and the log. I would think there probably is a log somewhere, but the fact that I've been using Aginity for close to a year now, and I still haven't found something similar to a log, is saying something about this feature. A log is like a standard thing nowadays, for running codes, to check against what has happened with the code, and for debugging what you have done wrong within the code. It also contains error messages, and help you troubleshoot with a clearer picture. The error message display current is very small and hard to read, sometimes the error message itself is not as easy to understand either. I use SAS on a daily basis as well, I feel like SAS has done a way better job on this issue, than Aginity.