TrustRadius Insights for Coginiti are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Pros
Intuitive User Interface: Many users have found the user interface of the big data analytic software to be intuitive and easy to use, especially when connecting to various databases. They appreciate how it simplifies their workflow and makes it easier to navigate through different features.
Transparency of Database: Reviewers have appreciated the transparency provided by the software's database, which includes detailed table information such as columns, data types, data length, and space usage. This feature has been particularly helpful in understanding and analyzing the structure of the database.
Collapsible Object Browser: The object browser in the software is highly praised by users for its ease of navigation. It allows them to have a clear picture of tables and views, along with their composition. Users prefer its collapsible format organized by schema names, table/view names, and specific columns over other similar software options.
Aginity is a Very reliable tool that has been enabling our organization to access databases or external files for integration this feature has immensely improved our work efficiency and productivity. also, its ability to access past tasks has been helping us to refer back and share data. agility offers excellent data synchronization helping us maintain consistency within the system.
Pros
Big data analytic, it's able analyze large data warehouse.
Very easy to use especially connecting to various database.
Productivity tracking.
Cons
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.
Likelihood to Recommend
Aginity is able to track productivity which has been helping us be able to determine areas that need improvement. we have found agility very user-friendly in terms of ease of scalability. moreover, its ability to reuse SQL has saved us a lot of time because we do not have to re-code SQL.
It's almost two years now ever since I started using Aginity at my workstation. Aginity is used in a few selected departments in my current firm. I use it to access data in relational databases and external applications and integrate it to Aginity pro.
Pros
Accessing data scattered in relational datbases.
Creating sophisticated analytics with SQL interface.
Reusing and sharing past projects with colleagues.
Cons
Aginity do not offer capabilities for large enterprise organizations.
Likelihood to Recommend
Aginity allocates a wide array of BI and analytics tools in a single cloud system. I would recommend my colleagues and other business persons to implement it in order to eradicate spreadsheets and manual data analysis processes.
Aginity had empowered our employees with BI, database management, and analytics tools that make it effective to re-use SQL codes. Aginity is used in a few selected departments to drive more innovations by sharing the team's SQL skills in one central location.
Pros
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.
Cons
The vendor hasn't offered enough tutorials inform of documentations and articles for all Aginity features.
Likelihood to Recommend
Aginity once customized to optimal can suit a lot of business processes such as data cleansing, business process automation, and sharing SQL code lines with others. We have been able to collaborate in one secure platform in our organization with this tool where we share useful SQL codes for free.
Aginity is the tool we use in order to query the database. We [use] it for IBM Pure Data (Netezza), Hortonworks and we had some trials with DB2. We use it in order to see all objects' metadata, to review DDL and DML on existing structures, and to see information regarding columns, keys, distribution, and so on.
Pros
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
Cons
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
Likelihood to Recommend
Aginity is almost always friendly and easy to use. Therefore anybody could start using it without any doubt. The queries helping you to prepare some fix or other operation on the DB are really useful and allow users to save some time. Stored procedures are also well done, and export to file on the selected information is really easy to use.
VU
Verified User
Manager in Information Technology (201-500 employees)
We have been using Aginity mainly to connect to our Redshift instance and it has been very helpful to perform queries, do all the necessary maintenance, and follow in real-time what's going on in our environment.
Before start using Aginity, we were running everything in Redshift's editor what was causing a bit of trouble due to do not be the best way in terms of performance and productivity.
Pros
Transactions isolation
Queries
Schema visualization
Performance
Cons
It would be nice to have more performance features
Likelihood to Recommend
I would always recommend Aginity to you if you are looking for a tool to handle your queries easily and with a good performance. It is really easy to use the tool and you do not need to spend too much time learning. The price is also ok and if you are not really caring about analyze performance it fits very well.
VU
Verified User
Employee in Information Technology (11-50 employees)
Our business intelligence department all use Aginity to access our RedShift data. Our analyst team uses the tool to generate reports and run analysis on our data warehouse which lives in Amazon RedShift. Our business intelligence engineering team uses Aginity to perform some of the RedShift operational tasks and to validate data within the data warehouse.
Pros
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
Cons
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.
Likelihood to Recommend
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.
I used Aginity Workbench to build, update, and read from Netezza. Mainly, I used Aginity as a consultant to help build hand written ETL processes for a company I contracted with. In the organization itself, very few people used it aside from a few SQL-savvy business analysts. It is possible more people used it since I complete the contract more than 10 months ago. It really isn't being pushed by the organization, but served more as a portal to building an EDW.
Pros
Cleaner than most GUI's.
Easy to read.
Drag in table names instead of writing them.
Cons
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).
Likelihood to Recommend
I believe it is the standard GUI when working with Netezza. In that sense, I would recommend it. However, most GUIs are best suited for their native client. I'm not about to connect this to Redshift, Greenplum, or anything else. Then again, I have not tried connecting to those, so I can not speak poorly of its capability to do so. I just tend to choose the recommended tool.
It is being used by my department, and possibly some other departments, but not across the entire organization. I know Toad is also a popular tool, since Aginity is specific to Netezza, and Netezza is going to be retired in the near future for my department. It addresses the business need for data analysis, by providing a direct interface to our Netezza database, for designing, creating, and executing SQL queries. It allows transparent data viewing and data research.
Pros
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.
Cons
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.
Likelihood to Recommend
Overall I like Aginity for what it has to offer right now. I also use SAS on a daily basis, and whenever I need to create scripts for flexible and repeatable automation processes, I go to SAS for its macro facilities. To me, Aginity works very well for quick data research, but other programs such as SAS are more suited for robust analysis involving complicated coding.
