Reviews (1-4 of 4)
October 26, 2019
Score 9 out of 10
Aginity is used to query and fetch data from Hive and Netezza data-mart tables. We do produce operational and audit reports by fetching data through this tool as well.
- Aginity has well-suited drivers to connect to multiple relational data sources including Hadoop.
- Easy to select databases and tables in their object browser and describe the metadata.
- You can open multiple sessions each for dev-test and pros simultaneously which helps to validate data.
- Default query tuning hints and parallel joints.
- Improve response time when it’s objects are selected.
Read this authenticated review
Mostly suited for data analysis, validations and to use as an query tool to fetch data from sources.
April 26, 2017
Score 9 out of 10
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.
- 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.
Read Jordan Squire's full review
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.
April 20, 2016
Score 8 out of 10
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.
- 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.
Read Roger Luo's full review
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.
April 26, 2016
Score 7 out of 10
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.
- 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).
Read this authenticated review
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.