Adverity is a fully-integrated data platform for automating the connectivity, transformation, governance & utilization of data at scale.
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IBM DataStage
Score 7.7 out of 10
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IBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.
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Pricing
Adverity
IBM DataStage
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Adverity
IBM DataStage
Free Trial
Yes
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Adverity
IBM DataStage
Features
Adverity
IBM DataStage
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Adverity
-
Ratings
IBM DataStage
8.2
11 Ratings
0% below category average
Connect to traditional data sources
00 Ratings
8.411 Ratings
Connecto to Big Data and NoSQL
00 Ratings
8.010 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Adverity
-
Ratings
IBM DataStage
7.7
11 Ratings
5% below category average
Simple transformations
00 Ratings
8.011 Ratings
Complex transformations
00 Ratings
7.511 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Adverity
-
Ratings
IBM DataStage
6.9
11 Ratings
13% below category average
Data model creation
00 Ratings
6.68 Ratings
Metadata management
00 Ratings
5.010 Ratings
Business rules and workflow
00 Ratings
7.010 Ratings
Collaboration
00 Ratings
7.011 Ratings
Testing and debugging
00 Ratings
6.511 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Adverity is particularly useful if there is a large range of data sets that you want to combine to get an 'overall' view. Previously we had used Google Analytics, but found that this was too useful for our big client accounts that we were working on. So I think that if there is an individual who is responsible for analytics or data, and also a paid media team then this is a tool which is essential. For companies that have limited activity then I think this tool could potentially over-complicate for less reward.
DataStage is somewhat outdated for an ETL. I guess that's what makes it a bit lagged behind its competitors. It can be used for data processing, sure, but its performance seems to be lagging behind or quite slow given the server it is running from. I won’t depend on this application if it's handling a lot of mission-critical banking and business data.
I think it would have been more user friendly if there was more labelling capabilities, so that when you are sharing the dashboard they would explain what the data is - rather than depending on someone knowing how to use the dashboards or being there to explain it.
Our teams found that some of the scheduling functionality could be a little big buggy, so this was something that needed extra care and attention, so therefore may be an area that needs to be improved (unless it was just our account and usage).
Technical support is a key area IBM should improve for this product. Sometimes our case is assigned to a support engineer and he has no idea of the product or services.
Provide custom reports for datastage jobs and performance such as job history reports, warning messages or error messages.
Make it fully compatible with Oracle and users can direct use of Oracle ODBC drivers instead of Data Direct driver. Same for SQL server.
Because it is robust, and it is being continuously improved. DS is one of the most used and recognized tools in the market. Large companies have implemented it in the first instance to develop their DW, but finding the advantages it has, they could use it for other types of projects such as migrations, application feeding, etc.
It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
With effective capabilities and easy to manipulate the features and easy to produce accurate data analytics and the Cloud services Automation, this IBM platform is more reliable and easy to document management. The features on this platform are equipped with excellent big data management and easy to provide accurate data analytics.
This tool has allowed us to be able to see areas for opportunities, when all of the data has been combined
We were also able to better prioritise actions and where to focus our attention, when we had one view where all of the data was together. This allowed us to deliver better results for our clients, and also have a clearer roadmap of activity
It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.