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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SAS Data Management
Score 8.0 out of 10
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A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.
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Pricing
IBM DataStage
SAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM DataStage
SAS Data Management
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
IBM DataStage
SAS Data Management
Features
IBM DataStage
SAS Data Management
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
IBM DataStage
8.2
11 Ratings
0% above category average
SAS Data Management
8.3
10 Ratings
2% above category average
Connect to traditional data sources
8.511 Ratings
8.610 Ratings
Connecto to Big Data and NoSQL
8.010 Ratings
8.19 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
IBM DataStage
7.7
11 Ratings
4% below category average
SAS Data Management
6.7
8 Ratings
18% below category average
Simple transformations
8.011 Ratings
6.18 Ratings
Complex transformations
7.511 Ratings
7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
IBM DataStage
6.9
11 Ratings
12% below category average
SAS Data Management
6.7
8 Ratings
15% below category average
Data model creation
6.58 Ratings
5.56 Ratings
Metadata management
5.010 Ratings
7.47 Ratings
Business rules and workflow
7.010 Ratings
6.67 Ratings
Collaboration
7.011 Ratings
7.07 Ratings
Testing and debugging
6.511 Ratings
6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
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.
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
SAS/Access is great for manipulating large and complex databases.
SAS/Access makes it easy to format reports and graphics from your data.
Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
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.
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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 SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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.
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
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.