IBM DataStage vs. SAS Data Management

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM DataStage
Score 8.6 out of 10
N/A
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.N/A
SAS Data Management
Score 8.0 out of 10
N/A
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.N/A
Pricing
IBM DataStageSAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM DataStageSAS Data Management
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
IBM DataStageSAS Data Management
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
IBM DataStage
9.1
9 Ratings
10% above category average
SAS Data Management
8.3
10 Ratings
1% above category average
Connect to traditional data sources9.59 Ratings8.610 Ratings
Connecto to Big Data and NoSQL8.88 Ratings8.19 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
IBM DataStage
9.5
9 Ratings
12% above category average
SAS Data Management
6.7
8 Ratings
22% below category average
Simple transformations9.89 Ratings6.18 Ratings
Complex transformations9.39 Ratings7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
IBM DataStage
9.0
9 Ratings
10% above category average
SAS Data Management
6.7
8 Ratings
20% below category average
Data model creation9.36 Ratings5.56 Ratings
Metadata management8.78 Ratings7.47 Ratings
Business rules and workflow8.18 Ratings6.67 Ratings
Collaboration9.09 Ratings7.07 Ratings
Testing and debugging9.59 Ratings6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
IBM DataStage
8.9
8 Ratings
8% above category average
SAS Data Management
7.9
9 Ratings
4% below category average
Integration with data quality tools8.88 Ratings7.69 Ratings
Integration with MDM tools9.08 Ratings8.27 Ratings
Best Alternatives
IBM DataStageSAS Data Management
Small Businesses
Skyvia
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Score 9.6 out of 10
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Score 9.6 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
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Score 8.2 out of 10
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Score 8.2 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
IBM InfoSphere Information Server
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Score 8.2 out of 10
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User Ratings
IBM DataStageSAS Data Management
Likelihood to Recommend
8.8
(9 ratings)
7.6
(11 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(2 ratings)
Usability
9.0
(2 ratings)
6.0
(2 ratings)
Performance
9.0
(1 ratings)
9.0
(1 ratings)
Support Rating
9.6
(3 ratings)
7.7
(6 ratings)
User Testimonials
IBM DataStageSAS Data Management
Likelihood to Recommend
IBM
Excellent Cloud data mapping tool and easy creating multiple project data analytics in real-time and the report distribution are excellent via this IBM product. Easy tool to provide data visualization and the integration is effective and helpful to migrating huge amounts of data across other platforms and different websites insights gathering.
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SAS
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.
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Pros
IBM
  • Data movement
  • Seamless integration of scripts and etl jobs
  • Descriptive logging
  • Ability to work with myriad of data assets
  • Direct integration for Governance catalog
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SAS
  • 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.
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Cons
IBM
  • Connector Stages to Snowflake on the cloud. We had some issues initially but since then had been corrected.
  • Accessing tool from a browser (zero foot-print). Currently we need to either install locally or connect to a server to do ETL work.
  • Diversify ways of authenticating users.
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SAS
  • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
  • Debugging errors from the logs is a complicated process.
  • E-mail alert system is very primitive and needs customization to make it more modern,
  • Cannot send SMS alerts for jobs.
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Likelihood to Renew
IBM
No answers on this topic
SAS
We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
IBM
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.
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SAS
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.
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Performance
IBM
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.
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SAS
It worked as expected.
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Support Rating
IBM
I believe that IBM generally has one of the worst and most complex assistance systems (physical and online) that exists.
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SAS
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.
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Alternatives Considered
IBM
It's obvious since they both are from the same vendors and it makes it easier and can get better rates for licensing. Also, sales rapes are very helpful in case of escalations and critical issues.
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SAS
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.
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Return on Investment
IBM
  • Reduce development time by 65% compared with hand coding.
  • Reduces ETL process maintenance times.
  • Better data governance for technical and non-technical people.
  • Improve time to market for initiatives that require data integration.
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SAS
  • We have more users who can connect to the many different data sources.
  • Our users do have existing SAS programming knowledge and that can carry over.
  • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
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