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
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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
Considered Both Products
IBM DataStage
Verified User
Anonymous
Chose IBM DataStage
IBM DataStage performes bettere than SSIS in every aspect. IBM DataStage performes better than SAP Data Services in terms of variables and job orchestration flexibility. It is as strong as ODI, but less complex to implement. It allows to write SQL queries as dbt and glue, but I …
its very good and i would get best support from ibm if their is any issue.i would upgrade it very easily.ibm red books are very good for learning and getting expertise on the product.we would get frequent updates when their is a patch released.it would be easy to integrate with …
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 …
IBM Infosphere DataStage has been in the market for more than a decade now. It is reliable and the user community online is vast and which helps with the resolution identification easily. IBM has done a good job keeping up with guiding connectors and links for new databases …
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.
Currently not using any of the Informatica tools, so, I don't have a real way of comparing the tools. But comparison against Microsoft SSIS (Sql Server Integration Services) I'd say DataStage stacks favorably. DataStage is a powerful tool for ETL processes that integrates …
Data Analyst | Data Developer - Advanced Analytics
Chose IBM DataStage
We chose IBM InfoSphere DataStage because it is the tool that has been used, historically, at the company level. In the near future, nothing prevents us from orienting ourselves to new solutions in view of a restructuring of architecture.
Compared to other ETL tools, the connectors really work, and makes the developments less complex because they facilitate the development of the processes. The maintenance of the processes is simple, since it is a very visual tool, and you can count on the technical …
DataStage offers better integration capabilities without the need to write code manually. It also has a native ETL engine whereas MSIS requires a SQL Server. It has better integration capabilities with data quality, data profiling and data governance tools. The main drawback of …
No, it wasn’t my decision to use such an ETL product. I’m just the administrator at this point. I’ve heard there are other products there that are even on cloud support. That is much easier to use, more agile, and user-friendly. That doesn’t have that barrier from user to …
The product is best when combined with the other products of the SAS suite. In particular, it's great for the preparation, analysis and display of the data if it is carried out with the products indicated above. When it is combined with products other than those of the SAS …
SAS Data Management Platform requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres. Has almost all features present as compared to the alternatives we evaluated. On top of it, SAS offered statistical transformations and strong metadata …
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.
Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end …
Datastage might be the closest one. Being a full ETL tool, it's weird to compare both. Datastage might be more robust for extraction but it lacks the simplicity that the end users need for everyday data extract and analysis.
SAS/Access can work well with MySQL. There are some coding differences between the two, for example how missing values are handled or rules for variable names. MySQL has simpler coding, but if you are familiar with Base SAS, it is not too difficult to learn. With SAS/Access the …
SAS integration is not easy because there are various PAM related modules which require additional vendor involvement. Overall once all integrations are set up, it's a great tool and provides multiple options to users for running their model.
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.
SAS/Access is well suited for companies who need to manipulate and analyze large databases and data-sets. It does the same thing as SQL, and if you already know basic SAS coding it is easier to pick up. SAS/Access works well with analyzing data from multiple data-sources at once, including large databases stored in external and virtual environments like Hadoop. Data can be easily reassembled from relational databases for use by the user. SAS/Access is not necessary if you are only pulling data from one database that you have the physical file for.
SAS supports the main database connection options that allow you to optimize the performance of your extracts and loads.
Simplicity of the syntax for a basic connection.
Ability to configure by an administrator in a BI environment so that all users can benefit from the connection without having to establish it by themselves.
It is a versatile product but sometimes difficult to use due to the very close link with the proprietary programming language where specific knowledge is required.
Compared to competitors on the market that offer the same functions for the integration perimeter, it is certainly very expensive.
It is very simple to use when combined with products from the SAS suite, less so it is being used stand-alone or integrated with other well-known brands.
Because it is a flexible tool that can manage many flows and create a strong solution with a interesting use of variables. Easy to scale up as you can copy jobs arleady build and modify them. SQL queries allow to be fast in development and have the pushdown feature, but you loose a little of user friendly look. Metadata management is not strong as a visual feature, but can be determine by job codes.
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.
No, it wasn’t my decision to use such an ETL product. I’m just the administrator at this point. I’ve heard there are other products there that are even on cloud support. That is much easier to use, more agile, and user-friendly. That doesn’t have that barrier from user to administrator to the developer standpoint.
Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end that allows us to transform and load our data quickly and efficiently programmer time wise.
Not directly related to ROI or cost figures. Only comment here is that IBM tools tend to be more costly than average ETL tools, but it depends on if the company is an IBM shop.
One positive aspect is the company has had not a need to switch ETL tool for years.
Upgrading to newer versions of the tool brings flexibility in the tool and up-to-date features in relation to other applications.