Apache Hadoop vs. IBM DataStage

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.5 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
IBM DataStage
Score 7.7 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
Pricing
Apache HadoopIBM DataStage
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HadoopIBM DataStage
Free Trial
NoYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HadoopIBM DataStage
Features
Apache HadoopIBM DataStage
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Apache Hadoop
-
Ratings
IBM DataStage
8.1
11 Ratings
2% below category average
Connect to traditional data sources00 Ratings8.311 Ratings
Connecto to Big Data and NoSQL00 Ratings7.910 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Apache Hadoop
-
Ratings
IBM DataStage
7.7
11 Ratings
5% below category average
Simple transformations00 Ratings8.011 Ratings
Complex transformations00 Ratings7.411 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Apache Hadoop
-
Ratings
IBM DataStage
7.0
11 Ratings
11% below category average
Data model creation00 Ratings6.78 Ratings
Metadata management00 Ratings5.010 Ratings
Business rules and workflow00 Ratings7.110 Ratings
Collaboration00 Ratings7.111 Ratings
Testing and debugging00 Ratings6.611 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Apache Hadoop
-
Ratings
IBM DataStage
5.4
10 Ratings
38% below category average
Integration with data quality tools00 Ratings5.410 Ratings
Integration with MDM tools00 Ratings5.410 Ratings
Best Alternatives
Apache HadoopIBM DataStage
Small Businesses

No answers on this topic

Skyvia
Skyvia
Score 10.0 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.2 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopIBM DataStage
Likelihood to Recommend
8.0
(37 ratings)
6.9
(10 ratings)
Likelihood to Renew
9.6
(8 ratings)
-
(0 ratings)
Usability
8.0
(6 ratings)
8.0
(4 ratings)
Performance
8.0
(1 ratings)
9.0
(1 ratings)
Support Rating
7.5
(3 ratings)
9.6
(3 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
User Testimonials
Apache HadoopIBM DataStage
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
Read full review
IBM
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.
Read full review
Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
Read full review
IBM
  • Connect to multiple types of data-sources including Oracle, Teradata, Snowflake, SQl Server.
  • Powerful tool to load large volumes of data.
  • Transformation stages allow us to reduce the amount of code needed to create ETL scripts.
  • Allow us to synchronize and refresh data as much as needed.
Read full review
Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
Read full review
IBM
  • 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.
Read full review
Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
Read full review
IBM
No answers on this topic
Usability
Apache
As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
Read full review
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.
Read full review
Performance
Apache
No answers on this topic
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.
Read full review
Support Rating
Apache
It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
Read full review
IBM
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.
Read full review
Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
Read full review
IBM
No answers on this topic
Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
Read full review
IBM
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.
Read full review
Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
Read full review
IBM
  • 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.
Read full review
ScreenShots