Hitachi Lumada Data Integration vs IBM InfoSphere DataStage comparison

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Executive Summary

We performed a comparison between Hitachi Lumada Data Integration and IBM InfoSphere DataStage based on real PeerSpot user reviews.

Find out in this report how the two Data Integration Tools solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Hitachi Lumada Data Integration vs. IBM InfoSphere DataStage Report (Updated: March 2023).
688,083 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"We can schedule job execution in the BA Server, which is the front-end product we're using right now. That scheduling interface is nice.""It has a really friendly user interface, which is its main feature. The process of automating or combining SQL code with some databases and doing the automation is great and really convenient.""I can use Python, which is open-source, and I can run other scripts, including Linux scripts. It's user-friendly for running any object-based language. That's a very important feature because we live in a world of open-source.""Lumada has allowed us to interact with our employees more effectively and compensate them properly. One of the cool things is that we use it to generate commissions for our salespeople and bonuses for our warehouse people. It allows us to get information out to them in a timely fashion. We can also see where they're at and how they're doing.""One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs.""Flexible deployment, in any environment, is very important to us. That is the key reason why we ended up with these tools. Because we have a very highly secure environment, we must be able to install it in multiple environments on multiple different servers. The fact that we could use the same tool in all our environments, on-prem and in the cloud, was very important to us.""One of the most valuable features is the ability to create many API integrations. I'm always working with advertising agents and using Facebook and Instagram to do campaigns. We use Pentaho to get the results from these campaigns and to create dashboards to analyze the results.""The fact that it's a low-code solution is valuable. It's good for more junior people who may not be as experienced with programming."

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"It is quite useful and powerful.""The best feature of IBM InfoSphere DataStage for me was that it was very much user-friendly. The solution didn't require that much raw coding because most of its features were drag and drop, plus it had a large number of functionalities.""It's a robust solution.""Offers great flexibility.""When we have needed help from the IBM team, they were helpful. Our company is a premium partner so we get fast responses.""It works with multiple servers and offers high availability.""The most valuable feature of the solution is the ability to incorporate very complex business rules in Data Stage.""As a data integration platform, it is easy to use. It is quite robust and useful for volumetric analysis when you have huge volumes of data. We have tested it for up to ten million rows, and it is robust enough to process ten million rows internally with its parallel processing. Its error logging mechanism is far simpler and easier to understand than other data integration tools. The newer version of InfoSphere has the data catalog and IDC lineage. They are helpful in the easy traceability of columns and tables."

More IBM InfoSphere DataStage Pros →

Cons
"It could be better integrated with programming languages, like Python and R. Right now, if I want to run a Python code on one of my ETLs, it is a bit difficult to do. It would be great if we have some modules where we could code directly in a Python language. We don't really have a way to run Python code natively.""If you develop it on MacBook, it'll be quite a hassle.""In the Community edition, it would be nice to have more modules that allow you to code directly within the application. It could have R or Python completely integrated into it, but this could also be because I'm using an older version.""I work with different databases. I would like to work with more connectors to new databases, e.g., DynamoDB and MariaDB, and new cloud solutions, e.g., AWS, Azure, and GCP. If they had these connectors, that would be great. They could improve by building new connectors. If you have native connections to different databases, then you can make instructions more efficient and in a more natural way. You don't have to write any scripts to use that connector.""Its basic functionality doesn't need a whole lot of change. There could be some improvement in the consistency of the behavior of different transformation steps. The software did start as open-source and a lot of the fundamental, everyday transformation steps that you use when building ETL jobs were developed by different people. It is not a seamless paradigm. A table input step has a different way of thinking than a data merge step.""Some of the scheduling features about Lumada drive me buggy. The one issue that always drives me up the wall is when Daylight Savings Time changes. It doesn't take that into account elegantly. Every time it changes, I have to do something. It's not a big deal, but it's annoying.""I have been facing some difficulties when working with large datasets. It seems that when there is a large amount of data, I experience memory errors.""Lumada could have more native connectors with other vendors, such as Google BigQuery, Microsoft OneDrive, Jira systems, and Facebook or Instagram. We would like to gather data from modern platforms using Lumada, which is a better approach. As a comparison, if you open Power BI to retrieve data, then you can get data from many vendors with cloud-native connectors, such as Azure, AWS, Google BigQuery, and Athena Redshift. Lumada should have more native connectors to help us and facilitate our job in gathering information from these new modern infrastructures and tools."

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"The initial setup could be more straightforward.""The solution can be a bit more user-friendly, similar to Informatica.""It would be useful to provide support for Python, AR, and Java.""The error messaging needs to be improved.""Its documentation is not up to the mark. While building APIs, we had a lot of problems trying to get around it because it is not very user-friendly. We tried to get hold of API documentation, but the documentation is not very well thought out. It should be more structured and elaborate. In terms of additional features, I would like to see good reporting on performance and performance-tuning recommendations that can be based on AI. I would also like to see better data profiling information being reported on InfoSphere.""Their web interface is good but the on-prem sites are outdated. The solution could also be improved if they could integrate the data pipeline scheduling part of their interface.""Currently lacking virtualization ability.""In the future, I would like to see more integration with cloud technologies."

More IBM InfoSphere DataStage Cons →

Pricing and Cost Advice
  • "It does seem a bit expensive compared to the serverless product offering. Tools, such as Server Integration Services, are "almost" free with a database engine. It is comparable to products like Alteryx, which is also very expensive."
  • "I think Lumada's price is fair compared to some of the others, like BusinessObjects, which is was the other thing that I used at my previous job. BusinessObject's price was more reasonable before SAP acquired it. They jacked the price up significantly. Oracle's OBIEE tool was also prohibitively expensive."
  • "When we first started with it, it was much cheaper. It has gone up drastically, especially since Hitachi bought out Pentaho."
  • "The cost of these types of solutions are expensive. So, we really appreciate what we get for our money. Though, we don't think of the solution as a top-of-the-line solution or anything like that."
  • "The pricing has been pretty good. I'm used to using everything open-source or freeware-based. I understand that organizations need to make sure that the solutions are secure, and that's basically where I hit a roadblock in my current organization. They needed to ensure that we had a license and we had a secure way of accessing it so that no outside parties could get access to our data, but in terms of pricing, considering how much other teams are spending on cloud solutions or even their existing solutions, its price point is pretty good. At this time, there are no additional costs. We just have the licensing fees."
  • "There was a cost analysis done and Pentaho did favorably in terms of cost."
  • "If a company is looking for an ETL solution and wants to integrate it with their tech stack but doesn't want to spend a bunch of money, Pentaho is a good solution"
  • "You need to go through the paid version to have Hitachi Lumada specialized support. However, if you are using the free version, then you will have only the community support. You will depend on the releases from Hitachi to solve some problem or questions that you have, such as bug fixes. You will need to wait for the newest versions or releases to solve these types of problems."
  • More Hitachi Lumada Data Integration Pricing and Cost Advice →

  • "The price is expensive but there are no licensing fees."
  • "It is quite expensive."
  • "It's quite expensive."
  • "I have no information on the exact pricing for IBM InfoSphere DataStage because the solution is usually procured by the clients my company works with, though the pricing is higher compared to other solutions, so many clients choose to go with a different solution rather than IBM InfoSphere DataStage."
  • "The pricing depends on the setup. However, we paid $100,000 as a one-time cost for an on-premises setup."
  • More IBM InfoSphere DataStage Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Hi Rajneesh, yes here is the feature comparison between the community and enterprise edition :… more »
    Top Answer: In my opinion, the reporting side of this tool needs serious improvements. In my previous company, we worked with Hitachi Lumada Data Integration and while it does a good job for what it’s worth, it… more »
    Top Answer:My company has used this product to transform data from databases, CSV files, and flat files. It really does a good job. We were most satisfied with the results in terms of how many people could use… more »
    Top Answer: My company currently uses the free version of the product, and we are definitely switching to a paid one. We needed a tool that can help us not only integrate our data but use it effectively. For the… more »
    Top Answer: I think the tool may cause some difficulties if you have not used other data integration solutions before. I have worked at companies that used different tools for data integration, and they work… more »
    Top Answer:IBM Cloud Paks makes a big difference in your data integration. My company has been using it alongside IBM InfoSphere DataStage and while the main product is good on its own, this one truly expands… more »
    Ranking
    6th
    Views
    6,004
    Comparisons
    3,376
    Reviews
    24
    Average Words per Review
    1,319
    Rating
    7.8
    11th
    Views
    15,280
    Comparisons
    12,493
    Reviews
    11
    Average Words per Review
    466
    Rating
    7.7
    Comparisons
    Also Known As
    Kettle, Pentaho Data Integration
    Learn More
    Overview

    Hitachi Lumada Data Integration is a top-raking data integration tool that aims to deliver accurate data from various sources to end users. This is a complete data integration platform that utilizes visual tools in the delivery of analytics-ready data. The product eliminates coding and complexity to ensure equal accessibility of its services to IT users as well as businesses that do not specialize in the field.

    The solution offers powerful data integration, which is achieved through:

    • Accelerated data onboarding
    • Flexible data self-service
    • Robust data flow orchestration

    Users of Hitachi Lumada Data Integration can collaborate to build, deploy, and monitor dataflows in order to streamline data delivery. The visual tools of the product reduce the time of operation and lower complexity, allowing even beginners to operate the platform seamlessly. The onboarding process is initiated through broad connectivity to a wide variety of data sources and applications.

    A drag-and-drop interface allows users to easily create data pipelines and ready-made templates to execute edge to cloud. The product provides users with the opportunity to blend data on premises or using cloud services, including Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). The tool allows for a seamless switch between the native engine and Apache Spark, and operationalizes Python, Scala, and Weka machine-learning models.

    The tool offers features for extensive business analytics through:

    • Ad-hoc analysis
    • Flexible interface
    • Enterprise reporting

    Hitachi Lumada Data Integration offers its clients modern data architectures for data analytics. Through interactive visualizations and easy integration, users are able to increase data integrity for their organizations. The product offers a web-based drag-and-drop dashboard for a flexible experience, collaboration with other applications, and advanced multi tenancy. There is special enterprise reporting which consists of operational self-serving reporting, security with content permissions, and additional high-level protection, achieved through locking, and expirations.

    Hitachi Lumada Data Integration Features

    The tool offers its clients various features which can be used to achieve efficient data integration and further analysis. These features include:

    • Data access: The tool allows users to access data sources at the edge, core, and cloud. This reduces the time and complexity of the process while blending sources to deliver data in a format ready to be analyzed.

    • Machine learning: The solution offers a feature to orchestrate machine learning. R, Python, Scale, and Weka models are provided to users of this product.

    • Enterprise reporting: Hitachi Lumada Data Integration provides its clients with detailed visualized reporting. This feature is highly secured, which provides additional protection for clients' data.

    • Connect and move: This feature offers users the option to connect to sources on premises or in the cloud and move data of any size and format.

    • Flexibility: The product allows users broad connectivity and flexibility with no vendor lock-in to on-premise or cloud services.

    • Cluster to container: The tool offers the option to create scalable pipelines with Kubernetes clusters. This is possible across multiple clouds.

    • Dataflow studio: This feature allows users to build and manage data pipelines, view run metrics, analyze activities, and resume paused ones.

    • Authoring: The tool has an editor feature, which allows for the transformation of activities while the dataflow is in progress.

    Hitachi Lumada Data Integration Benefits

    The tool offers increased work productivity through efficient data integration. A number of the benefits include:

    • Ability to increase productivity in the work process due to effective automation.

    • Production deployment time can be sped up while saving costs for the company.

    • The no-code functionality improves pipeline quality in comparison to hand-coding data.

    • The tool offers high-quality reports which reduce implementation time.

    • Employees can save time and resources by manually embedding reporting and applications through this solution.

    • The utilization of this tool can increase business user adoption by improving data accuracy.

    Reviews from Real Users

    Philip R., a senior engineer at a comms service provider, says this product "Saves time and makes it easy for our mixed-skilled team to support the product".

    Ryan F., a senior data engineer at Burgiss, appreciates Hitachi Lumada Data Integration because low-code makes development faster than with Python.

    IBM InfoSphere DataStage is a high-quality data integration tool that aims to design, develop, and run jobs that move and transform data for organizations of different sizes. The product works by integrating data across multiple systems through a high-performance parallel framework. It supports extended metadata management, enterprise connectivity, and integration of all types of data.

    The solution is the data integration component of IBM InfoSphere Information Server, providing a graphical framework for moving data from source systems to target systems. IBM InfoSphere DataStage can deliver data to data warehouses, data marts, operational data sources, and other enterprise applications. The tool works with various types of patterns - extract, transform and load (ETL), and extract, load, and transform (ELT). The scalability of the platform is achieved by using parallel processing and enterprise connectivity.

    The solution has various versions, catering to different types of companies, which include the Server Edition, the Enterprise Edition, and the MVS Edition. Depending on which version a company has bought, different goals can be achieved. They include the following:

    • Designing data flows to extract information from multiple sources, transform the data, and deliver it to target databases or applications.

    • Delivery of relevant and accurate data through direct connections to enterprise applications.

    • Reduction of development time and improvement of consistency through prebuilt functions.

    • Utilization of InfoSphere Information Server tools for accelerating the project delivery cycle.

    IBM InfoSphere DataStage can be deployed in various ways, including:

    • As a service: The tool can be accessed from a subscription model, where its capabilities are a part of IBM DataStage on IBM Cloud Park for Data as a Service. This option offers full management on IBM Cloud.

    • On premises or in any cloud: The two editions - IBM DataStage Enterprise and IBM DataStage Enterprise Plus - can run workloads on premises or in any cloud when added to IBM DataStage on IBM Cloud Pak for Data as a Service.

    • On premises: The basic jobs of the tool can be run on premises using IBM DataStage.

    IBM InfoSphere DataStage Features

    The tool has various features through which users can integrate and utilize their data effectively. The components of IBM InfoSphere DataStage include:

    • AI services: The tool offers services such as data science, event messaging, data warehousing, and data virtualization. It accelerates processes through artificial intelligence (AI) and offers a connection with IBM Cloud Paks - the cloud-native insight platform of the solution.

    • Parallel engine: Through this feature, ETL performance can be optimized to process data at scale. This is achieved through parallel engine and load balancing, which maximizes throughput.

    • Metadata support: This feature of the product uses the IBM Watson Knowledge Catalog to protect companies' sensitive data and monitor who can access it and at what levels.

    • Automated delivery pipelines: IBM InfoSphere DataStage reduces costs by automating continuous integration and delivery of pipelines.

    • Prebuilt connectors: The feature for prebuilt connectivity and stages allows users to move data between multiple cloud sources and data warehouses, including IBM native products.

    • IBM DataStage Flow Designer: This feature offers assistance through machine learning design. The product offers its clients a user-friendly interface which facilitates the work process.

    • IBM InfoSphere QualityStage: The tool provides a feature that automatically resolves data quality issues and increases the reliability of the delivered data.

    • Automated failure detection: Through this feature, companies can reduce infrastructure management efforts, relying on the automated detection that the tool offers.

    • Distributed data processing: Cloud runtimes can be executed remotely through this feature while maintaining its sovereignty and decreasing costs.

    IBM InfoSphere DataStage Benefits

    This solution offers many benefits for the companies that utilize it for data integration. Some of these benefits include:

    • Increased speed of workload execution due to better balancing and a parallel engine.

    • Reduction of data movement costs through integrations and seamless design of jobs.

    • Modernization of data integration by extending the capabilities of companies' data.

    • Delivery of reliable data through IBM Cloud Pak for Data.

    • Utilization of a drag-and-drop interface which assists in the delivery of data without the need for code.

    • Effective data manipulation allows data to be merged before being mapped and transformed.

    • Creating easier access of users to their data by providing visual maps of the process and the delivered data.

    Reviews from Real Users

    A data/solution architect at a computer software company says the product is robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data.

    Tirthankar Roy Chowdhury, team leader at Tata Consultancy Services, feels the tool is user-friendly with a lot of functionalities, and doesn't require much coding because of its drag-and-drop features.

    Offer
    Learn more about Hitachi Lumada Data Integration
    Learn more about IBM InfoSphere DataStage
    Sample Customers
    66Controls, Providential Revenue Agency of Ro Negro, NOAA Information Systems, Swiss Real Estate Institute
    Dubai Statistics Center, Etisalat Egypt
    Top Industries
    REVIEWERS
    Healthcare Company19%
    Financial Services Firm19%
    Comms Service Provider11%
    Manufacturing Company11%
    VISITORS READING REVIEWS
    Computer Software Company17%
    Comms Service Provider13%
    Financial Services Firm13%
    Government7%
    REVIEWERS
    Computer Software Company70%
    Aerospace/Defense Firm10%
    Healthcare Company10%
    Financial Services Firm10%
    VISITORS READING REVIEWS
    Financial Services Firm22%
    Computer Software Company15%
    Manufacturing Company8%
    Insurance Company8%
    Company Size
    REVIEWERS
    Small Business27%
    Midsize Enterprise31%
    Large Enterprise42%
    VISITORS READING REVIEWS
    Small Business24%
    Midsize Enterprise10%
    Large Enterprise65%
    REVIEWERS
    Small Business47%
    Midsize Enterprise6%
    Large Enterprise47%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise10%
    Large Enterprise76%
    Buyer's Guide
    Hitachi Lumada Data Integration vs. IBM InfoSphere DataStage
    March 2023
    Find out what your peers are saying about Hitachi Lumada Data Integration vs. IBM InfoSphere DataStage and other solutions. Updated: March 2023.
    688,083 professionals have used our research since 2012.

    Hitachi Lumada Data Integration is ranked 6th in Data Integration Tools with 24 reviews while IBM InfoSphere DataStage is ranked 11th in Data Integration Tools with 10 reviews. Hitachi Lumada Data Integration is rated 7.8, while IBM InfoSphere DataStage is rated 7.8. The top reviewer of Hitachi Lumada Data Integration writes "Saves time and makes it easy for our mixed-skilled team to support the product, but more guidance and better error messages are required in the UI". On the other hand, the top reviewer of IBM InfoSphere DataStage writes "Robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data". Hitachi Lumada Data Integration is most compared with SSIS, Talend Open Studio, Informatica Enterprise Data Catalog, Azure Data Factory and Mule Anypoint Platform, whereas IBM InfoSphere DataStage is most compared with SSIS, Talend Open Studio, Azure Data Factory, AWS Glue and Informatica PowerCenter. See our Hitachi Lumada Data Integration vs. IBM InfoSphere DataStage report.

    See our list of best Data Integration Tools vendors and best Cloud Data Integration vendors.

    We monitor all Data Integration Tools reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.