Azure Data Factory vs Oracle Data Integrator (ODI) comparison

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Executive Summary

We performed a comparison between Azure Data Factory and Oracle Data Integrator (ODI) 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 Azure Data Factory vs. Oracle Data Integrator (ODI) Report (Updated: November 2022).
656,862 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
"In StreamSets, everything is in one place.""I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks.""It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution.""StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes.""StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."

More StreamSets Pros →

"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code.""The initial setup is very quick and easy.""One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect.""The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted.""It is beneficial that the solution is written with Spark as the back end.""The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable.""Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data.""The best part of this product is the extraction, transformation, and load."

More Azure Data Factory Pros →

"The most valuable features of ODI are the knowledge modules, such as the Loading Knowledge module and the Check Knowledge module, they are helpful. We can check for the constraints in ODI. That helps in figuring out what are the constraints that are the primary keys created in the tables. We can check them with the Check Knowledge module.""The most valuable features of ODI are the ease of development, you can have a template, and you can onboard transfer very quickly. There's a lot of knowledge modules available that we can use. If you want to connect, for example, a Sibyl, SQL, Oracle, or different products, we don't have to develop them from scratch. They are available, but if it's not, we can go into the marketplace and see if there's a connector there. Having the connector available reduces the amount of hard work needed. We only have to put the inputs and outputs. In some of the products, we use there is already integration available for ODI, which is helpful.""Integration with all systems is easy with Oracle Data Integrator, and it is easy to use. I have not used any other product, but with Oracle Data Integrator, we can easily connect to an ERP system, an SAP system, or a cloud application.""The most valuable feature of ODI is the to use of the whole ETL to create a data lake.""ODI's best features are customization, integration with other versioning tools, and the ability to define new knowledge modules.""It's scalable.""What I found most valuable in Oracle Data Integrator (ODI) is that it integrates well with almost all technologies currently being used in my company.""ODI's most valuable features are it utilizes the database engine and is very lightweight."

More Oracle Data Integrator (ODI) Pros →

Cons
"If you use JDBC Lookup, for example, it generally takes a long time to process data.""Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful.""We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back.""Sometimes, when we have large amounts of data that is very efficiently stored in Hadoop or Kafka, it is not very efficient to run it through StreamSets, due to the lack of efficiency or the resources that StreamSets is using.""The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."

More StreamSets Cons →

"The solution needs to be more connectable to its own services.""Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog.""Data Factory's performance during heavy data processing isn't great.""Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there.""It can improve from the perspective of active logging. It can provide active logging information.""Data Factory's cost is too high.""One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases.""User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."

More Azure Data Factory Cons →

"It has been very good. Just recently, I've faced an issue, but I solved it somehow. While integrating with a file, I faced an issue where I wanted output files, and I had used the text field limited quotations, but at the end of the file, there was a line breakage for the last column. So, we just removed the text field because it was not working correctly for us.""The solution lacks some functions and features.""ODI could improve by being more user-friendly. Informatica, which is also an ETL tool, similar to ODI, but Informatica is very user-friendly, easy to use, and simple to integrate, compared to ODI. ODI has many features, put them all together, and sometimes we get confused about which ones to use, which ones not to use.""The initial setup is complex, especially if you also have to install a console.""The price needs to be lowered. It's too expensive.""An area for improvement in Oracle Data Integrator (ODI) is real-time integration. Currently, my company has a workaround to implement real-time integration, an area on which Oracle must focus more. Real-time integration should be easier in Oracle Data Integrator (ODI). Another area for improvement in Oracle Data Integrator (ODI) is integration with more publishers and subscribers rather than just database integrations.""The interface of ODI could be improved. For example, navigating and finding functions can be difficult. For example, you have to know which step you need to go to look at where your job status is. The logical step is a bit complex compared to other tools. It's much easier to get a graphical view, but with ODI, it's graphical, plus you have to know all the other pieces that fit around it. You have to think about the logical and physical aspects.""An area for improvement would be the lack of SQL compatibility - ODI has no ability to interact with SQL unstructured types and data types."

More Oracle Data Integrator (ODI) Cons →

Pricing and Cost Advice
  • "StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."
  • "It has a CPU core-based licensing, which works for us and is quite good."
  • "There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."
  • "The pricing is good, but not the best. They have some customized plans you can opt for."
  • More StreamSets Pricing and Cost Advice →

  • "I would not say that this product is overly expensive."
  • "The licensing is a pay-as-you-go model, where you pay for what you consume."
  • "Our licensing fees are approximately 15,000 ($150 USD) per month."
  • "The licensing cost is included in the Synapse."
  • "It's not particularly expensive."
  • "Product is priced at the market standard."
  • "There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
  • "I don't see a cost; it appears to be included in general support."
  • More Azure Data Factory Pricing and Cost Advice →

  • "The solution is expensive because of the model they use. The cost is for the license and for support."
  • "ODI comes included when buying the cloud version of the Oracle database license."
  • "There is a standard license to use the solution but there are other costs in addition, such as hardware and operating system."
  • "Per user, it is $900 USD per year, though they will give some discount. However, even a 60% to 70% of discount for each won't help us much. On top of that, there is the perpetual license you must pay at the outset."
  • "I have yet to determine the exact figure for Oracle Data Integrator (ODI) pricing, but it has lower pricing than Informatica."
  • More Oracle Data Integrator (ODI) Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:It is really easy to set up and the interface is easy to use.
    Top Answer:We've seen a couple of cases where it appears to have a memory leak or a similar problem. It grows for a bit and then… more »
    Top Answer:We typically use it to transport our Oracle raw datasets up to Microsoft Azure, and then into SQL databases there.
    Top Answer:AWS Glue and Azure Data factory for ELT best performance cloud services.
    Top Answer:Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability… more »
    Top Answer:Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load… more »
    Top Answer:Oracle Integration Cloud Service has a fairly easy initial setup, and Oracle offers initial support and guidance for… more »
    Top Answer:What is the OLAP that you are using? Hosted in Cloud or on-premise?  The target DB should have its tool to extract… more »
    Top Answer:I know I'm late to the party but here are my comments to this. I would ask what version of ODI are you running, but… more »
    Comparisons
    Also Known As
    ODI
    Learn More
    StreamSets
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    Overview

    StreamSets offers an end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power the modern data ecosystem and hybrid integration.

    Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps.

    With StreamSets, you can deliver the continuous data that drives the connected enterprise.

    Azure Data Factory is a managed cloud service built for extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects. This is a digital integration tool as well as a cloud data warehouse that allows users to create, schedule, and manage data in the cloud or on premises. The use cases of the product include data engineering, operational data integration, analytics, ingesting data into data warehouses, and migrating on-premise SQL Server Integration Services (SSIS) packages to Azure.

    The tool allows users to create data-driven workflows for initiating data movement and data transformation at scale. Data can be ingested from disparate data stores via pipelines. Companies can utilize this product to build complex ETL processes for transforming data visually with data flows. Azure Data Factory also offers services such as Azure HDInsight Hadoop, Azure Databricks, Azure Synapse Analytics, and Azure SQL Database. These services are created to facilitate data management and control for organizations, providing them with better visibility of their data for improved decision-making.

    Azure Data Factory allows companies to create schedules for moving and transforming data into their pipelines. This can be done hourly, daily, weekly, or according to the specific needs of the organization. The steps through which the data-driven workflows work in Azure Data Factory are the following:

    1. Connecting to required sources and collecting data. After connecting to the various sources where data is stored, the pipelines move the data to a centralized location for further processing.

    2. Transforming and enriching the data. Once the data is moved to a centralized data store in the cloud, the pipelines transform it through services like HDInsight Hadoop, Azure Data Lake Analytics, Spark, and Machine Learning.

    3. Delivering the transformed data to on-premise sources or keeping it in cloud storage sources for usage by different tools and applications.

    Azure Data Factory Concepts

    The solution consists of a series of interconnected systems that provide data integration and related services for users. The following concepts create the end product for users:

    • Pipelines: A pipeline refers to the logical grouping of activities that performs a unit of work which together perform a task.

    • Mapping data flows: Azure Data Factory lets its users create and manage graphs of data transformation logic for transforming any-sized data. The logic is executed on a Spark cluster, which does not have to be managed or maintained personally by the user.

    • Linked services: The linked services in the tool define the connection to the data source. There are various services used for two main purposes - to represent a data store that the solution supports and to represent a compute resource that can host the execution of an activity.

    • Integration runtime: The integration runtime in the tool provides the bridge between the activity and linked services needed for it.

    • Triggers: There are various types of triggers in the solution, created for different types of events. They determine when a pipeline execution should be initiated.

    • Pipeline runs: Pipeline runs are instantiated by passing the arguments to the parameters that are defined in pipelines, executing the pipelines' work.

    • Control flow: Control flow in Azure Data Factory is an orchestration of pipeline activities.

    • Connect and collect: This serves as the first step of the services that this tool offers. It connects all the required sources of data and processing in order to prepare the data for moving it to a centralized location for further processing. The step eliminates the need for companies to integrate expensive custom solutions for data movement. Through Copy Activity, Azure Blob storage, and Azure HDInsight Hadoop cluster, users can quickly initiate the first step of organizing their data.

    • Transform and enrich: The collected data can be processed or transformed by using the mapping data flows of the product. Data transformation graphs can be executed on Spark without the need to understand its clusters or how programming works.

    • CI/CD and publish: Through Azure DevOps and GitHub clients, the tool can receive full support for CI/CD for their data pipelines, which allows for the development and delivery of ETL processes before publishing the finished product.

    • Monitor: When users have successfully built and deployed their data integration pipelines, the service offers them the option to monitor the scheduled activities and pipelines. This is done through Azure Monitor, API, PowerShell, and health panels on the Azure portal.

    Azure Data Factory Benefits

    Azure Data Factory offers clients many several benefits. Some of these include:

    • An easy-to-use platform which is suitable for both beginner and expert users, as it offers code-free processes and built-in support.

    • Pay-as-you-go option for clients to pay only for the services that they are using.

    • Powerful tool with more than 90 built-in connectors, which allow companies to ingest on-premise and software as service (SaaS) data quickly.

    • Provided autonomous ETL, which unlocks operational efficiencies and citizen integrators.

    • The tool is designed to handle large volumes of data and provide users with better scalability and performance than classic ETL systems.

    • Azure Data Factory allows users to easily migrate ETL workloads to the solution’s cloud.

    • The solution offers great security for its users, as it provides the option for assigning specific permissions and roles within the organization.

    • Azure Data Factory is highly automated, which allows users to orchestrate their data more efficiently.

    • The platform is a combination of GUI and scripting-based interfaces, which gives users more freedom over data management.

    • The tool provides organizations with the option to rely on Microsoft to fully manage the process. This eliminates the potential need of hiring a third-party expert.

    Reviews from Real Users

    According to Dan M., a Chief Strategist & CTO at a consultancy, Azure Data Factory is secure and reasonably priced.

    A Senior Manager at a tech services company evaluates the tool as reasonably priced, scales well, good performance.

    Oracle Data Integrator (ODI) is a data integration software solution that provides a unified infrastructure to streamline data and application integration projects. It uses a powerful design approach to data integration, which separates the declarative rules from the implementation details. The solution is based on a unique ELT (Extract Load Transform) architecture, eliminating the need for a standalone ETL server and proprietary engine. 

    Oracle Data Integrator Features

    ODI has many valuable key features. Some of the most useful ones include:

    • Automatic documentation generation
    • Visualization of data flows in the interfaces
    • Customization of generated code
    • Automatic reverse-engineering of existing applications or databases
    • Graphical development and maintenance of transformation and integration interfaces
    • Robust data integrity control features, assuring the consistency and correctness of data
    • Powerful core differentiators
    • Heterogeneous ELT, declarative design and knowledge modules
    • Flexibility and modularity
    • Oracle Data Integrator repository
    • Topology navigator
    • Operator Navigator
    • Security Navigator
    • Integrator Console
    • ODI domains

    Oracle Data Integrator Benefits

    There are many benefits to implementing ODI. Some of the biggest advantages the solution offers include:

    • Efficient architecture: Oracle Data Integrator has a simple architecture that utilizes the source and target servers to perform complex transformations, making it an efficient solution.
    • Supports all platforms: ODI gives you platform independence by supporting all platforms, hardware, and OSes with the same software.
    • Cost-effective: Oracle Data Integrator reduces costs associated with initial hardware and software acquisition, and also decreases maintenance costs because it eliminates the need for an ETL Server and an ETL engine.
    • Automatic detection of faulty data: By using ODI, faulty data is recycled before insertion in the target application, providing you with a data quality firewall.
    • Easy development and maintenance: With a low learning curve, Oracle Data Integrator increases developer productivity while facilitating ongoing maintenance. 
    • Active integration: ODI includes all styles of data integration: data-based, event-based and service-based.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot users currently using the Oracle Data Integrator (ODI) solution.

    Brian D., Business Process and Strategy Specialist Advisor at NTTData, says, “The Knowledge Module (KM) is my favorite feature of ODI. This is where I learned how to use variables to make jobs dynamic. I took that knowledge and created a KM that would go into iTunes and pull the sales of eBooks. Making something that is reusable, like a KM, is important to not only reduce build time but also maintenance in the future.”

    Ashok S., Applications Support Manager at a marketing services firm, mentions, "The most valuable features of ODI are the ease of development, you can have a template, and you can onboard transfer very quickly. There's a lot of knowledge modules available that we can use. If you want to connect, for example, a Sibyl, SQL, Oracle, or different products, we don't have to develop them from scratch. They are available, but if it's not, we can go into the marketplace and see if there's a connector there. Having the connector available reduces the amount of hard work needed. We only have to put the inputs and outputs. In some of the products, we use there is already integration available for ODI, which is helpful."

    Offer
    Learn more about StreamSets
    Learn more about Azure Data Factory
    Learn more about Oracle Data Integrator (ODI)
    Sample Customers
    Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
    Milliman, Pier 1 Imports, Rockwell Automation, Ziosk, Real Madrid
    Griffith University, Kansas City Power & Light, Keste, Raymond James Financial, Valdosta State University
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm17%
    Computer Software Company14%
    Manufacturing Company7%
    Insurance Company7%
    REVIEWERS
    Computer Software Company35%
    Manufacturing Company9%
    Non Profit9%
    Insurance Company6%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm11%
    Comms Service Provider8%
    Energy/Utilities Company7%
    REVIEWERS
    Financial Services Firm28%
    Computer Software Company10%
    University7%
    Hospitality Company7%
    VISITORS READING REVIEWS
    Computer Software Company23%
    Financial Services Firm13%
    Comms Service Provider11%
    Government7%
    Company Size
    REVIEWERS
    Small Business22%
    Midsize Enterprise33%
    Large Enterprise44%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise74%
    REVIEWERS
    Small Business27%
    Midsize Enterprise21%
    Large Enterprise51%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise13%
    Large Enterprise70%
    REVIEWERS
    Small Business32%
    Midsize Enterprise14%
    Large Enterprise54%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise73%
    Buyer's Guide
    Azure Data Factory vs. Oracle Data Integrator (ODI)
    November 2022
    Find out what your peers are saying about Azure Data Factory vs. Oracle Data Integrator (ODI) and other solutions. Updated: November 2022.
    656,862 professionals have used our research since 2012.

    Azure Data Factory is ranked 1st in Data Integration Tools with 41 reviews while Oracle Data Integrator (ODI) is ranked 4th in Data Integration Tools with 12 reviews. Azure Data Factory is rated 8.0, while Oracle Data Integrator (ODI) is rated 8.2. The top reviewer of Azure Data Factory writes "There's the good, the bad and the ugly....unfortunately lots of ugly". On the other hand, the top reviewer of Oracle Data Integrator (ODI) writes "We can make all the EPM tools work together as one and we can create a puzzle that will increase the performance and capability of all EPM tools". Azure Data Factory is most compared with Informatica PowerCenter, Microsoft Azure Synapse Analytics, Informatica Cloud Data Integration, Alteryx Designer and Denodo, whereas Oracle Data Integrator (ODI) is most compared with Oracle Integration Cloud Service, SSIS, Informatica PowerCenter, Oracle GoldenGate and Talend Open Studio. See our Azure Data Factory vs. Oracle Data Integrator (ODI) report.

    See our list of best Data Integration Tools 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.