Azure Data Factory vs SSIS comparison

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40,005 views|32,089 comparisons
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Comparison Buyer's Guide
Executive Summary

We performed a comparison between Azure Data Factory and SSIS 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. SSIS 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
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy.""Data Factory's most valuable feature is Copy Activity.""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.""Its integrability with the rest of the activities on Azure is most valuable.""Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure.""The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable.""We haven't had any issues connecting it to other products.""The most valuable feature is the copy activity."

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"It is easy to set up the solution.""Overall, it's a good product.""The performance is good.""SSIS provides you with lookup and transformation functions, and you have the flexibility to write your own custom code.""The most important features are it works well and provides self-service BI.""The performance and stability are good.""SSIS integrates well with SQL servers and Microsoft products.""It is easy to set up. The deployment is also very quick."

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Cons
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful.""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.""Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail.""There's space for improvement in the development process of the data pipelines.""Azure Data Factory can improve by having support in the drivers for change data capture.""It would be better if it had machine learning capabilities.""There are limitations when processing more than one GD file.""A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

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"It would be nice if you could run SSIS on other environments besides Windows.""We purchase an add on called task factory primarily to allow bulk delete, update and upsert capability. I'd like to see this be part of the standard package.""At one point, we did have to purchase an add-on.""We'd like them to develop data exploration more.""You have to write push down join & lookup SQL to the database yourself via stored procedures or use of the SQL Task to get very high performance. That said, this is a common complaint for nearly all ETL tools on the market and those that offer an alternative such as Informatica offer them at a very expensive add-on price.""SSIS sometimes hangs, and there are some problems with servers going down after they've been patched.""SSIS is cumbersome despite its drag-and-drop functionality. For example, let's say I have 50 tables with 30 columns. You need to set a data type for each column and table. That's around 1,500 objects. It gets unwieldy adding validation for every column. Previously, SSIS automatically detected the data type, but I think they removed this feature. It would automatically detect if it's an integer, primary key, or foreign key column. You had fewer problems building the model.""Microsoft's technical support has decreased in quality over the last few years, becoming less responsive and tending to pass problems on instead of solving them."

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Pricing and Cost Advice
  • "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."
  • "Pricing appears to be reasonable in my opinion."
  • More Azure Data Factory Pricing and Cost Advice →

  • "Based on my experience and understanding, Talend comes out to be a little bit expensive as compared to SSIS. The average cost of having Talend with Talend Management Console is around 72K per region, which is much higher than SSIS. SSIS works very well with Microsoft technologies, and if you have Microsoft technologies, it is not really expensive to have SSIS. If you have SQL Server, SSIS is free."
  • "We have an enterprise license for this solution."
  • "It comes bundled with other solutions, which makes it difficult to get the price on the specific product."
  • "All of my clients have this product included as part of their Microsoft license."
  • "SSIS is a cheaper option compared to the cost of other ETL tools."
  • "Our license with SSIS is annual."
  • "t's incredibly cost effective, easy to learn the basics quickly (although like all ETL tools requires the traditional learning curve to get good at) and has an immense user base."
  • "SSIS' licensing is a little high, but it gives good value for money."
  • More SSIS Pricing and Cost Advice →

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    Questions from the Community
    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 and reliability I am looking for, good scalability, and is easy to set up and… more »
    Top Answer:Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power… more »
    Top Answer:SSIS PowerPack is a group of drag and drop connectors for Microsoft SQL Server Integration Services, commonly called SSIS. The collection helps organizations boost productivity with code-free… 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 data.
    Ranking
    1st
    Views
    40,005
    Comparisons
    32,089
    Reviews
    48
    Average Words per Review
    502
    Rating
    8.0
    3rd
    Views
    27,553
    Comparisons
    21,430
    Reviews
    35
    Average Words per Review
    450
    Rating
    7.7
    Comparisons
    Also Known As
    SQL Server Integration Services
    Learn More
    Overview

    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.

    SQL Server Integration Services (SSIS) is a Microsoft platform designed to build enterprise-level data integration and data transformation solutions. Users now have the ability to solve intricate business queries by downloading and copying files, cleansing and mining data, loading data warehouses, and managing SQL Server objects and data through Integration Services. SSIS is a component of the Microsoft SQL Server data software used for many data migration tasks.

    SSIS loads data into one or more destinations by extracting and transforming data from a wide variety of sources such as XML data files, flat files, and relational data sources.

    Integration Services include:

    • An SSIS catalog database to manage, store, and run packages.
    • An ample set of built-in transformations and tasks.
    • Graphical tools for building packages.

    Create packages programmatically and code custom tasks through programming the extensive Integration Services. With graphical Integration Services, you can create solutions without writing any code.

    Benefits of SSIS

    There are many benefits of SSIS, such as:

    • Solve complex business problems - encrypt files with SSIS and send them to various network locations.

    • Migration of DTS packages to SSIS - users can migrate DTS packages to SSIS while choosing to run DTS packages using DTS runtime or incorporate DTS packages into SSIS.

    • Development of ETL processes - Microsoft’s SSIS packages provide the ability to extract, transform, and load data into data warehouses. This service takes data from various sources, like CSV files, XML files, flat files, and relational data sources and transforms and loads them to their destinations.

    • Data migration from other databases - with Integrations Services, users can transform data to make sure it complies with the rules of the database they are migrating to.

    • Managing and automating SQL server objects - SSIS packages can manage and automate SQL server objects which will help save you time and resources.

    Reviews from Real Users

    The SSIS platform stands out among its competitors for a variety of reasons. Two major ones are its debugging capabilities during data flow execution and its easy connectivity with other Microsoft tools.

    Muhammad J., a senior manager software developer at Techlogix, notes, "The debugging capabilities are great, particularly during data flow execution. You can look into the data and see what's going on in the pipeline."

    Ismail L., a data engineer at a tech service company, writes, "The most valuable thing is that it is easy to connect with Microsoft tools. In Europe, particularly in France, a lot of companies use Excel, SQL Server, and other Microsoft tools, and it is easier to connect SSIS with Microsoft tools than other products."

    Offer
    Learn more about Azure Data Factory
    Learn more about SSIS
    Sample Customers
    Milliman, Pier 1 Imports, Rockwell Automation, Ziosk, Real Madrid
    PKP Energetyka, UniCredit Bank, Mostar, waldwasser, Ashok leyland, Florida Atlantic University, Stadt Frankfurt am Main
    Top Industries
    REVIEWERS
    Computer Software Company35%
    Insurance Company8%
    Manufacturing Company8%
    Financial Services Firm8%
    VISITORS READING REVIEWS
    Computer Software Company17%
    Financial Services Firm12%
    Government7%
    Energy/Utilities Company6%
    REVIEWERS
    Financial Services Firm21%
    Manufacturing Company11%
    Insurance Company9%
    Government9%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company15%
    Insurance Company7%
    Government7%
    Company Size
    REVIEWERS
    Small Business28%
    Midsize Enterprise20%
    Large Enterprise53%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise13%
    Large Enterprise70%
    REVIEWERS
    Small Business29%
    Midsize Enterprise20%
    Large Enterprise52%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    Buyer's Guide
    Azure Data Factory vs. SSIS
    March 2023
    Find out what your peers are saying about Azure Data Factory vs. SSIS and other solutions. Updated: March 2023.
    688,083 professionals have used our research since 2012.

    Azure Data Factory is ranked 1st in Data Integration Tools with 47 reviews while SSIS is ranked 3rd in Data Integration Tools with 35 reviews. Azure Data Factory is rated 8.0, while SSIS is rated 7.6. The top reviewer of Azure Data Factory writes "The good, the bad and the lots of ugly". On the other hand, the top reviewer of SSIS writes "SSIS 2016 - The good, the bad, and the ugly". Azure Data Factory is most compared with Informatica PowerCenter, Microsoft Azure Synapse Analytics, Informatica Cloud Data Integration, Alteryx Designer and Oracle Data Integrator (ODI), whereas SSIS is most compared with Informatica PowerCenter, Talend Open Studio, Oracle Data Integrator (ODI), AWS Glue and SAP Data Services. See our Azure Data Factory vs. SSIS 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.