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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Apache Airflow

    Score8.7 out of 10
    N/AApache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL.N/A

    IBM StreamSets

    Score7.9 out of 10
    N/AIBM® StreamSets enables users to create and manage smart streaming data pipelines through a graphical interface, facilitating data integration across hybrid and multicloud environments. IBM StreamSets can support millions of data pipelines for analytics, applications and hybrid integration.N/A
    Pricing
    Apache AirflowIBM StreamSets
    Editions & Modules
    No answers on this topic
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    Offerings
    Pricing Offerings
    Apache AirflowIBM StreamSets
    Free Trial
    NoNo
    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 AirflowIBM StreamSets
    Considered Both Products
    Apache
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    12 Answers
    100%
    Would buy again
    9 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    12 Answers
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    12 Answers
    100%
    Happy with the feature set
    9 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    9 Answers
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    12 Answers
    100%
    Implementation went as expected
    8 Answers
    Features
    Apache AirflowIBM StreamSets
    Workload Automation
    Comparison of Workload Automation features of Apache Airflow and IBM StreamSets
    Feature
    Apache Airflow
    8.5
    12 Ratings
    3% above category average
    IBM StreamSets
    -
    Ratings
    Multi-platform scheduling9.112 Ratings00 Ratings
    Central monitoring8.712 Ratings00 Ratings
    Logging8.312 Ratings00 Ratings
    Alerts and notifications9.212 Ratings00 Ratings
    Analysis and visualization6.112 Ratings00 Ratings
    Application integration9.412 Ratings00 Ratings
    Best Alternatives
    Apache AirflowIBM StreamSets
    Small Businesses
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    Medium-sized Companies
    JAMS
    Score7.9 out of 10
    Apache Spark
    Score8.8 out of 10
    Enterprises
    Redwood RunMyJobs
    Score9.7 out of 10
    Apache Spark
    Score8.8 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Apache AirflowIBM StreamSets
    Likelihood to Recommend
    8.9
    (12 ratings)
    7.3
    (9 ratings)
    Usability
    7.8
    (3 ratings)
    7.7
    (8 ratings)
    User Testimonials
    Apache AirflowIBM StreamSets
    Likelihood to Recommend
    Apache
    Airflow is well-suited for data engineering pipelines, creating scheduled workflows, and working with various data sources. You can implement almost any kind of DAG for any use case using the different operators or enforce your operator using the Python operator with ease. The MLOps feature of Airflow can be enhanced to match MLFlow-like features, making Airflow the go-to solution for all workloads, from data science to data engineering.
    Incentivized
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    IBM
    IBM StreamSets excels in real-time logistics data ingestion and transformation across hybrid systems. It’s less ideal for lightweight ETL tasks or static datasets where simpler tools can achieve similar results with less overhead and complexity.
    Incentivized
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    Pros
    Apache
    • Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
    • Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
    • Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.
    Incentivized
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    IBM
    • It helps streaming huge data that we have in our Teradata database to various reporting applications that runs on cloud seamlessly.
    • We also use IBM StreamSets to power few BI dashboards that our product managers use on regular basis to showcase various data with clients.
    • I think the data quality is way better compared to Informatica tool.
    Incentivized
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    Cons
    Apache
    • UI/Dashboard can be updated to be customisable, and jobs summary in groups of errors/failures/success, instead of each job, so that a summary of errors can be used as a starting point for reviewing them.
    • Navigation - It's a bit dated. Could do with more modern web navigation UX. i.e. sidebars navigation instead of browser back/forward.
    • Again core functional reorg in terms of UX. Navigation can be improved for core functions as well, instead of discovery.
    Incentivized
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    IBM
    • The error messages I feel aren t always very descriptive so troubleshooting can take longer
    • Maybe more customisation options for scheduling can be done, rest it works pretty well.
    Incentivized
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    Usability
    Apache
    For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.
    Incentivized
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    IBM
    The StreamSets platform is very easy to use and the interface is extremely intuitive. The drag-and-drop, low-code design makes it accessible for teams with varying technical skills, allowing us to quickly connect sources, define transformations, and deploy pipelines without heavy coding. StreamSets allows us to get started quickly and not have to worry about our pipelines breaking once they're built.
    Incentivized
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    Alternatives Considered
    Apache
    Multiple DAGs can be orchestrated simultaneously at varying times, and runs can be reproduced or replicated with relative ease. Overall, utilizing Apache Airflow is easier to use than other solutions now on the market. It is simple to integrate in Apache Airflow, and the workflow can be monitored and scheduling can be done quickly using Apache Airflow. We advocate using this tool for automating the data pipeline or process.
    Incentivized
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    IBM
    First advantage is that this software is particularly new and it keeps updating according to the needs of the user. Other advantage is the it organises and produces conclusions on the basis of data without leaving any relevant information. Other softwares lack in data summarising and readability of the charts and sheets they produce.
    Incentivized
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    Return on Investment
    Apache
    • Impact Depends on number of workflows. If there are lot of workflows then it has a better usecase as the implementation is justified as it needs resources , dedicated VMs, Database that has a cost
    • Donot use it if you have very less usecases
    Incentivized
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    IBM
    • time saving for automatic collection and integration of data
    • time saving thanks to live monitoring and reaction
    • time saving for standardization of data
    Incentivized
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