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Spring Cloud Data Flow vs StreamSets comparison

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Executive Summary

We performed a comparison between Spring Cloud Data Flow and StreamSets 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 Spring Cloud Data Flow vs. StreamSets report (Updated: August 2022).
633,572 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
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure.""The most valuable feature is real-time streaming."

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"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 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.""It is really easy to set up and the interface is easy to use.""In StreamSets, everything is in one place.""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.""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."

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Cons
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation.""Some of the features, like the monitoring tools, are not very mature and are still evolving."

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"We've seen a couple of cases where it appears to have a memory leak or a similar problem.""If you use JDBC Lookup, for example, it generally takes a long time to process data.""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.""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.""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.""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."

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Pricing and Cost Advice
  • "This is an open-source product that can be used free of charge."
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  • "We are running the community version right now, which can be used free of charge."
  • "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 →

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    Questions from the Community
    Top Answer:The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation. The documentation on offer is not that… more »
    Top Answer:Mostly the use cases are related to building a data pipeline. There are multiple microservices that are working in the Spring Cloud Data Flow infrastructure, and we are building a data pipeline… more »
    Top Answer:While the deployment is on-premises, the data center is not on-premises. It's in a different geographical location, however, it was the client's own data center. We deployed there, and we installed… more »
    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 we'd have to restart the container, maybe once a month when it gets high.
    Top Answer:We typically use it to transport our Oracle raw datasets up to Microsoft Azure, and then into SQL databases there.
    Ranking
    17th
    Views
    8,438
    Comparisons
    6,450
    Reviews
    2
    Average Words per Review
    1,101
    Rating
    8.0
    11th
    Views
    5,397
    Comparisons
    3,634
    Reviews
    5
    Average Words per Review
    1,947
    Rating
    8.2
    Comparisons
    Learn More
    StreamSets
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    Overview

    Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
    Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

    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.

    Offer
    Learn more about Spring Cloud Data Flow
    Learn more about StreamSets
    Sample Customers
    Information Not Available
    Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company21%
    Financial Services Firm21%
    Comms Service Provider8%
    Retailer6%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company15%
    Insurance Company8%
    Government7%
    Company Size
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise74%
    REVIEWERS
    Small Business14%
    Midsize Enterprise29%
    Large Enterprise57%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise74%
    Buyer's Guide
    Spring Cloud Data Flow vs. StreamSets
    August 2022
    Find out what your peers are saying about Spring Cloud Data Flow vs. StreamSets and other solutions. Updated: August 2022.
    633,572 professionals have used our research since 2012.

    Spring Cloud Data Flow is ranked 17th in Data Integration Tools with 2 reviews while StreamSets is ranked 11th in Data Integration Tools with 6 reviews. Spring Cloud Data Flow is rated 8.0, while StreamSets is rated 8.4. The top reviewer of Spring Cloud Data Flow writes "Good logging mechanisms, a strong infrastructure and pretty scalable". On the other hand, the top reviewer of StreamSets writes "Integrates with different enterprise systems and enables us to easily build data pipelines without knowing how to code". Spring Cloud Data Flow is most compared with Apache Flink, Amazon Kinesis, Apache Spark Streaming, Cloudera DataFlow and Databricks, whereas StreamSets is most compared with Informatica PowerCenter, SSIS, Oracle GoldenGate, Azure Data Factory and Talend Open Studio. See our Spring Cloud Data Flow vs. StreamSets 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.