We performed a comparison between SnapLogic and StreamSets based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."SnapLogic is a great platform for establishing integrations among various systems or patterns by using any kind of interface. If something is not supported by predefined snaps – snaps are connectors in SnapLogic – you can create them (custom snaps) or write a script."
"An important tool for building prototypes and MVPs than can seamlessly turn into production jobs"
"SnapLogic is an IPA tool that leverages a low code environment to connect to multiple sources, extract data, and store it in Azure data lake."
"What I found most valuable in SnapLogic is the ETL feature, particularly the Transform Snap Pack, for example, any kind of reading or writing on Transform Snaps. Other than that, all the third-party connectivity tools such as the SAP Snap Pack, Salesforce Snap Pack, Workday Snap Pack, even the ServiceNow Snap Pack, I find all those are pretty useful in SnapLogic."
"The product is easy to use and has many connectivity options."
"It's more developer-friendly, and development can be done at a faster phase."
"The initial setup is very straightforward."
"The solutions ability to connect "snaps" or components to the graphic user interface is very intuitive, prevents errors, and makes implementations easy."
"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."
"One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill."
"It's very easy to integrate. It integrates with Snowflake, AWS, Google Cloud, and Azure. It's very helpful for DevOps, DataOps, and data engineering because it provides a comprehensive solution, and it's not complicated."
"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."
"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."
"The best feature that I really like is the integration."
"They should expand in terms of features for SaaS-based market requirements in different sectors."
"The dashboards regarding scheduled tasks need further improvement."
"One of the areas for improvement in SnapLogic is that the connectors for some of the applications should be more available in terms of testing in the dev environment. Another area for improvement is that the logging should be standardized, for example, the integration with an ELK stack should be required out-of-the-box, so you can ship the log and have it in the ELK stack. There should be integration with ELK stack for the log shipping."
"One area for improvement in SnapLogic is the transparency in the flow of data. It needs to have more transparency. Right now, users only have a preview option at the end of any job flow, so at the end of any Snap Pack, there is a data preview option that lets you review the data and see how it's moving. What would make the solution better is more debugging and more access to change data from the preview panel or more functionality in terms of the preview option."
"There is room for improvement with APM management and how task execution looks."
"SnapLogic sits somewhere in the middle. It doesn’t offer enough easy canned integrations for its users like some of the easier to use integration apps."
"What could be improved in SnapLogic is that it was not capable in terms of processing a large number of datasets, but at that point, SnapLogic was evolving. It didn't give a lot of Snaps. I heard recently there are a lot of Snaps getting added and the solution was being enhanced, particularly to connect different data sources. When I was working with SnapLogic six months to one year back, I faced the issue of it not being capable of handling a huge volume of datasets or didn't have much of Snaps, and that was the drawback. If there is any large number of data sets, that's based on or depends on your configuration. If it is a huge volume of data, other traditional ETL tools such as Informatica and Talend can process millions and billions of records, while in SnapLogic, the Snaplex fails or it returns an error in terms of processing that huge volume of data. Informatica, Talend, or any other ETL tool can run for hours in terms of jobs, while SnapLogic jobs fail when the threshold is reached. SnapLogic isn't able to withstand processing, but I don't know if that's still an issue at present, because the solution is getting enhanced and it's been more than six months to one year since I last worked with SnapLogic. There are now a lot of Snaps getting added to the solution, and if it can overcome the limitations I mentioned, SnapLogic could be the go-to tool because currently, it's not being used as much in organizations. It's being used comparatively less compared to other retail tools."
"The support is the most important improvement they could make."
"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."
"The data collector in StreamSets has to be designed properly. For example, a simple database configuration with MySQL DB requires the MySQL Connector to be installed."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"Using ETL pipelines is a bit complicated and requires some technical aid."
"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."
SnapLogic doesn't meet the minimum requirements to be ranked in Data Integration with 13 reviews while StreamSets is ranked 8th in Data Integration with 21 reviews. SnapLogic is rated 8.2, while StreamSets is rated 8.4. The top reviewer of SnapLogic writes "Automates manual activities and has helpful documentation that allows users to self-study". 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". SnapLogic is most compared with Azure Data Factory, IBM InfoSphere DataStage, AWS Glue, Informatica Cloud Data Integration and Workato, whereas StreamSets is most compared with Azure Data Factory, Fivetran, Informatica PowerCenter, SSIS and webMethods.io Integration. See our SnapLogic vs. StreamSets report.
See our list of best Data Integration vendors and best Cloud Data Integration vendors.
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