We performed a comparison between AWS Database Migration Service and StreamSets based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."This solution is very good at mini-batch processing."
"The solution is instantaneous. We can launch the service and reduce the end number of manpower."
"Scalable and stable solution for migrating databases to AWS, with valuable features such as parallel full load and continuous data replication."
"The installation is easy."
"As the solution is on the cloud, we don't have to worry about the maintenance of software."
"For our simple requirement of migration, DMS is just a typical AWS RDS with an IPSec tunnel to Oracle. The most valuable features for us are the networking capabilities like VPCs and VPNs."
"The database migration services allow us to do real-time synchronization of on-premise and database to plan out our releases."
"The most valuable feature of the solution is the one I use for report generation. The security risk is very low."
"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."
"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"
"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."
"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."
"The ability to have a good bifurcation rate and fewer mistakes is valuable."
"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."
"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."
"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 live duplication has a delay of two minutes, which can be an issue."
"Migrating from here and pushing the data from on-premise to AWS cloud is a big challenge and a few more services from AWS would be helpful. For example, we are currently using ILDB internet tools which move data from on-premise to the AWS cloud. A few more services would be really helpful for me to move the master data."
"The solution’s scalability and performance could be improved."
"I think that Amazon needs to improve the migration scenarios after analytics"
"There is no connectivity to the source database or the target database."
"The product's performance could be a little bit better."
"If they had some sort of functionality where, at a specific point in time, if I want to start a new job, it should automatically pick up from where it has been left rather than having people worry about the exact job number and the timing."
"This solution can offer more tweaks where the latency can be brought down to fifteen seconds."
"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 documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."
"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."
"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."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."
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AWS Database Migration Service is ranked 2nd in Cloud Data Integration with 27 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. AWS Database Migration Service is rated 7.8, while StreamSets is rated 8.4. The top reviewer of AWS Database Migration Service writes "A cloud solution for live replication but has stability issues". On the other hand, the top reviewer of StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". AWS Database Migration Service is most compared with AWS Glue, Oracle GoldenGate, Qlik Replicate, Fivetran and Confluent, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and webMethods Integration Server. See our AWS Database Migration Service vs. StreamSets report.
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