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."Support is helpful."
"The installation is easy."
"Scalable and stable solution for migrating databases to AWS, with valuable features such as parallel full load and continuous data replication."
"What I like about AWS Database Migration Service is that it's a good product that allows you to migrate terabytes of data. My team was able to migrate almost 16TB of data using AWS Database Migration Service. The solution works fine for my use case."
"I am very impressed by the scalability of AWS Database Migration Service."
"AWS Database Migration Service is good for smaller workloads and provides compatibility."
"The most valuable features of the AWS Database Migration Service are the ease of migration, beneficial storage system, security, and simple instance creation. Additionally, the cloud that is provided is more complete than other solutions."
"The most valuable feature of AWS Database Migration Service is it catches all the history changes, such as inset, observe, and delete. It tracks everything."
"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."
"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"
"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."
"In StreamSets, everything is in one place."
"The best feature that I really like is the integration."
"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 entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."
"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 server has limits on how many can connect to the database."
"It would be helpful if the bandwidth could be independent of the network or if we could have a dedicated bandwidth for this product."
"The initial setup can be difficult for beginners in AWS Database Migration Service. You will need the training to complete it."
"Database Migration Service could be more integrated. I think that it makes sense to add integration to these functions. For example, AWS Glue has a feature called Orchestrator to create data flows, and that's more straightforward."
"There are a set of complexities and challenges when a user wants to integrate AWS products with Microsoft products."
"This solution is compatible with only AWS."
"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."
"One area that AWS DMS can improve on is its conversion of data types. For example, in Oracle, you have a data type called RAW, but in PostgreSQL there is no such thing. Thus, AWS DMS doesn't know what type I want to use when migrating from Oracle to PostgreSQL, and when performing the migration, AWS DMS changed the RAW data type to the byte data type, which isn't what I wanted."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."
"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."
"Visualization and monitoring need to be improved and refined."
"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."
"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."
"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."
"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."
More AWS Database Migration Service Pricing and Cost Advice →
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.
See our list of best Cloud Data Integration vendors.
We monitor all Cloud Data Integration 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.
