AWS Database Migration Service Reviews

We use this solution to get our data into Lakehouse with the CDC. So, Change Data Capture is also very important for us. AWS Database Migration Service has an inbuilt functionality for capturing change data.

The identifier of this solution informs us whether it's an insert operation, an update operation, or a delete operation. Since our main data is OLTP, the status of the order can keep changing; it can easily go from payment to successful and resend to cancel. 

This solution is very good at mini-batch processing if a user needs a latency between thirty seconds and two minutes. 

This solution can offer more tweaks where the latency can be brought down to fifteen seconds. DMS is not the go-to choice when it comes to data streaming, and the major reason is the latency issues because it's file-based and not message-based. So if DMS could offer such a solution, it has the potential to replace Kafka as well. DMS is more of a one-click setup in comparison to Kafka. 

I have been using the solution for two months. 

The solution is very stable. We haven't faced any downtimes yet. I would rate the stability a ten out of ten. 

I would rate the scalability an eight out of ten. We haven't faced any issues with scalability. As it's a background service that is actually replicating our data, DMS does not have an end user; it only turns the data into S3. When we connect to the database, that is when the end user comes into the picture. 

Our previous architecture was based on Debezium and Kafka, where Debezium was being used as a CDC tool. The learning curve for Debezium is much more steep as compared to AWS Database Migration Service. Also, with Debezium, if you are not using any external vendors, then you need to have DMS self-hosted on your own Kubernetes cluster. 

The setup process for this product is quite simple and AWS has provided very good documentation for this purpose. 

We implemented the solution in-house. 

I would rate the pricing a seven out of ten. 

I would rate the solution a seven out of ten. I would definitely recommend this product to others. 

All of our infrastructure is on Amazon, so we used AWS Database Migration Service to perform a database migration from one relational database to another within the AWS cloud. The migration was from an Oracle database to PostgreSQL database, and AWS DMS helped us transfer all the tables and other objects from the one database to the other automatically.

If your infrastructure is already on Amazon, it simply makes the most sense to use a tool officially provided by them as an additional service, rather than having to rely on a third-party solution.

On the other hand, if you have a custom infrastructure and you want to migrate to Amazon, it also makes thing much easier to integrate. The way it works is brilliant, and it's based on similar logic to Oracle's GoldenGate migration tool in that you can migrate everything from data tables to schemas from one database to another. So in most situations where you would need to migrate to Amazon, the best way is by using AWS DMS.

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.

For example, if I wanted to manually transfer the RAW data type in the Oracle database to something else like VARCHAR in the PostgreSQL database, AWS DMS doesn't seem to have this functionality. It would be great if I could change the data type conversions manually instead of automatically.

Another area that has proven difficult for me is the use of AWS Schema Conversion Tool, which is a free, cross-platform app that they offer as part of AWS DMS. I was under the impression that I would first have to use this tool to convert from one database to another, and then use AWS DMS, but when I used it, some of the tasks didn't work correctly. To my surprise, when I skipped using the Schema Conversion Tool and went ahead with the migration with AWS DMS, it automatically transferred everything and it was all correct. So I am not sure what the point of the Schema Conversion Tool is, because the default functionality of AWS DMS seemed to transfer and convert the databases fine without it.

There is also room for improvement from a support perspective. It is sometimes necessary to contact their support team when there is something you don't understand, and when I wrote a support ticket they simply weren't able to help. Yet, when our company contacted the manager of our reseller, they were able to create a meeting room with an Amazon specialist for DMS, and with one call, all our questions were answered. I think their email support team could be much better when compared with their personal support team. 

I have used the solution only once, during a migration which took place over two or three months. 

I only used AWS DMS over the course of about three months, but I could tell that it's not always stable. I think it's fine if you only need to use it for a short time with a one-time migration, but if you intend to use it all the time in, for instance, a staging environment, every day of the month, I wouldn't say that's a good idea. I would only use it for quick migrations.

I have certainly needed the support, especially when I don't understand why something doesn't work. This is often the case when dealing with different types of databases, such as Oracle and PostgreSQL. We also use a lot of other databases, so for us, contacting support is almost inevitable.

Once, when I wrote a support ticket but I didn't get the help I needed, our company wrote to the manager of our reseller who arranged for a meeting with Amazon's personal support. We spoke with an AWS DMS specialist in this meeting and showed him our problem, and with this one call, all our questions were answered.

It's easy to set up when you use Amazon's official documentation, and the first steps are simple. Amazon also has a few practice videos so you can see how it is done.

However, it's not always easy to adapt the documentation according to our own particular applications and databases. For example, if you've never used it before, you will likely need to set aside a minimum of 40 hours for reading and testing.

I implemented it by myself.

The pricing is per hour, though I do not have the exact figures.

If you have specific questions about the service, a personal support team from Amazon is available, but this will bring in additional costs.

Our infrastructure is fully on Amazon, so for us AWS DMS was an obvious choice to perform our migration as it is an additional service that Amazon provides. To those who are thinking of using the same, I would say go ahead and try it. If you come across any problems or have questions, you will most likely need to contact Amazon support, which can give good service, but it's not ideal. The paid support, however, worked well for us.

I would rate AWS Database Migration Service a seven out of ten. 

We're currently moving our whole database from AWS to Oracle. We want to avoid interrupting production systems, so we're using DMS to continuously replicate data from the AWS RDS database to the Oracle database in OCI. Once we're sure all data is consistent, we'll switch over to Oracle and shut down the AWS database.

This should minimize downtime to about 15 minutes, and all our services in AWS then point to the Oracle database.

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.

Currently, we're happy with DMS because it's simple and meets our needs. We're still syncing the data, but once that's done, we'll cut off the AWS database. Compared to Oracle GoldenGate, DMS is definitely easier to use. We haven't encountered any major difficulties.

The cost is a concern. We use DMS because of its simplicity, but the price could definitely be more competitive.

So, in my opinion, some potential areas for improvement are price and possibly supporting Oracle Autonomous Database (ADB) on AWS, as it's a powerful option.

Oracle ADB on AWS would significantly reduce our migration workload. Price and lack of ADB support are the main downsides of DMS for us right now. In fact, about 60% of our monthly AWS costs go towards database services.

We've been using DMS for a while to replicate databases between AWS and Oracle, mainly for backups and test environments.

I would rate the stability a six out of ten. It took us a while to get it running smoothly. It wasn't entirely straightforward. But once it was set up, it was stable. AWS support was helpful during the initial setup.

We haven't encountered any scalability issues so far. We might need to increase the database size later, but it's not a problem. So, I would rate it an eight out of ten.

We actually bumped up our support level for extra coverage, and they've been very helpful. We also have AWS expertise on our team, so there haven't been many difficulties. Overall, the support is good.

The biggest challenge we faced was setting up the IPSec tunnel between the two private networks. It took a while to figure out why they weren't communicating even though the tunnel was up. Luckily, our AWS networking experts managed to fix the routing issue.

Neutral

Currently, we're moving from AWS to Oracle. We're migrating our database, and that's already been taken care of. The issue with AWS has been addressed, and we no longer have any problems with it.

We're new to DMS. We decided to use it about three months ago. That's why we compared DMS with GoldenGate to choose the best option for migrating our database. 

The setup process was simple enough for us because our database is plain and doesn't have many blocks. It's just a typical cloud-based product, like most AWS services.

We use the enterprise and the AWS license, which is a bit expensive. We're consolidating our databases from AWS to Oracle, which we find more cost-effective. So, we're using an autonomous database in Oracle, a feature not offered by AWS.

We've been using AWS for a long time, including for non-Oracle services, and overall, we're very happy. It's much better than GoldenGate, which was a headache for us. 

Overall, I would rate the solution an eight out of ten. 

We were using the solution for the migration and replication of data.

AWS Database Migration Service is good for smaller workloads and provides compatibility.

The solution’s scalability and performance could be improved.

I have been using AWS Database Migration Service since it came up.

I rate the solution a six or seven out of ten for scalability.

The solution’s technical support is good.

Neutral

The solution’s initial setup is easy.

The solution’s pricing is reasonable.

AWS Database Migration Service is a cloud-based solution.

Overall, I rate AWS Database Migration Service a six or seven out of ten.

We have taken that as a Platform as a Service. So, how we are running here, we just migrated whatever database instance in the rack was there to AWS. It was an "as-it-is" migration. 

For data, we tried to use SSIS to transfer the data from the patch to AWS.

The main thing why people are going behind AWS is the cost. 

For example, on the current project, I am working with an insurance company. So the basic thing is they want to accomplish whatever add-on services AWS provides, but they don't want to go all in a single step. Plus, they want to see what the platform is. Then they look step by step. So, it is an incremental adoption kind of thing.

So, we are helping and enhancing our knowledge of that.  

As a solution, the better thing is if more platforms come with direct compatibility, like connecting to different data sources. 

The basic problem I faced the most was while transferring and reading data from Excel. So, one time, I found that all the components I had declared in my scripts were able to take it. 

And after some patching happens, it is not able to support that. Again, we need to update the version of Excel. So, it's not like a plug-in type place where you have done the solution and are confident that it will work. So, this is an area of improvement. 

If we look at Microsoft products, most things look or are plug-and-play. For example, if you are using storage as a service, we need to go for CLI commands. So, those types of stuff that's not as easy as using a Microsoft product, like DDoS, that level of easiness is not there.

In the project I am in, we migrated from SQL Server from RAS to AWS recently.

I would rate the stability a six out of ten. We had some issues with stability.

I would rate the scalability an eight out of ten. It is able to scale up and fulfill requirements. 

The only thing weakness is compatibility. Like, once you program and forget it, it's not that type of thing. 

I faced some problems while patching; new things come up, and sometimes old things don't support, causing a bit of a headache for me. 

We have a big-sized company with various clients. 

Experience with customers and support was good. I got a good response. It was not a delayed response, or it was not that I had to go back to the multiple times for the issue. It was not there. 

Overall, I had a good experience with the support.

The initial setup is simple. Not that much complex.

The pricing is neither high nor low. It is value for money. Moreover, the facilities or the add-ons they give are good.

Overall, I would rate the solution a ten out of ten. 

We looked for Oracle to Aurora conversion migrations. This has two parts, one is called the static table schema migrations, which is a one-time snapshot that we just stamp and load. The other is the CDC replications, or real-time streaming replications, heterogeneously from Oracle to Aurora. 

The solution is simple, which is key. 

AWS Database Migration Service is a huge product, and it takes a great amount of effort to reverse engineer what they do on the backend. It would be better if they did more troubleshooting at the moment. Currently, if something goes wrong, you get a message that says one thing that has nothing to do with the RCA, and it could be misleading. You aren't even sure which part was broken.

There is no connectivity to the source database or the target database. Any of those channels could break, and it becomes very hard to troubleshoot. 

I have been using AWS Database Migration Service since 2016.

The solution is stable. Typically, once the solution is up and running, and you don't change your application code, it will keep working. Even if it does break down, it will automatically recover itself and resumes from where it stopped.

The scalability of AWS Database Migration Service depends on how you define the scale. There are two considerations, one is the initial part of ETL replication. The other is the CDC part, which is after the full image replication is done. 

On the full ETL, you can scale. Meaning, even within the table you can do a parallel on the table level, or within the table level. After, you do a soft positioning for each range you want. A DMS would assign a process link up to that range, this speeds up the skip performance for the ETL.

As for the CDC, there are limitations. CDC is typically a single channel or single thread. That is because CDC is time-based and a binary transactional log. To do a parallel, you would have to do a lot of work. In our scenario, I could not use DMS. I had to use the in-house developer to do a catalog version of CDC.

My experience with Amazon's technical support depends on who I get for support. If I'm lucky to get someone with experience, the issue will be resolved right away. If I get an amateur, they will avoid answering any questions and send me tons of documents. 

Most of my questions are eventually fixed or solved. I would rate service and support a seven out of ten overall.

Neutral

In a typical deployment scenario, I set up the lead-only account on the source database. I make sure that I will not write anything to the source database to compromise the integrity of my source database. I have to write to the target database. Then the solution is ready for use.

Deployment of AWS Database Migration Service requires a POC first, then you make sure that everything is working and run it for about three weeks in an on-premise environment. Then you deploy, either manually or through the telephone, to an AWS production environment.

AWS Database Migration Service is very inexpensive. The cost is considerably lower than Agility or Oracle Golden Gate. We do not have a license for the solution. We are charged based on our usage.

We evaluated Oracle Golden Gate. They offer similar features to AWS Database Migration, but they lacked simplicity. With Golden Gate, you have to set up the entire enterprise software stack which requires so many steps.

We also looked into Aurora for replication, version eight. This product offers parallel replications of CDC, which is very useful. 

AWS Database Migration Service is most useful for a company that is trying to do partial applications for a short amount of time until the entire application is cut over from one place to another.

If you are considering AWS Database Migration as a solution for your organization, I recommend you pay attention to your CDC throughput, it is a single showstopper if you misuse it. I try to use it for our current application's traffic, which is about 30 megabytes per second. DMS would not be able to handle that in-house, it would just keep lagging.

Overall, I would rate AWS Database Migration Service a nine out of ten. It is a very useful product.

The tool is offered as part of AWS stacks. We use it for data migrations from on-premise to AWS stack via PostgreSQL and MySQL. We also use it for the infrastructure configuration to simplify the setup because we are going on RDS. The AWS platform will manage everything. We use it for the simplification of migration. We do not do a lot of study on how exactly to map the database provisioning.

The database migration services allow us to do real-time synchronization of on-premise and database to plan out our releases. We do prod testing to keep the prod data in sync, at the same time, not expose it much. The automation of this synchronization helps us ensure the data is consistent in both AWS and on-prem. Then we can switch over wherever you need it. Parallely, we can do production performance testing and user experience testing without actually writing a lot of code. It comes out of the box. It is one feature that we like a lot.

The other feature I like is schema migration. When we want to upgrade it to MySQL, we can easily upgrade it. It is another stack. We haven’t used database migration. We can use it if we want to move from Oracle to PostgreSQL. It also comes as an out-of-the-box solution. I think these three things are very good. However, we have not used database migration yet because we do not plan to install software yet. The solution has a good feature stack.

The product's performance could be a little bit better. It is good in terms of the data, but it is difficult for the first time. After that, the synchronization is fine. We saw a few failures because of the bandwidth the first time the data got loaded. The performance could be better, but it's only for the first time. We haven't seen any performance-related issues post the initial setup.

I am using the solution right now.

There's no issue with stability. The solution is quite stable. It has to be stable. The only reason we are moving to AWS is to be scalable and perform well.

On-premises scalability is the reason why we are moving into AWS. The product's purpose is to introduce scalability. We would not have picked it up if it was not a ten out of ten. It is expected to be scalable because of how the nodes are getting set up in AWS. We have a medium to large user group. It's for a finance-related project. So there are quite a bit of end users, but not very high. It is targeted at brokers and stock traders.

The technical support is really good. We have partnered with Amazon, and we are part of Amazon's consultation team. There's a service engineer and an overall account manager who take care of the issues. For any automation issues, we can go through them to coordinate. They provide excellent support.

Positive

The initial setup is quite easy. The product has one of the easiest installation setups.

My team, who has expertise in Data Migration Services, did the implementation in a few hours. We have five DevOps team members, two architects, one for data and one for infra and application, and managers. The development team varies. It depends on the system. The rest is the core team. Below the core team, we usually have pilot teams and project teams. We might have a specific development team if a feature enhancement needs to happen, but it is very rare. The core team comprises five DevOps, two architects, and one manager. The maintenance team takes over the maintenance of the on-premise system.

I recommend using the solution if the end goal is AWS. It should not be used for GCPRs and on-premise migration. A lot of the features are applied while the migration tool is in place. The migration tools, like data and schema migration tools, make more sense if the target infrastructure is AWS. You could not use it as a separate tool. If someone is looking at an AWS infrastructure, they have to use the product. However, if they are not looking at AWS and want to use it as a tool, they should not use it. For such cases, they can use the available free and open-source versions of the tools.

Whatever features are there in my system are all available in the solution. Out-of-box migration is also available. I don't see anything that is missing. My system is a real-time system. For me, it's a relational database with straightforward data structures. The volume is much higher if someone has big data processing migration, which may be a problem. For any big data solution, they will have to rework it. The product will not support it. When you have properly structured data, it is not that difficult for AWS to make it. I don't know how effective it will be if you have unstructured data, like big data and unstructured datasets. I have not seen a lot of use cases.

Overall, I rate the product an eight out of ten.

We use this solution to enable us to carry out heavy, data-level migrations across multiple ETL tools.

We particularly like that this solution has the facility to integrate with all ETL tools.

We also like that this solution provides us with high speed velocity, performance, scalability, and throughput for our data migration tasks.

We would like to see some improvement in the performance of large scale procedures, such as when we migrate from Oracle to csSQL.

We have been working with this solution for over five years.

We would rate this solution a 10 out of 10.

We utilize it for mostly heterogeneous migration when you are migrating from one RDBMS platform to another. Obviously, we can use it for homogeneous migrations as well. However, it really comes in handy when you are migrating from the same source platform to the same destination. 

You get a lot of other options for migration, for example, you get different types of backups. You get the option for the native replication being supported by the RDBMS engines. However, when you are migrating from one platform to another platform, which is a heterogeneous case, you need some kind of Golden Gate, CDC, and all that. DMS with heterogeneous migration is, therefore, really very handy, particularly with data transformation and migration use cases.

They're working and improving this service further. They were developing DMS for various use cases, including those specific to Babel Fish. 

It is easy to set up. 

The solution can scale. 

It is very stable. 

Support is helpful.

The performance of data migration could be smoother.

I've been using the solution for almost a year. 

The solution has been stable in my experience. There are no bugs or glitches and it doesn't crash or freeze. 

This is a very scalable product. Expanding out is easy.

The most recent project I did was with a data size that was relatively small. In past, some of my colleagues told me that DMS gets performance issues and that the data migration performance issues they faced happened when the data size was huge. On the other hand, AWS says that for huge data sizes, you need to increase the size of your resources. Therefore, I cannot say with confidence if the issues were the fault of the product or the fault of the size of resources. However, I have heard it lacks performance for large data sets.

We've used the solution for two clients in two different data migrations. 

Technical support has been good. they are helpful and responsive. 

It is very easy to set up the solution. It's not complex at all. 

Users do need to pay for licensing, and the cost is based on the resources used. 

I'd recommend the solution to others.

I'd rate the product eight out of ten. 

I am using AWS Database Migration Service for migrations and relationship migrations.

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.

AWS Database Migration Service can become complex when testing. Other solutions, such as Microsoft Azure makes it easy to do. There are more steps to complete tasks in AWS Database Migration Service than in Microsoft Azure.

I have been using AWS Database Migration Service for approximately five years.

The stability of the AWS Database Migration Service is good.

AWS Database Migration Service is scalable.

I have not contacted support.

I have used Microsoft Azure previously and it is overall easier to use than AWS Database Migration Service. 

My advice to those new to this solution is for them to take notes and know all the documentation needed for the migrations.

I rate AWS Database Migration Service a nine out of ten.