Table of contents
Minimal Downtime
AWS Database Migration Service ensures minimal downtime during the database migration process, making it ideal for applications that require continuous availability.
Supports Multiple Database Engines
It supports migration of data between a wide variety of database engines including Oracle, Microsoft SQL Server, MySQL, MariaDB, PostgreSQL, and more.
Cost-Effective
With a pay-as-you-go pricing model, users only pay for the compute resources used during the migration process, making it a cost-effective solution.
Managed Service
As a fully managed service, it reduces the administrative overhead associated with database migrations, including hardware provisioning, software patching, and monitoring.
Continuous Data Replication
It supports continuous data replication with high availability, allowing for nearly real-time data synchronization between the source and target databases.
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Overall, AWS Database Migration Service is a reliable and efficient tool for migrating databases to the cloud, especially within the AWS ecosystem. Its flexibility, along with support for various database scenarios, makes it a worthwhile option for organizations looking to modernize their data infrastructure.
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The major infrastructure providers offer CDC products that work within their ecosystem. Tools like AWS DMS, GCP Datastream, and Azure Data Factory can be configured to stream changes from Postgres to other infrastructure. - Source: dev.to / over 1 year ago
The second big drawback is speed. There will be more latency in this scenario. How much latency depends upon the environment. If there is RDBMS in the source, AWS Data Migration Service will at worst take around 60 seconds to replicate. That cost needs to be accounted for. Secondarily, many triggering events are leveraged which happen fairly quickly but they do add up. - Source: dev.to / about 2 years ago
Amazon Database Migration Service might initially seem like a perfect tool for a smooth and straightforward migration to RDS. However, our overall experience using it turned out to be closer to an open beta product rather than a production-ready tool for dealing with a critical asset of any company, which is its data. Nevertheless, with the extra adjustments, we made it work for almost all our needs. - Source: dev.to / about 2 years ago
Does AWS DMS make sense here? Doesn't the aforementioned "snapshot+restore to provisioned and upgrade" method suffice? I wanted to get some opinions before deep diving into the docs for yet another AWS service. Source: almost 3 years ago
One easy solution is AWS DMS. I use it for on-going CDC replication with custom transforms, but you can use it for simple replication too. Source: about 3 years ago
Https://aws.amazon.com/dms/ Azure Database Migration Service. - Source: Hacker News / about 3 years ago
One of the features that I am currently missing with AWS Healthlake is a proper “event-ing” framework. With DynamoDB you’ve got streams. With RDS you can use DMS. But with Healthlake there is no native change data capture mechanism. - Source: dev.to / about 3 years ago
Professional Work: Python, Prefect for orchestration, Cloud Native CDC(GCP Datastream or AWS DMS), custom python code for other ETL, Postgres or Databricks (Delta Lake) depending on data volume, Pinecone for vectors, . Source: about 3 years ago
Yep, you should definitely swap over if the pricing isn't an issue. Database Migration Service might make the process easier. Source: about 3 years ago
You don't state that you are on AWS, but one service I've used to do a similar thing recently is AWS Database Migration Service. Which leverages a replication slot in PG to publish changes. You can feed those changes into a FIFO SQS queue which keeps the items in order, meaning that the Order would virtually always be created before the item. Source: over 3 years ago
Also check out database migration service, it can be used for migrating between VPC's and accounts: https://aws.amazon.com/dms/. Source: over 3 years ago
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 3 years ago
I think in some cases you are right, but my comment here brings up that these are frequently not the right tools for team's scale. Every cloud provider has a Change Data Capture (CDC) now. AWS has DMS andGCP has [Cloud Data Fusion](https://cloud.google.com/data-fusion/docs/concepts/replication for example. There is nothing inherently simpler about Snowflake/Redshift/Generic OLAP db than Postgres, if anything a lot... Source: over 3 years ago
We came across this useful service from Amazon called AWS DMS (Database Migration Service) that helps you migrate any database from one server to another. Not just MySQL, but any other databases like Postgres, MSSQL, etc. - Source: dev.to / over 3 years ago
In the previous article we went over the high-level approach around using AWS DMS and then created the replication instance on which your migration processing will run and then created the source and target endpoints that manage the connection to the source and target databases. The last step is to create the database migration task. - Source: dev.to / almost 4 years ago
The AWS Database Migration Service (AWS DMS) was designed to help quickly and securely migrate databases into AWS. The premise is that the source database remains available during the migration to help minimize application downtown. AWS DMS supports homogeneous migrations such as SQL Server to SQL Server or Oracle to Oracle as well as some heterogeneous migrations between different platforms. You can also use the... - Source: dev.to / almost 4 years ago
AWS Database Migration Service (AWS DMS) now supports virtual private cloud (VPC) endpoints as sources and targets. AWS DMS can now connect to any AWS service with VPC endpoints so long as explicitly defined routes to the services are defined in their AWS DMS VPC. - Source: dev.to / almost 4 years ago
I’m not really sure what exactly you’re looking to do. But I know about AWS Database Migration Service https://aws.amazon.com/dms/ Basically create a transformation function from one DB connection to another and let aws do the work. I don’t know how complicated it would be to implement. It always looks easier when someone tells you how they did it ha. Source: about 4 years ago
Look into DMS as it was built just for that https://aws.amazon.com/dms/. Source: over 4 years ago
AWS products, Glue, DMS and who knows what other product AWS has came up with. One of the issues I have with AWS is that everything is so much decoupled and there are so many products that it's hard to figure out what you can use at the end. Source: over 4 years ago
I've done a little research and seems that AWS DMS could be a solution, but I wonder how well it handles on-going replication and am curious if anyone here as used it. Source: over 4 years ago
The AWS Database Migration Service (DMS) enjoys a notable presence in the data integration and ETL space, offering capabilities that facilitate both one-time and continuous data replication processes. Public opinion about AWS DMS is largely mixed, with praises often shadowed by criticisms related to its real-world implementation.
Flexibility and Versatility: AWS DMS is recognized for supporting a range of database migrations, including both homogeneous (e.g., Oracle to Oracle) and heterogeneous (e.g., MySQL to PostgreSQL) migrations. It can handle migrations across relational, NoSQL, and other data stores, provided that at least one endpoint is hosted on AWS. This makes it suitable for various use cases, as highlighted in different blog posts discussing its capabilities like CDC (Change Data Capture) for Postgres and replication between MySQL and Aurora DB.
Ongoing Replication: One significant advantage of AWS DMS is its ability to not just migrate data but also support ongoing replication tasks. This functionality allows organizations to build strategies around zero-downtime migrations and ensure data is kept synchronized across environments. AWS DMS can function within a broader tech stack, integrating with services like Amazon RDS and third-party data structures.
Integration with AWS Ecosystem: AWS DMS effectively complements the AWS ecosystem. When coupled with tools like AWS Glue, it enhances automation in data processing and integration pipelines. This advantage plays a critical role for organizations that leverage AWS for broader cloud operations.
Performance Concerns: A recurring theme across user accounts is AWS DMS’s latency issues. With reported replication lag sometimes reaching up to 60 seconds, AWS DMS may not be ideal for real-time applications where low latency is crucial. Users have mixed experiences, with some seeing this trade-off as acceptable for less time-sensitive applications, while others find it a hindrance for real-time operations.
Product Maturity and Usability: Some critics perceive AWS DMS as being close to an "open beta" in terms of its maturity, with the need for additional adjustments to achieve satisfactory results. This sentiment was echoed in stories describing challenging yet ultimately successful migrations. There is an expectation that AWS DMS is not as streamlined or intuitive as it might appear initially, requiring technical adjustments to align with business requirements fully.
Comparative Analysis: When placed alongside other data migration and ETL tools, such as Azure Data Factory or GCP Datastream, AWS DMS can sometimes be overshadowed by these alternatives—especially in environments that are not Amazon-centric. As the integration landscape becomes increasingly competitive, AWS DMS must continue improving to maintain its relevance.
Overall, AWS DMS is a solid choice for AWS-centric operations needing database migration capabilities, mainly when existing infrastructure is already deployed within the AWS ecosystem. However, potential users should weigh its strengths against challenges like latency and the need for technical finesse. For organizations ready to invest in optimizing their DMS deployments, the service offers considerable value, although organizations seeking hassle-free, instant solutions might find its complexity burdensome. This duality in public opinion underscores AWS DMS as a powerful yet intricate tool, requiring mindful consideration and planning.
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