AWS Database Migration Service (AWS DMS) is a cloud service that makes it easy to migrate relational databases, data warehouses, NoSQL databases, and other types of data stores. You can use AWS DMS to migrate your data into the AWS Cloud or between combinations of cloud and on-premises setups.
AWS DMS is a server in the AWS Cloud that runs replication software. You create a source and target connection to tell AWS DMS where to extract from and load to. Then you schedule a task that runs on this server to move your data.
How AWS DMS Works?
AWS Database Migration Service (AWS DMS) is a web service that you can use to migrate data from a source data store to a target data store. These two data stores are called endpoints. You can migrate between source and target endpoints that use the same database engine, such as from an Oracle database to an Oracle database. You can also migrate between source and target endpoints that use different database engines, such as from an Oracle database to a PostgreSQL database. The only requirement to use AWS DMS is that one of your endpoints must be on an AWS service. You can't use AWS DMS to migrate from an on-premises database to another on-premises database.
At a high level, when using AWS DMS you do the following:
- Create a replication server.
- Create source and target endpoints that have connection information about your data stores.
- Create one or more migration tasks to migrate data between the source and target data stores.
A task can consist of three major phases:
- The full load of existing data
- The application of cached changes
- Ongoing replication
AWS DMS loads data from tables on the source data store to tables on the target data store. While the full load is in progress, any changes made to the tables being loaded are cached on the replication server; these are the cached changes.
When the full load for a given table is complete, AWS DMS immediately begins to apply the cached changes for that table. Once the table is loaded and the cached changes applied, AWS DMS begins to collect changes as transactions for the ongoing replication phase.
At the start of the ongoing replication phase, a backlog of transactions generally causes some lag between the source and target databases. The migration eventually reaches a steady state after working through this backlog of transactions. At this point, you can shut down your applications, allow any remaining transactions to be applied to the target, and bring your applications up, now pointing at the target database.
Limitations:
AWS DMS creates the target schema objects necessary to perform the migration. However, AWS DMS takes a minimalist approach and creates only those objects required to efficiently migrate the data. In other words, AWS DMS creates tables, primary keys, and in some cases unique indexes, but doesn't create any other objects that are not required to efficiently migrate the data from the source. For example, it doesn't create secondary indexes, nonprimary key constraints, or data defaults.
AWS DMS doesn't perform schema or code conversion. If you want to convert an existing schema to a different database engine, you can use AWS SCT. AWS SCT converts your source objects, table, indexes, views, triggers, and other system objects into the target data definition language (DDL) format. You can also use AWS SCT to convert most of your application code, like PL/SQL or TSQL, to the equivalent target language.
In the next part we will discuss about AWS SCT (Schema Conversion Tool) for heterogeneous migrations.
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