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Zero-ETL for self-managed Database Sources now available in 7 new regions https://docs.aws.amazon.com/glue/latest/dg/zero-etl-using.html now supports zero-ETL for self-managed database sources in seven additional regions. Using Glue zero-ETL, you can setup an integration to replicate data from Oracle, SQL Server, MySQL or PostgreSQL databases which are located on-premises or on AWS EC2 to Redshift with a simple experience that eliminates configuration complexity. AWS zero-ETL for self-managed database sources will automatically create an integration for an on-going replication of data from your on-premises or EC2 databases through a simple, no-code interface. You can now replicate data from Oracle, SQL Server, MySQL and PostgreSQL databases into Redshift. This feature further reduces users' operational burden and saves weeks of engineering effort needed to design, build, and test data pipelines to ingest data from self-managed databases to Redshift. AWS Glue zero-ETL for self-managed database sources are available in the following additional AWS Regions: Asia Pacific (Hong Kong), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (London), South America (São Paulo), and US (Virginia) regions. To get started, sign into the https://us-east-1.console.aws.amazon.com/ec2/home?region=us-east-1#LaunchInstances:instanceType=r8a.large. For more information visit the https://aws.amazon.com/glue/ or review the https://docs.aws.amazon.com/glue/latest/dg/zero-etl-using.html documentation.

Zero-ETL for self-managed Database Sources now available in 7 new regions

docs.aws.amazon.com/glue/latest/dg/zero-etl-... now supports zero-ETL for self-managed database sources in seven additional regions. Using Glue z...

#AWS #AwsDatabaseMigrationService #AmazonRedshift #AwsGlue

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Zero-ETL for self-managed Database Sources now available in 7 new regions https://docs.aws.amazon.com/glue/latest/dg/zero-etl-using.html now supports zero-ETL for self-managed database sources in seven additional regions. Using Glue zero-ETL, you can setup an integration to replicate data from Oracle, SQL Server, MySQL or PostgreSQL databases which are located on-premises or on AWS EC2 to Redshift with a simple experience that eliminates configuration complexity. AWS zero-ETL for self-managed database sources will automatically create an integration for an on-going replication of data from your on-premises or EC2 databases through a simple, no-code interface. You can now replicate data from Oracle, SQL Server, MySQL and PostgreSQL databases into Redshift. This feature further reduces users' operational burden and saves weeks of engineering effort needed to design, build, and test data pipelines to ingest data from self-managed databases to Redshift. AWS Glue zero-ETL for self-managed database sources are available in the following additional AWS Regions: Asia Pacific (Hong Kong), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (London), South America (São Paulo), and US (Virginia) regions. To get started, sign into the https://us-east-1.console.aws.amazon.com/ec2/home?region=us-east-1#LaunchInstances:instanceType=r8a.large. For more information visit the https://aws.amazon.com/glue/ or review the https://docs.aws.amazon.com/glue/latest/dg/zero-etl-using.html documentation.

Zero-ETL for self-managed Database Sources now available in 7 new regions

docs.aws.amazon.com/glue/latest/dg/zero-etl-... now supports zero-ETL for self-managed database sources in seven additional regions. Using Glue z...

#AWS #AwsDatabaseMigrationService #AmazonRedshift #AwsGlue

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Zero-ETL for self-managed Database Sources now available in 7 new regions AWS Glue now supports zero-ETL for self-managed database sources in seven additional regions. Using Glue zero-ETL, you can setup an integration to replicate data from Oracle, SQL Server, MySQL or PostgreSQL databases which are located on-premises or on AWS EC2 to Redshift with a simple experience that eliminates configuration complexity. AWS zero-ETL for self-managed database sources will automatically create an integration for an on-going replication of data from your on-premises or EC2 databases through a simple, no-code interface. You can now replicate data from Oracle, SQL Server, MySQL and PostgreSQL databases into Redshift. This feature further reduces users' operational burden and saves weeks of engineering effort needed to design, build, and test data pipelines to ingest data from self-managed databases to Redshift. AWS Glue zero-ETL for self-managed database sources are available in the following additional AWS Regions: Asia Pacific (Hong Kong), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (London), South America (São Paulo), and US (Virginia) regions. To get started, sign into the AWS Management Console. For more information visit the AWS Glue page or review the AWS Glue zero-ETL documentation.

🆕 AWS Glue introduces zero-ETL for self-managed databases in 7 new regions: HK, Tokyo, Singapore, Sydney, London, São Paulo, and Virginia. It eases data replication from Oracle, SQL Server, MySQL, or PostgreSQL to Redshift, cutting down e…

#AWS #AwsDatabaseMigrationService #AmazonRedshift #AwsGlue

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AWS Databases are now available on the Vercel Marketplace Today, AWS Databases including Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB are generally available on the Vercel Marketplace, enabling you to create and connect to an AWS database directly from Vercel in seconds. To get started, you can create a new AWS Account from Vercel that includes access to the three databases and $100 USD in credits. These credits can be used with any of these database option for up to six months. Once your account is set up, you can have a production-ready Aurora database or DynamoDB table powering your Vercel projects within seconds. You can also manage your plan, add payment information, and view usage details anytime by visiting the AWS settings portal from the Vercel dashboard. To learn more, visit the https://vercel.com/marketplace/aws on the Vercel Marketplace. The integration includes serverless options for https://aws.amazon.com/rds/aurora/, https://aws.amazon.com/rds/aurora/dsql/, and https://aws.amazon.com/dynamodb/?nc2=type_a to simplify your application needs and reduce costs by scaling to zero when not in use. You can create a database in the following https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Tokyo), and Asia Pacific (Mumbai) with more Regions coming soon. AWS Databases deliver security, reliability, and price performance without the operational overhead, whether you're prototyping your next big idea or running production AI and data driven applications. For more information, visit the https://aws.amazon.com/products/databases/

AWS Databases are now available on the Vercel Marketplace

Today, AWS Databases including Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB are generally available on the Vercel Marketplace, enabling you to create ...

#AWS #AmazonDynamodb #AmazonAurora #AwsDatabaseMigrationService

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AWS Databases are now available on the Vercel Marketplace Today, AWS Databases including Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB are generally available on the Vercel Marketplace, enabling you to create and connect to an AWS database directly from Vercel in seconds. To get started, you can create a new AWS Account from Vercel that includes access to the three databases and $100 USD in credits. These credits can be used with any of these database option for up to six months. Once your account is set up, you can have a production-ready Aurora database or DynamoDB table powering your Vercel projects within seconds. You can also manage your plan, add payment information, and view usage details anytime by visiting the AWS settings portal from the Vercel dashboard. To learn more, visit the AWS landing page on the Vercel Marketplace. The integration includes serverless options for Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB to simplify your application needs and reduce costs by scaling to zero when not in use. You can create a database in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Tokyo), and Asia Pacific (Mumbai) with more Regions coming soon. AWS Databases deliver security, reliability, and price performance without the operational overhead, whether you're prototyping your next big idea or running production AI and data driven applications. For more information, visit the AWS Databases webpage.

🆕 AWS Databases like Aurora and DynamoDB are now on Vercel Marketplace for quick setup and a $100 six-month credit. Manage and scale serverless databases across regions with no overhead. Visit AWS on Vercel for details.

#AWS #AmazonDynamodb #AmazonAurora #AwsDatabaseMigrationService

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AWS DMS Schema Conversion adds SAP (Sybase) ASE to PostgreSQL support with generative AI AWS https://aws.amazon.com/dms/ (DMS) https://docs.aws.amazon.com/dms/latest/userguide/CHAP_SchemaConversion.html is a fully managed feature of DMS that automatically assesses and converts database schemas to formats compatible with AWS target database services. Today, we're excited to announce that Schema Conversion now supports conversions from SAP Adaptive Server Enterprise (ASE) database (formerly known as Sybase) to Amazon RDS PostgreSQL and Amazon Aurora PostgreSQL, powered by Generative AI capability. Using Schema Conversion, you can automatically convert database objects from your SAP (Sybase) ASE source to an to Amazon RDS PostgreSQL and Amazon Aurora PostgreSQL target. The integrated generative AI capability intelligently handles complex code conversions that typically require manual effort, such as stored procedures, functions, and triggers. Schema Conversion also provides detailed assessment reports to help you plan and execute your migration effectively. To learn more about this feature, see the documentation for using SAP (Sybase) ASE as a source forhttps://docs.aws.amazon.com/dms/latest/userguide/dm-data-providers-source-sybase-ASE.html and using SAP (Sybase) ASE as a source for https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.SAP.html for data migration. For details about the generative AI capability, please refer to the https://docs.aws.amazon.com/dms/latest/userguide/schema-conversion-convert.databaseobjects.html#schema-conversion-convert.databaseobjects.genai. For AWS DMS Schema Conversion regional availability, please refer to the https://docs.aws.amazon.com/dms/latest/userguide/CHAP_SchemaConversion.html#schema-conversion-supported-regions page.

AWS DMS Schema Conversion adds SAP (Sybase) ASE to PostgreSQL support with generative AI

AWS https://aws.amazon.com/dms/ (DMS) docs.aws.amazon.com/dms/latest/userguide/CHA... is a fully managed feature of DMS that automatically ass...

#AWS #AwsDatabaseMigrationService

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AWS DMS Schema Conversion adds SAP (Sybase) ASE to PostgreSQL support with generative AI AWS Database Migration Service (DMS) Schema Conversion is a fully managed feature of DMS that automatically assesses and converts database schemas to formats compatible with AWS target database services. Today, we're excited to announce that Schema Conversion now supports conversions from SAP Adaptive Server Enterprise (ASE) database (formerly known as Sybase) to Amazon RDS PostgreSQL and Amazon Aurora PostgreSQL, powered by Generative AI capability. Using Schema Conversion, you can automatically convert database objects from your SAP (Sybase) ASE source to an to Amazon RDS PostgreSQL and Amazon Aurora PostgreSQL target. The integrated generative AI capability intelligently handles complex code conversions that typically require manual effort, such as stored procedures, functions, and triggers. Schema Conversion also provides detailed assessment reports to help you plan and execute your migration effectively. To learn more about this feature, see the documentation for using SAP (Sybase) ASE as a source for AWS DMS Schema Conversion and using SAP (Sybase) ASE as a source for AWS DMS for data migration. For details about the generative AI capability, please refer to the User Guide. For AWS DMS Schema Conversion regional availability, please refer to the Supported AWS Regions page.

🆕 AWS DMS Schema Conversion now supports SAP ASE to PostgreSQL migrations using generative AI for automatic, detailed conversion of complex database objects, simplifying migrations.

#AWS #AwsDatabaseMigrationService

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AWS DMS introduces Data Resync for improved migration accuracy AWS Database Migration Service (AWS DMS) now supports Data Resync, a new feature that automatically corrects data inconsistencies identified during validation between source and target databases. Data Resync integrates with your existing DMS migration tasks and supports both Full Load and Change Data Capture (CDC) phases. It uses your current task settings—including connection configurations, table mappings, and transformations—to apply corrections automatically, helping ensure accurate and reliable migrations without manual intervention. With Data Resync, AWS DMS can detect and resolve common data issues, such as missing records, duplicate entries, or mismatched values, based on validation results. Data Resync is available starting with AWS DMS replication engine version 3.6.1, and currently supports migration paths from Oracle and SQL Server to PostgreSQL. For detailed information on how Data Resync enhances migration accuracy, please refer to the https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Validating.DataResync.html

AWS DMS introduces Data Resync for improved migration accuracy

AWS Database Migration Service (AWS DMS) now supports Data Resync, a new feature that automatically corrects data inconsistencies identified during validation between source and target databases.
...

#AWS #AwsDatabaseMigrationService

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AWS DMS introduces Data Resync for improved migration accuracy AWS Database Migration Service (AWS DMS) now supports Data Resync, a new feature that automatically corrects data inconsistencies identified during validation between source and target databases. Data Resync integrates with your existing DMS migration tasks and supports both Full Load and Change Data Capture (CDC) phases. It uses your current task settings—including connection configurations, table mappings, and transformations—to apply corrections automatically, helping ensure accurate and reliable migrations without manual intervention. With Data Resync, AWS DMS can detect and resolve common data issues, such as missing records, duplicate entries, or mismatched values, based on validation results. Data Resync is available starting with AWS DMS replication engine version 3.6.1, and currently supports migration paths from Oracle and SQL Server to PostgreSQL. For detailed information on how Data Resync enhances migration accuracy, please refer to the AWS DMS Technical Documentation.

🆕 AWS DMS introduces Data Resync to automatically correct data inconsistencies during migration, ensuring accurate and reliable migrations without manual intervention, available from Oracle and SQL Server to PostgreSQL.

#AWS #AwsDatabaseMigrationService

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Announcing AWS DMS Serverless automatic storage scaling https://aws.amazon.com/dms/ (AWS DMS Serverless) now offers storage scaling. With this enhancement you never have to worry about exceeding the DMS Serverless 100GB default replication storage capacity limit when processing very large transaction volumes or using detailed logging. You can now use AWS DMS Serverless for replicating even the highest of transaction volumes since there is no longer any storage capacity limits. AWS DMS Severless will automatically increase the storage for your replications any time the existing capacity reaches it limits. To learn more, see the https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Serverless.Components.html#CHAP.Serverless.storage.autoscaling. For AWS DMS regional availability, please refer to the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/.

Announcing AWS DMS Serverless automatic storage scaling

https://aws.amazon.com/dms/ (AWS DMS Serverless) now offers storage scaling. With this enhancement you never have to worry about exceeding the DMS Serverless 100GB default replication sto...

#AWS #AwsDatabaseMigrationService #AmazonRedshift

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Announcing AWS DMS Serverless automatic storage scaling AWS Database Migration Service Serverless (AWS DMS Serverless) now offers storage scaling. With this enhancement you never have to worry about exceeding the DMS Serverless 100GB default replication storage capacity limit when processing very large transaction volumes or using detailed logging. You can now use AWS DMS Serverless for replicating even the highest of transaction volumes since there is no longer any storage capacity limits. AWS DMS Severless will automatically increase the storage for your replications any time the existing capacity reaches it limits. To learn more, see the AWS DMS Serverless storage capacity documentation. For AWS DMS regional availability, please refer to the AWS Region Table.

🆕 AWS DMS Serverless now scales storage automatically, eliminating the 100GB limit for replications, enabling seamless handling of large transaction volumes with no storage capacity constraints. For details, see AWS DMS Serverless documentation.

#AWS #AwsDatabaseMigrationService #AmazonRedshift

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AWS DMS Schema Conversion now supports conversions from IBM Db2 for z/OS to Amazon RDS for Db2 AWS https://aws.amazon.com/dms/ (DMS) Schema Conversion is a fully managed feature of DMS that automatically assesses and converts database schemas to formats compatible with AWS target database services. Today, we are excited to announce that Schema Conversion now supports conversions from IBM Db2 for z/OS to https://aws.amazon.com/rds/db2/. Using Schema Conversion, you can automatically convert database objects from your IBM Db2 for z/OS source to an Amazon RDS for Db2 target, including stored procedures, functions, views, and other database structures. This is especially valuable for mainframe migrations as it simplifies complex processes by resolving syntax differences and compatibility issues between environments. Schema Conversion also provides detailed assessment reports to help you plan and execute your migration effectively. To learn more refer to using https://docs.aws.amazon.com/dms/latest/userguide/sc-data-providers-db2.html and https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.DB2zOS.html. For AWS DMS Schema Conversion regional availability, please refer to the https://docs.aws.amazon.com/dms/latest/userguide/CHAP_SchemaConversion.html#schema-conversion-supported-regions.  

AWS DMS Schema Conversion now supports conversions from IBM Db2 for z/OS to Amazon RDS for Db2

AWS https://aws.amazon.com/dms/ (DMS) Schema Conversion is a fully managed feature of DMS that automatically assesses and converts database schemas to formats compa...

#AWS #AwsDatabaseMigrationService

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AWS DMS Schema Conversion now supports conversions from IBM Db2 for z/OS to Amazon RDS for Db2 AWS Database Migration Service (DMS) Schema Conversion is a fully managed feature of DMS that automatically assesses and converts database schemas to formats compatible with AWS target database services. Today, we are excited to announce that Schema Conversion now supports conversions from IBM Db2 for z/OS to Amazon Relational Database Service (RDS) for Db2. Using Schema Conversion, you can automatically convert database objects from your IBM Db2 for z/OS source to an Amazon RDS for Db2 target, including stored procedures, functions, views, and other database structures. This is especially valuable for mainframe migrations as it simplifies complex processes by resolving syntax differences and compatibility issues between environments. Schema Conversion also provides detailed assessment reports to help you plan and execute your migration effectively. To learn more refer to using IBM Db2 z/OS as a source for AWS DMS Schema Conversion and using IBM Db2 for z/OS as a source for AWS DMS. For AWS DMS Schema Conversion regional availability, please refer to the AWS Region Table.

🆕 AWS DMS Schema Conversion now supports migrating IBM Db2 for z/OS to Amazon RDS for Db2, simplifying mainframe migrations by resolving syntax differences and providing detailed assessment reports.

#AWS #AwsDatabaseMigrationService

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AWS Database Migration Service now supports Multi-ENI networking for homogeneous migrations. Amazon Database Migration Service (DMS) now supports the Multi-ENI networking model and Credentials Vending System for DMS Homogenous Migrations. Customers can now choose the Multi-ENI connection type and use the Credentials Vending System, providing a simplified networking configuration experience for secure connectivity to their on-premises database instances. For information see documentation for AWS https://docs.aws.amazon.com/dms/latest/userguide/data-migrations.html. For AWS DMS regional availability, please refer to the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/.  

AWS Database Migration Service now supports Multi-ENI networking for homogeneous migrations.

Amazon Database Migration Service (DMS) now supports the Multi-ENI networking model and Credentials Vending System for DMS Homogenous Migrations.

Customers can n...

#AWS #AwsDatabaseMigrationService

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AWS Database Migration Service now supports Multi-ENI networking for homogeneous migrations. Amazon Database Migration Service (DMS) now supports the Multi-ENI networking model and Credentials Vending System for DMS Homogenous Migrations. Customers can now choose the Multi-ENI connection type and use the Credentials Vending System, providing a simplified networking configuration experience for secure connectivity to their on-premises database instances. For information see documentation for AWS DMS Homogeneous Migrations. For AWS DMS regional availability, please refer to the AWS Region Table.

🆕 AWS Database Migration Service now supports Multi-ENI networking for homogeneous migrations.

#AWS #AwsDatabaseMigrationService

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Announcing AWS DMS Serverless comprehensive premigration assessments https://aws.amazon.com/dms/ (AWS DMSS) now supports premigration assessments for replications . A premigration assessment evaluates the source and target databases of a database migration task to help identify problems that might prevent a migration from running as expected. By identifying and fixing these issues before a migration starts, you can avoid delays in completing the database migration. The premigration assessments will obtain detailed information about the source schema and tables to provide recommendations on the AWS DMS settings that should be used. For example, the assessment can suggest which method of reading redo logs for change data capture (CDC) should be used or it could check if the recommended settings have been enabled, providing best practice recommendations from AWS DMS experts. To learn more, see https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Tasks.AssessmentReport.html. AWS DMSS premigration assessments are available in all AWS Regions where DMSS is available. For AWS DMSS regional availability, please refer to the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/.  

Announcing AWS DMS Serverless comprehensive premigration assessments

https://aws.amazon.com/dms/ (AWS DMSS) now supports premigration assessments for replications . A premigration assessment evaluates the source and target databases of a datab...

#AWS #AwsDatabaseMigrationService #AmazonRedshift

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Announcing AWS DMS Serverless comprehensive premigration assessments AWS Database Migration Service Serverless (AWS DMSS) now supports premigration assessments for replications . A premigration assessment evaluates the source and target databases of a database migration task to help identify problems that might prevent a migration from running as expected. By identifying and fixing these issues before a migration starts, you can avoid delays in completing the database migration. The premigration assessments will obtain detailed information about the source schema and tables to provide recommendations on the AWS DMS settings that should be used. For example, the assessment can suggest which method of reading redo logs for change data capture (CDC) should be used or it could check if the recommended settings have been enabled, providing best practice recommendations from AWS DMS experts. To learn more, see Enabling and working with premigration assessments. AWS DMSS premigration assessments are available in all AWS Regions where DMSS is available. For AWS DMSS regional availability, please refer to the AWS Region Table.

🆕 Announcing AWS DMS Serverless comprehensive premigration assessments

#AWS #AwsDatabaseMigrationService #AmazonRedshift

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Announcing the general availability of AWS Database Migration Service Serverless support for files with an S3 source endpoint AWS Database Migration Service Serverless (AWS DMSS) now supports files on S3 source endpoints. Using AWS DMSS, you can now migrate data in CSV or parquet format from S3 to any supported AWS DMSS target endpoint. AWS DMSS supports both full load and Change Data Capture (CDC) migration modes for CSV and Parquet files with S3 source endpoints using AWS DMS console, AWS CLI, or AWS SDKs in https://docs.aws.amazon.com/dms/latest/userguide/CHAP_ReplicationInstance.html For information about AWS DMS S3 source endpoints see https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.S3.html. Visit https://aws.amazon.com/dms/ to get started. For AWS DMS regional availability, please refer to the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/.

Announcing the general availability of AWS Database Migration Service Serverless support for files with an S3 source endpoint

AWS Database Migration Service Serverless (AWS DMSS) now supports files on S3 source endpoints. Using AWS DMSS, you can now...

#AWS #AwsDatabaseMigrationService #AmazonS3

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Announcing the general availability of AWS Database Migration Service Serverless support for files with an S3 source endpoint AWS Database Migration Service Serverless (AWS DMSS) now supports files on S3 source endpoints. Using AWS DMSS, you can now migrate data in CSV or parquet format from S3 to any supported AWS DMSS target endpoint. AWS DMSS supports both full load and Change Data Capture (CDC) migration modes for CSV and Parquet files with S3 source endpoints using AWS DMS console, AWS CLI, or AWS SDKs in all regions where DMSS is available. For information about AWS DMS S3 source endpoints see DMS S3. Visit AWS DMS to get started. For AWS DMS regional availability, please refer to the AWS Region Table.

🆕 Announcing the general availability of AWS Database Migration Service Serverless support for files with an S3 source endpoint

#AWS #AwsDatabaseMigrationService #AmazonS3

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AWS DMS now supports Kerberos authentication for Oracle and SQL Server Source Endpoints https://aws.amazon.com/dms/ now allows customers to use Kerberos authentication to securely connect to Oracle and SQL Server source endpoints. This feature allows users to authenticate database connections using the Kerberos protocol, a widely adopted standard for secure identity verification. With this update, AWS DMS can authenticate using credentials stored in AWS Directory Service for Microsoft Active Directory or in an on-premises Microsoft Active Directory that has a forest trust relationship with an AWS Managed Active Directory. Customers can use this feature for Oracle Database and SQL Server without additional licensing costs, simplifying secure migrations. This feature can be configured directly in the AWS DMS Console, CLI, or SDK. To learn more about Kerberos authentication with AWS DMS, please refer to our https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Security.Kerberos.html.

AWS DMS now supports Kerberos authentication for Oracle and SQL Server Source Endpoints

https://aws.amazon.com/dms/ now allows customers to use Kerberos authentication to securely connect to Oracle and SQL Server source endpoints. This feature allows users to...

#AWS #AwsDatabaseMigrationService

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AWS DMS now supports Kerberos authentication for Oracle and SQL Server Source Endpoints AWS Database Migration Service (AWS DMS) now allows customers to use Kerberos authentication to securely connect to Oracle and SQL Server source endpoints. This feature allows users to authenticate database connections using the Kerberos protocol, a widely adopted standard for secure identity verification. With this update, AWS DMS can authenticate using credentials stored in AWS Directory Service for Microsoft Active Directory or in an on-premises Microsoft Active Directory that has a forest trust relationship with an AWS Managed Active Directory. Customers can use this feature for Oracle Database and SQL Server without additional licensing costs, simplifying secure migrations. This feature can be configured directly in the AWS DMS Console, CLI, or SDK. To learn more about Kerberos authentication with AWS DMS, please refer to our technical documentation.

🆕 AWS DMS now supports Kerberos authentication for Oracle and SQL Server Source Endpoints

#AWS #AwsDatabaseMigrationService

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AWS DMS Schema Conversion now uses generative AI AWS Database Migration Service (AWS DMS) Schema Conversion with generative AI is now available. The feature is currently available for database schema conversion from commercial engines, such as Microsoft SQL Server, to Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL. Using generative AI recommendations, you can simplify and accelerate your database migration projects, particularly when converting complex code objects which typically require manual conversion, such as stored procedures, functions, or triggers. AWS DMS Schema Conversion with generative AI converts up to 90% of your schema. AWS DMS Schema Conversion with generative AI is currently available in three https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/: US East (N. Virginia), US West (Oregon), and Europe (Frankfurt). You can use this feature in the AWS Management Console or AWS Command Line Interface (AWS CLI) by selecting a commercial database such as Microsoft SQL Server as your source database and Amazon Aurora PostgreSQL or Amazon RDS for PostgreSQL as your target when initiating a schema conversion project. When converting applicable objects, you will see an option to enable generative AI for conversion. To get started, visit the https://docs.aws.amazon.com/dms/latest/userguide/CHAP_SchemaConversion.html and check out this https://aws.amazon.com/blogs/aws/aws-data-migration-service-improves-database-schema-conversion-with-generative-ai.

AWS DMS Schema Conversion now uses generative AI

AWS Database Migration Service (AWS DMS) Schema Conversion with generative AI is now available. The feature is currently available for database schema conversion from commercial engines, such as Microsoft SQL S...

#AWS #AwsDatabaseMigrationService

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AWS DMS Schema Conversion now uses generative AI AWS Database Migration Service (AWS DMS) Schema Conversion with generative AI is now available. The feature is currently available for database schema conversion from commercial engines, such as Microsoft SQL Server, to Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL. Using generative AI recommendations, you can simplify and accelerate your database migration projects, particularly when converting complex code objects which typically require manual conversion, such as stored procedures, functions, or triggers. AWS DMS Schema Conversion with generative AI converts up to 90% of your schema. AWS DMS Schema Conversion with generative AI is currently available in three AWS Regions: US East (N. Virginia), US West (Oregon), and Europe (Frankfurt). You can use this feature in the AWS Management Console or AWS Command Line Interface (AWS CLI) by selecting a commercial database such as Microsoft SQL Server as your source database and Amazon Aurora PostgreSQL or Amazon RDS for PostgreSQL as your target when initiating a schema conversion project. When converting applicable objects, you will see an option to enable generative AI for conversion. To get started, visit the AWS DMS Schema Conversion User Guide and check out this blog post.

🆕 AWS DMS Schema Conversion now uses generative AI

#AWS #AwsDatabaseMigrationService

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AWS Database Migration Service now automates time-intensive schema conversion tasks using generative AI AWS DMS Schema Conversion converts up to 90% of your schema to accelerate your database migrations and reduce manual effort with the power of generative AI.

AWS Database Migration Service now automates time-intensive schema conversion tasks using generative AI

AWS DMS Schema Conversion converts up to 90% of your schema to accelerate your d...

#AWS #AmazonAurora #AmazonRds #Announcements #AwsDatabaseMigrationService #Database #Launch #Migration #News

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AWS DMS now supports Data Masking https://aws.amazon.com/dms/ now supports Data Masking, enabling customers to transform sensitive data at the column level during migration, helping to comply with data protection regulations like GDPR. Using AWS DMS, you can now create copies of data that redacts information at a column level that you need to protect. AWS Data Masking will automatically mask the portions of data you specify. Data Masking offers three transformation techniques: digit randomization, digit masking, and hashing. It's available for all endpoints supported by DMS Classic and DMS Serverless in version 3.5.4. To learn more about Data Masking with AWS DMS, please please refer to the https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Tasks.CustomizingTasks.TableMapping.SelectionTransformation.Masking.html.

AWS DMS now supports Data Masking

https://aws.amazon.com/dms/ now supports Data Masking, enabling customers to transform sensitive data at the column level during migration, helping to comply with data protection regulations like GDPR. Using AWS DMS, you can ...

#AWS #AwsDatabaseMigrationService

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AWS DMS now supports Data Masking AWS Database Migration Service (AWS DMS) now supports Data Masking, enabling customers to transform sensitive data at the column level during migration, helping to comply with data protection regulations like GDPR. Using AWS DMS, you can now create copies of data that redacts information at a column level that you need to protect. AWS Data Masking will automatically mask the portions of data you specify. Data Masking offers three transformation techniques: digit randomization, digit masking, and hashing. It's available for all endpoints supported by DMS Classic and DMS Serverless in version 3.5.4. To learn more about Data Masking with AWS DMS, please please refer to the AWS DMS technical documentation.

🆕 AWS DMS now supports Data Masking

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AWS DMS now delivers improved performance for data validation https://aws.amazon.com/dms/ has enhanced data validation performance for database migrations, enabling customers to validate large datasets with significantly faster processing times. This enhanced data validation is now available in version 3.5.4 of the replication engine for both full load and full load with CDC migration tasks. Currently, this enhancement supports migration paths from Oracle to PostgreSQL, SQL Server to PostgreSQL, Oracle to Oracle, and SQL Server to SQL Server, with additional migration paths planned for future releases. To learn more about data validation performance improvements with AWS DMS, please refer to thehttps://docs.aws.amazon.com/dms/latest/userguide/CHAP_Validating.html#CHAP_Validating_Enhanced.

AWS DMS now delivers improved performance for data validation

https://aws.amazon.com/dms/ has enhanced data validation performance for database migrations, enabling customers to validate large datasets with significantly faster processing times.

This enh...

#AWS #AwsDatabaseMigrationService

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AWS DMS now delivers improved performance for data validation AWS Database Migration Service (AWS DMS) has enhanced data validation performance for database migrations, enabling customers to validate large datasets with significantly faster processing times. This enhanced data validation is now available in version 3.5.4 of the replication engine for both full load and full load with CDC migration tasks. Currently, this enhancement supports migration paths from Oracle to PostgreSQL, SQL Server to PostgreSQL, Oracle to Oracle, and SQL Server to SQL Server, with additional migration paths planned for future releases. To learn more about data validation performance improvements with AWS DMS, please refer to the AWS DMS Technical Documentation.

🆕 AWS DMS now delivers improved performance for data validation

#AWS #AwsDatabaseMigrationService

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Announcing AWS DMS Serverless improved Oracle to S3 full load throughput AWS Database Migration Service Serverless (AWS DMSS) now offers improved throughput for Oracle to Amazon S3 full load migrations. With this enhancement, you can now migrate data from Oracle databases to S3 up to two times faster than previously possible with AWS DMSS. AWS DMSS Oracle to Amazon S3 Full Load performance enhancements will be applied automatically whenever AWS DMSS detects a full load migration between an Oracle database and Amazon S3. For detailed information on these improvements, refer to the AWS DMSS enhanced throughput documentation. To learn more, see the AWS DMS Full Load for Oracle databases documentation. For AWS DMS regional availability, please refer to the AWS Region Table.

🆕 Announcing AWS DMS Serverless improved Oracle to S3 full load throughput

#AWS #AwsDatabaseMigrationService #AmazonRedshift

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Announcing AWS DMS Serverless improved Oracle to S3 full load throughput https://aws.amazon.com/dms/ (AWS DMSS) now offers improved throughput for Oracle to Amazon S3 full load migrations. With this enhancement, you can now migrate data from Oracle databases to S3 up to two times faster than previously possible with AWS DMSS. AWS DMSS Oracle to Amazon S3 Full Load performance enhancements will be applied automatically whenever AWS DMSS detects a full load migration between an Oracle database and Amazon S3. For detailed information on these improvements, refer to the AWS DMSS https://aws.amazon.com/blogs/database/enhanced-full-load-performance-in-aws-dms-serverless/ documentation. To learn more, see the AWS DMS https://docs.aws.amazon.com/dms/latest/sbs/chap-manageddatabases.oracle2rds.load.html documentation. For AWS DMS regional availability, please refer to the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/.

Announcing AWS DMS Serverless improved Oracle to S3 full load throughput

https://aws.amazon.com/dms/ (AWS DMSS) now offers improved throughput for Oracle to Amazon S3 full load migrations. With this enhancement, you can now migrate data from O...

#AWS #AwsDatabaseMigrationService #AmazonRedshift

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