Register Now for AWS Database Migration Workshop
Story Highlights
Organizations are looking to enable new capabilities that improve performance at a reduced cost, all in a scalable, secure, and highly available environment. To achieve these goals, more companies are modernizing their database applications through cloud migration.
You can improve performance and agility while reducing costs by migrating your on-premises databases to managed Amazon Database and Analytic Services. Amazon Web Services (AWS) managed database services offer you the latest Database-as-a-Service capabilities to automating time-consuming administration tasks (hardware provisioning, database setup, patching, and backups) so you don’t have to spend time worrying about managing your databases. AWS also offers tools including the AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT) to help accelerate your database migrations.
The workshop will take place on Tuesday, November 20 from 8:30 a.m. to 1:30 p.m. ET at the AWS NYC Loft (350 W Broadway, New York, NY 10013)
Click HERE for more information and registration.
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake, and Amazon DynamoDB is a nonrelational database that delivers reliable performance at any scale.
In this informational session with partners you’ll learn:
- How cloud-native databases like Amazon Aurora, Redshift, and DynamoDB enable new capabilities, improve performance, and increase scale at a reduced cost.
- How to determine which database is right for your database workload.
- About APN Partners who can help accelerate your database migrations.
- How to free your organization from the expense and vendor lock-in of commercial database engines.
