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Business performance at scale, speed and scalability from SQL Server to DynamoDB with AWS DMS.
Problem

Recurso Confiable was experiencing slow application performance due to the large volume of data, causing delays in the information that the GPS provider sends about the positioning of its users’ vehicles they decided to migrate their main tables from a database relational to a non-relational database.
Challenges

The methods of connection and interaction with the data from the application. § Stop thinking relationally and start thinking in a non-relational structure. §Identify the tables with the highest volume of data to be migrated to a non-relational structure and which will continue in a relational database. §How to map objects to determine source data to destination
Solution

To achieve a successful migration from SQL Server to DynamoDB IKTINUS proposed AWS DMS (Database Migration Service) to migrate the source data to DynamoDB using object mapping to restructure the original data to the desired data structure in DynamoDB Minimizing downtime during migration.Outcomes.Outcomes.
Outcomes

- Using a fully managed database increased the level of agility and minimize operational overhead, in addition to ensuring the high availability of the application
- Automatic storage scalability, since there is no limit to the amount of data you can store in a DynamoDB table
- Flexibility of querying an attribute using secondary indexes that have the same performance, scalability, and fault tolerance characteristics as those in a DynamoDB table.
- Access data with millisecond latency at any scale
- Cost-effectiveness since is specified the number of data reads and writes per second that need for the application.
Lessons Learned

Differences and impact in terms of costs and time on when to use Query and Scan.
Using mapping rules to migrate data from source to destination.
Using APIS to communicate and interact with DynamoDB tables.
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