The Data Samurai

We have had performance issues when loading the bulk data into the AWS Aurora.  The bulk load performance was so bad that it was nearly worthless pushing around 2 million rows in to AWS Aurora.  We were inserting about 1000 records per second.  This was much worse comparing with the other MySQL counterparts like MySQL, MariaDB etc. However a few tweaks to the parameter and it resolved most of the performance issues we faced in the bulk Load. The solution is to add two parameters when you connect to the AWS Aurora jdbc for bulk load. These two parameters are : useServerPrepStatmts =false rewriteBatchedStatements =true Your full JDBC connection string should look like “jdbc:mysql://host:3306/db? useServerPrepStmts=false & rewriteBatchedStatements=true ", "username", “password”” Once we changed these parameters, the performance was blazing fast.  We were able to load the 2 million rows in flat 3 minutes. The Aurora Sever used in the benchark was r3....

AWS Aurora is the only PaaS offering for a Relational DBMS based on MYSQL platform.  Aurora is a game changer for many companies in a way.  Having worked my way through figuring out the different aspects here are the observations : Good : Almost Full Stack Mysql compatibility.  The scale up is painless Cheaper and Better alternative to other other RDBMS Benefits of any of the PaaS offering The Read Speed can be increased by creating multi AZ(Availability Zone) configuration. Bad : The write speed is poor when compared to the read speed. Lack of bulk import functionality, that makes data ingestion painful Overall : It is a very good alternative to other RDS instances (SQL Server / Oracle) Cost effective and better alternative to dynamodb. If you have structured data that can be handled by traditional DBMS.