Posted On: Nov 11, 2013
Performance and Data Loading
- Distributed Tables: Tables can be distributed to all the compute nodes in an Amazon Redshift cluster, which can dramatically speed up certain queries because the replicated tables are effectively collocated with all other tables in the cluster, eliminating the need to transfer data between nodes.
- Approximate Count Distinct: Queries that return counts in the millions or more should see much faster performance when using approximate count distinct, implemented using the HyperLogLog algorithm, with a bounded error of up to 2%.
- Workload Queue Memory Management: Customers can specify the percentage of memory in addition to the number of query execution slots to assign to work queues in their clusters, giving them more flexibility when configuring workload management.
- Copy from Remote Hosts: Using this feature, customers can load their Redshift clusters in parallel from Amazon Elastic MapReduce (Amazon EMR) or other HDFS clusters, Amazon EC2 instances and other remote hosts using multiple SSH connections.
Security and Control
- Hardware Security Module (HSM) and AWS CloudHSM Support: You can use an on-premises HSM or AWS CloudHSM to manage your keys when using encrypted Amazon Redshift clusters.
- Database Auditing and Logging: Amazon Redshift logs information about connections and user activity related to your database, allowing you to monitor your cluster for security and troubleshooting processes. Customers can choose to enable database auditing and have these logs downloaded to Amazon S3 for secure and convenient access.
- Key Rotation: Customers can rotate keys for encrypted Amazon Redshift clusters based on their own corporate policies for data security. Customers can rotate keys managed by Amazon Redshift or an HSM.
- Event Notifications: Customers can choose to receive notifications about cluster events via Amazon Simple Notification Service (Amazon SNS).
To learn more, please visit the Amazon Redshift detail page and the Amazon Redshift documentation. If you have feedback or there are other features you'd like to see, please let us know in the Amazon Redshift forum.