![]() ![]() As Pete Carpenter described, creating a new Redshift instance is a simple matter of completing a few web forms and waiting for the cluster to come up. The original database remains open for query (but not update) during the scale-out (or scale-down) process. It is possible to dynamically change the number and or type of Redshift nodes in use, in effect a new cluster is spun up and the data copied from the existing system to the new before dropping the old system. In basic terms it is a share-nothing parallel processing columnar store database that supports columnar compression.Īt the cluster level all sorts of robustness features come in to play to handle routine hardware failures such as a node or disk regular automatic backups occur and on-demand backups can be made to S3 storage for DR or replication to other AWS networks. The Redshift product has its origins in ParAccel and that in turn Postgres and thus supports ANSI SQL and the ODBC and JDBC Postgres drivers. Parquet to redshift data types free#Apart from single node configurations, Redshift systems consist of a leader node and two or more database nodes the leader node is supplied free of charge (you only pay for the storage nodes) and is responsible for acting as the query parser, coordinating the results from the database nodes, and being a central network address for user access. For our trials we looked at the traditional disk based storage on a 2 node cluster to give us 4TB of disk spread across 4 CPU cores. Currently, there are 2 families of Redshift servers, the traditional hard-disk based, and the recently introduced SSD family, which has less storage but far more processing power and faster CPUs. As a cloud based system it is rented by the hour from Amazon, and broadly the more storage you hire the more you pay. Redshift is the Amazon Cloud Data Warehousing server it can interact with Amazon EC2 and S3 components but is managed separately using the Redshift tab of the AWS console. I am not going to talk performance in absolute terms as your mileage is going to vary. In this blog I will look at Amazon Redshift and how it compares with a more traditional DW approach using, as my example, Oracle. ![]() Recently, my colleague, Pete Carpenter, described a proof of concept we carried out using Amazon Redshift as the data warehouse storage layer in a system capturing data from Oracle E-Business Suite (EBS) using Attunity CloudBeam in conjunction with Oracle Data Integrator (ODI) for specialised ETL processing and Oracle Business Intelligence (OBI) as the reporting tool. ![]()
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