redshift vs postgresql vs oracle architectural differences

#Redshift vs postgresql vs oracle architectural differences code#
#Redshift vs postgresql vs oracle architectural differences series#

The number of slices per node is determined by the node size of the cluster. The slices then work in parallel to complete the operation. The leader node manages to distribute data to the slices and apportions the workload for any queries or other database operations to the slices. Each slice is allocated a portion of the node’s memory and disk space, where it processes a portion of the workload assigned to the node. You can start with a single 160 GB node and scale up to multiple 16 TB nodes to support a petabyte of data or more.įor a more detailed explanation of data warehouse clusters and nodes, see Internal Architecture and System Operation.Ī compute node is partitioned into slices. As your workload grows, you can increase the compute capacity and storage capacity of a cluster by increasing the number of nodes, upgrading the node type, or both.Īmazon Redshift provides two node types dense storage nodes and dense compute nodes.

#Redshift vs postgresql vs oracle architectural differences code#

The compute nodes execute the compiled code and send intermediate results back to the leader node for final aggregation.Įach compute node has its own dedicated CPU, memory, and attached disk storage, which is determined by the node type. The leader node compiles code for individual elements of the execution plan and assigns the code to individual compute nodes.

For more information, see SQL Functions Supported on the Leader Node. A query that uses any of these functions will return an error if it references tables that reside on the compute nodes. Amazon Redshift is designed to implement certain SQL functions only on the leader node. All other queries run exclusively on the leader node. The leader node distributes SQL statements to the compute nodes only when a query references tables that are stored on the compute nodes. Based on the execution plan, the leader node compiles code, distributes the compiled code to the compute nodes, and assigns a portion of the data to each compute node.

#Redshift vs postgresql vs oracle architectural differences series#

It parses and develops execution plans to carry out database operations, in particular, the series of steps necessary to obtain results for complex queries. The leader node manages communications with client programs and all communication with compute nodes. The compute nodes are transparent to external applications. Your client application interacts directly only with the leader node. If a cluster is provisioned with two or more compute nodes, an additional leader node coordinates the compute nodes and handles external communication.

The core infrastructure component of an Amazon Redshift data warehouse is a cluster.Ī cluster is composed of one or more compute nodes. For more information, see Amazon Redshift and PostgreSQL JDBC and ODBC. For information about important differences between Amazon Redshift SQL and PostgreSQL, see Amazon Redshift and PostgreSQL.Īmazon Redshift communicates with client applications by using industry-standard PostgreSQL JDBC and ODBC drivers. Amazon Redshift is based on industry-standard PostgreSQL, so most existing SQL client applications will work with only minimal changes. This section introduces the elements of the Amazon Redshift data warehouse architecture as shown in the following figure.Īmazon Redshift integrates with various data loading and ETL (extract, transform, and load) tools and business intelligence (BI) reporting, data mining, and analytics tools. This section presents an introduction to the Amazon Redshift system architecture.

When you execute analytic queries, you are retrieving, comparing, and evaluating large amounts of data in multiple-stage operations to produce a final result.Īmazon Redshift achieves efficient storage and optimum query performance through a combination of massively parallel processing, columnar data storage, and very efficient, targeted data compression encoding schemes. Using Amazon Redshift with Other ServicesĪn Amazon Redshift data warehouse is an enterprise-class relational database query and management system.Īmazon Redshift supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools.Internal Architecture and System Operation.