Welcome to Codingcompiler. Amazon Redshift is a fast and scalable data warehouse as a service from the cloud, designed for large data volumes up to the petabyte range. The typical administration tasks of the Data Warehouse are automated by the Amazon vendor. Business intelligence tools and SQL clients can connect to Amazon Redshift.
What is Amazon Redshift?
Amazon Redshift is a data warehouse service from the cloud. The data warehouse can hold data down to the petabyte range and is provided by Amazon on a cloud infrastructure.
Amazon Redshift is characterized by its high speed and good scalability, which can accelerate the processing and evaluation of large amounts of data. Queries are possible among others SQL-based. There are also ODBC and JDBC interfaces that Business Intelligence tools can use to connect to the data warehouse.
Amazon Redshift achieves high query speeds by physically distributing resources to a clustered structure and parsing processing. The typical data warehouse management tasks, such as backing up clusters, patching and updating, operating, monitoring, provisioning, and provisioning, are automated by Amazon. The first release of Amazon Redshift was released in 2012, based on an older version of PostgreSQL 8.0.2. A first official version was released in 2013.
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The cluster structure of Amazon Redshift
Amazon Redshift is based on a cluster structure. The service can be operated as a single-node cluster with a single server for smaller data volumes or as a multi-node cluster with many servers for large amounts of data.
A multi-node cluster consists of at least three nodes, a leader node and two compute nodes. The tasks of the Leader node are the management of the connections and requests, the provision of the execution plans and the parsing of the requests.
The actual execution of the calculations and queries takes place on the compute nodes. Individual compute nodes have storage capacities of two or 16 terabytes. The maximum storage capacity of a cluster is up to 1.6 petabytes. The nodes are connected to each other via a powerful 10 Gigabit / s backbone.
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Comparison of traditional data warehouses and Amazon Redshift
There are major differences between traditional data warehouses and Amazon Redshift. With traditional data warehouses, there is a great deal of time and resources spent on administrative activities. Amazon Redshift is fully managed as a cloud service and requires little resources in this regard.
Amazon Redshift delivers high processing speeds compared to a self-managed data warehouse because of the clustering and parallelism of requests. Own servers, network infrastructure or software are not required. There are no investments to provide the service.
Billing from Amazon Redshift is usage-based. According to Amazon, Amazon Redshift achieves up to ten times the performance of traditional databases for data warehouses. While traditional solutions often store their data on a line-by-line basis, Amazon Redshift works column-based, greatly improving query performance and providing greater compression capabilities.
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The automated administration services of Amazon Redshift
A key feature of Amazon Redshift is the integrated, automated management of all the tasks required to operate, set up, scale, and secure the service. Managed services range from providing the data processing infrastructure to securing the service to patching or updating.
All nodes are automatically monitored. After failures Amazon provides for the complete restoration of the services. Other management services include load balancing and planning the execution of queries.
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Benefits of using Amazon Redshift
There are many benefits to using Amazon Redshift as the data warehouse service from the cloud. Amazon provides a scalable, high-performance data warehouse that can handle huge amounts of data.
This reduces the cost and complexity of extensive data analysis. The setup of the data warehouse is done quickly and requires no investment in hardware or software. The billing of the service is usage-dependent.
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By using optimized hardware, smart caching, and parallel architecture, Amazon Redshift achieves high throughput and low response times. Almost all administrative tasks are automated and do not require any additional effort. Databases can be encrypted using a variety of cryptographic techniques and offer a high level of security.
As a result, Amazon Redshift can be used for critical applications in the financial, healthcare, or government sector. The clusters of the data warehouse can be isolated using Amazon Virtual Private Cloud (VPC).