Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data using your existing business intelligence tools. You can start small with no commitments, and scale to petabytes for less than a tenth of the cost of traditional solutions. Customers typically see 3x compression, reducing their costs significantly.
Features and benefits
Amazon Redshift delivers fast query performance by using columnar storage technology to improve I/O efficiency and parallelizing queries across multiple nodes. Amazon Redshift has custom JDBC and ODBC drivers that you can download from the Connect Client tab of our console, allowing you to use a wide range of familiar SQL clients. You can also use standard PostgreSQL JDBC and ODBC drivers. Data load speed scales linearly with cluster size, with integrations to Amazon S3, Amazon DynamoDB, Amazon Elastic MapReduce, Amazon Kinesis or any SSH-enabled host.
Amazon Redshift’s data warehouse architecture allows you to automate most of the common administrative tasks associated with provisioning, configuring and monitoring a cloud data warehouse. Backups to Amazon S3 are continuous, incremental and automatic. Restores are fast; you can start querying in minutes while your data is spooled down in the background. Enabling disaster recovery across regions takes just a few clicks.
Security is built-in. You can protect your data at rest and in transit, and use Amazon VPC to isolate your clusters. All API calls, connection attempts, queries and changes to the cluster are logged and auditable. You can use Amazon CloudTrail to audit Amazon Redshift API calls.
Optimized for Data Warehousing
Amazon Redshift uses a variety of innovations to obtain very high query performance on datasets ranging in size from a hundred gigabytes to a petabyte or more. It uses columnar storage, data compression, and zone maps to reduce the amount of I/O needed to perform queries. Amazon Redshift has a massively parallel processing (MPP) data warehouse architecture, parallelizing and distributing SQL operations to take advantage of all available resources. The underlying hardware is designed for high performance data processing, using local attached storage to maximize throughput between the CPUs and drives, and a 10GigE mesh network to maximize throughput between nodes.
With a few clicks of the Amazon Web Services Management Console or a simple API call, you can easily change the number or type of nodes in your cloud data warehouse as your performance or capacity needs change. Dense Storage (DS) nodes allow you to create very large data warehouses using hard disk drives (HDDs) for a very low price point. Dense Compute (DC) nodes allow you to create very high performance data warehouses using fast CPUs, large amounts of RAM and solid-state disks (SSDs). Amazon Redshift enables you to start with as little as a single 160GB DC2.Large node and scale up all the way to a petabyte or more of compressed user data using 16TB DS2.8XLarge nodes. While resizing, Amazon Redshift places your existing cluster into read-only mode, provisions a new cluster of your chosen size, and then copies data from your old cluster to your new one in parallel. You can continue running queries against your old cluster while the new one is being provisioned. Once your data has been copied to your new cluster, Amazon Redshift will automatically redirect queries to your new cluster and remove the old cluster.
No Up-Front Costs
You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing. For more details, visit the Billing Console.
Get Started in Minutes
With a few clicks in the Amazon Web Services Management Console or simple API calls, you can create a cluster, specifying its size, underlying node type, and security profile. Amazon Redshift will provision your nodes, configure the connections between them, and secure the cluster. Your data warehouse should be up and running in minutes.
Amazon Redshift handles all the work needed to manage, monitor, and scale your data warehouse, from monitoring cluster health and taking backups to applying patches and upgrades. You can easily resize your cluster as your performance and capacity needs change. By handling all these time-consuming, labor-intensive tasks, Amazon Redshift frees you up to focus on your data and business.
Amazon Redshift’s automated snapshot feature continuously backs up new data on the cluster to Amazon S3. Snapshots are continuous, incremental and automatic. Amazon Redshift stores your snapshots for a user-defined period, which can be from one to thirty-five days. You can take your own snapshots at any time, which leverage all existing system snapshots and are retained until you explicitly delete them. Redshift can also asynchronously replicate your snapshots to S3 in another region for disaster recovery. Once you delete a cluster, your system snapshots are removed but your user snapshots are available until you explicitly delete them.
You can use any system or user snapshot to restore your cluster using the Amazon Web Services Management Console or the Amazon Redshift APIs. Your cluster is available as soon as the system metadata has been restored and you can start running queries while user data is spooled down in the background.
Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3. Amazon Redshift continuously monitors the health of the cluster and automatically re-replicates data from failed drives and replaces nodes as necessary.
Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster. You can run Amazon Redshift inside Amazon Virtual Private Cloud (Amazon VPC) to isolate your data warehouse cluster in your own virtual network.
Audit and Compliance
Amazon Redshift integrates with Amazon CloudTrail to enable you to audit all Redshift API calls. Amazon Redshift also logs all SQL operations, including connection attempts, queries and changes to your database. You can access these logs using SQL queries against system tables or choose to have them downloaded to a location on Amazon S3.
Amazon Redshift is a SQL data warehouse solution and uses industry standard ODBC and JDBC connections. You can download our custom JDBC and ODBC drivers from the Connect Client tab of our console.
Amazon Redshift is integrated with other Amazon Web Services services and has built in commands to load data in parallel to each node from Amazon S3, Amazon DynamoDB or your Amazon EC2 instances, and on-premise servers using SSH. Amazon Kinesis also integrates with Amazon Redshift as a data target.
Redshift makes it simple and cost effective to run high performance queries on petabytes of semi-structured and structured data so that you can build powerful reports and dashboards using business intelligence tools.
Operational analytics on events
Bring together structured data from your data warehouse and semi-structured data such as application logs from your S3 data lake to get real-time operational insights on your applications and systems.
Data as a service
Share data inside and outside your organization for secure and governed collaboration on live data with Redshift data sharing.
Use SQL to automatically create, train, and deploy Amazon SageMaker models on the data in your data warehouse.