Redshift Reviews & Pricing

Key Features

• Massively Parallel Processing: Parallelize and distribute SQL (Structured Query Language) operations. Use local attached storage to maximize throughput between CPUs and drives.
• End-To-End Encryption: Utilize SSL encryption to secure data in transit and AES-256 encryption for data at rest. Encrypt all data written to disk and backup files. Migrate data between encrypted and unencrypted clusters and make use of highly customizable and robust data security options. 
• Cost-Effective: Enjoy on-demand pricing with no upfront costs, no commitments and no hidden charges. Pay only for the resources used. Use the pause and resume feature to suspend on-demand billing when the cluster isn’t going and pay only for backup storage.
• Scalable: Change the number or type of nodes with a few clicks from the console or an API call. Share live data across clusters, improving the agility of the company. Use S3 as a highly available, secure and cost-effective data lake, storing unlimited data in open formats.
• Advanced Query Accelerator: Enable the platform to run ten times faster by automatically boosting certain types of queries.
• Currency Scaling: Support thousands of users and queries simultaneously, enabling superior performance. Process queries without delays and assign clusters to particular groups and workloads while controlling the number.
• Data Sharing: Enable instant, granular and high-performance data access across clusters without moving or copying data. See information as it’s updated in the data warehouse via live access, at no additional cost. Provide a secure and organized collaboration within and across companies.
• Concurrency Limits: Attain flexibility while maintaining concurrency limits similar to other data warehouses. Configure limits based on regions instead of applying a single limit to all users.
• Fault Tolerance: Enhance the reliability of the data warehouse cluster — automatically re-replicate data and shift data to healthy nodes on the failure of drives, nodes and clusters.
• Column-Oriented Databases: Allow quick access to large data amounts and accomplish massive data processing tasks in an instant.
• Automatic Workload Management: Easily segregate a workload and assign a part of cluster resources to every workload.

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