The RedShift Advantage
- Dual Capability Redshift can be used both as a Data Warehouse and as a DataLake. A complementary service called Redshift Spectrum allows you to directly run SQL queries against exabytes of unstructured data in Amazon S3. No loading or transformation is required, and you can use open data formats, including Avro, CSV, Grok, Ion, JSON, ORC, Parquet, RCFile, RegexSerDe, SequenceFile, TextFile, and TSV.
- Fast processing The power of Massive Parallel Processing (MPP) capabilities of its data warehousing architecture and by utilizing all the available resources by distributing workload across multiple nodes, Redshift optimizes query processing even while processing huge volumes of data (petabyte).
- User Friendly Database administrators find it easy to adopt and use Redshift because of its striking similarities between Amazon Redshift’s relational database structure and the household SQL-based commands that can be operated upon it. Amazon Redshift automates the common administrative tasks to help manage, monitor, and scale your data warehouse with push-button simplicity
- Low cost The scalability of Amazon Redshift makes it an increasingly cost-effective alternative to traditional data warehousing practices. The on-demand pricing structure means you only pay for the resources you provision. Compared to more traditional, legacy data warehouses, Amazon Redshift provides a blend of both entry-level affordability and massive cost-efficiency at scale.
- Easy to configure and manage Provisioning is significantly simple as Amazon Redshift automatically handles lot of time and effort consuming aspects of managing your own data warehouse.Thus making it remarkably efficient to manage daily DevOps workflow.
- Advantages of The Amazon AWS Ecosystem For organizations already using Amazon AWS, there are considerable synergies for running Amazon Redshift with other services like speed, efficiency, cost and scalability.