Amazon Redshift provides an excellent scale-out option as your data and query complexity grows if you want to prevent your reporting and analytic processing from interfering with the performance of your OLTP workload. Amazon Redshift harnesses the scale and resources of multiple nodes and uses a variety of optimizations to provide order of magnitude improvements over traditional databases for analytic and reporting workloads against very large data sets. OLTP workloads require quickly querying specific information and support for transactions like insert, update, and delete and are best handled by Amazon RDS. Customers use Amazon RDS databases primarily for online-transaction processing (OLTP) workload while Redshift is used primarily for reporting and analytics. Redshift Spectrum automatically scales query compute capacity based on the data retrieved, so queries against Amazon S3 run fast, regardless of data set size.īoth Amazon Redshift and Amazon RDS enable you to run traditional relational databases in the cloud while offloading database administration. No loading or transformation is required, and you can use open data formats, including Avro, CSV, Grok, Amazon Ion, JSON, ORC, Parquet, RCFile, RegexSerDe, Sequence, Text, and TSV. Amazon Redshift also includes Amazon Redshift Spectrum, allowing you to run SQL queries directly against exabytes of unstructured data in Amazon S3 data lakes. With Redshift, you can start small for just $0.25 per hour with no commitments and scale out to petabytes of data for $1,000 per terabyte per year, less than a tenth the cost of traditional on-premises solutions.
It allows you to run complex analytic queries against terabytes to petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance storage, and massively parallel query execution. Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.
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