At Lucy in the Cloud, we spend all day helping our customers optimize their performance on Amazon Redshift. We have a front-row view of all the ways that Redshift can be used to help businesses manage their data. Redshift is a versatile product that can help businesses aggregate, store, analyze, and share their data.
The use-case when it comes to data warehousing is to unify disparate data sources in a single place and run custom analytics for your business.
With a rich ecosystem of data integration vendors, it’s easy to build pipelines to those sources and feed data into Redshift. Put a powerful BI / dashboard tool on top, and you have a full-blown BI stack. – Xavier Legrand, Lucy in the cloud
A key advantage of Redshift is simplicity. It used to take months to get a data warehouse up and running.
None of that anymore!
You can spin up a Redshift cluster in less than 15 minutes, and build a whole business intelligence stack in a weekend.
Analyze all of your data with the fastest and most widely used cloud data warehouse.
Analyze all of your data
No other data warehouse makes it as easy to gain new insights from all your data. With Redshift, you can query and combine exabytes of structured and semi-structured data across your data warehouse, operational database, and data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats, like Apache Parquet, so that you can do additional analytics from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker.
Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. Amazon EMR makes it easy to set up, operate, and scale your big data environments by automating time-consuming tasks like provisioning capacity and tuning clusters.
With EMR you can run petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. You can run workloads on Amazon EC2 instances, on Amazon Elastic Kubernetes Service (EKS) clusters, or on-premises using EMR on AWS Outposts.
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.
Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.
Amazon QuickSight is a scalable, serverless, embeddable, machine learning-powered business intelligence (BI) service built for the cloud. QuickSight lets you easily create and publish interactive BI dashboards that include Machine Learning-powered insights. QuickSight dashboards can be accessed from any device, and seamlessly embedded into your applications, portals, and websites.
QuickSight is serverless and can automatically scale to tens of thousands of users without any infrastructure to manage or capacity to plan for. It is also the first BI service to offer pay-per-session pricing, where you only pay when your users access their dashboards or reports, making it cost-effective for large scale deployments.
With QuickSight, you can ask business questions of your data in plain language and receive answers in seconds.
Performance at any scale
Amazon Redshift has up to 3x better price-performance than other cloud data warehouses, and the price-performance advantage improves as your data warehouse grows from gigabytes to exabytes.
Amazon Redshift takes advantage of AWS designed-hardware and machine learning (ML) to deliver the best price performance at any scale. This includes using the AWS Nitro System to accelerate data compression and encryption, ML techniques to analyze queries, and graph optimization algorithms to automatically organize and store data for faster query results.
Experience the next generation of Redshift with AQUA (Advanced Query Accelerator)
AQUA is a new distributed and hardware accelerated cache that allows Redshift queries to run up to 10x faster than other enterprise cloud data warehouses by automatically boosting certain operations. AQUA accelerates scan, filtering, and aggregation operations today, and will accelerate more operations in the future.
Success Stories with Amazon Redshift
Want to know how we used the power of Amazon Redshift to solve our customers’ data-related challenges?
Click on one of the use-cases below to find out more!