Analytics on AWS
100s of thousands
3X
faster with Amazon EMR than standard Apache Spark
5X
70%
100s of trillions
AWS analytics services
Amazon Athena
Query data in Amazon S3 using SQL.
Amazon EMR
Run open source big data frameworks.
Amazon Redshift
Fast, simple, cost-effective data warehousing.
Amazon Kinesis
Analyze real-time video and data streams.
Amazon OpenSearch Service
Search, visualize, and analyze up to petabytes of text and unstructured data.
Amazon QuickSight
Fast business analytics service.
AWS Glue DataBrew
Clean and normalize data up to 80 percent faster.
AWS Glue
Prepare and load data.
Amazon Managed Streaming for Apache Kafka (MSK)
Fully managed, highly available, and secure Apache Kafka service.
Amazon Kinesis Video Streams
Capture, process, and store video streams for analytics and ML.
Amazon Kinesis Data Firehose
Prepare and load real-time data streams into data stores and analytics tools.
Amazon Kinesis Data Streams
Collect streaming data for real-time analytics at scale.
AWS Database Migration Service
Replicate data from SQL and NoSQL systems to data stores and analytics systems.
AWS Data Exchange
Find and subscribe to third-party data in the cloud.
AWS analytics services
Solution areas
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Advanced analytics
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Data management
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Predictive analytics & machine learning
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Advanced analytics
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Advanced analytics
AWS provides the broadest and most cost-effective set of analytics services to help you gain insights faster from all your data.
Broadest selection of analytics services
Each analytics service is purpose-built for a wide range of analytics use cases such as interactive analysis, big data processing, data warehousing, real-time analytics, operational analytics, dashboards, and visualizations.
Reduce downtime & improve capacity utilization
By reducing Mean Time to Detect (MTTD) and Mean Time To Respond (MTTR), you can focus on fixing problems just as quickly as identifying them.
Price-performant
AWS is committed to providing the best performance at the lowest cost across all analytics services, and we are continually innovating to improve the price performance of our services.
Related AWS services
Resources
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Data management
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Data management
AWS makes it easy for you to combine, move, and replicate data across multiple data stores and your data lake.
Scalable
Collect, store, organize, and analyze data from multiple sources and formats and scale it to any size. Use AWS Lake Formation to automate tasks required to set up a data lake while saving time defining data structures, schema, and transformations.
Ease of use
AWS allows you to easily move data between the data lake and purpose-built data services. For example, AWS Glue is a serverless data integration service that makes it easy to prepare data for analytics, machine learning, and application development.
Faster data integration
AWS gives you the ability to query data across different data sources such as databases, data lakes, and data warehouses. For example, Amazon Athena enables you to use SQL to query a data lake and federated query lets you query live data from relational databases.
Flexible and fast
Easily ingest data in a variety of ways, including leveraging Amazon Kinesis, AWS Import/Export Snowball, AWS Direct Connect, and more. Store all of your data, regardless of volume or format, using Amazon Simple Storage Service (Amazon S3). You can also query data across different data sources such as databases, data lakes, and data warehouses.
Ease of movement
With data stored in a number of different systems, AWS allows you to easily move that data between all of your services and data stores: inside out, outside in, and around the perimeter.
Related AWS services
Resources
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Predictive analytics & machine learning
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Predictive analytics & machine learning
For predictive analytics use cases, AWS provides a broad set of machine learning services and tools that run on your data lake on AWS.
Deeper and faster insights
AWS analytics services leverage proven machine learning (ML) and natural language capabilities to help you gain deeper and faster insights from your data.
Platform integration
AWS provides built-in ML integration as part of its purpose-built data stores and analytics services, allowing you to create, train, and deploy ML models using familiar languages like SQL.
Experience
AWS is committed to providing the best performance at the lowest cost across all analytics services and we are continually innovating to improve the price-performance of our services.
Related AWS services
Resources
Featured Solutions on AWS
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Centralized Logging with OpenSearch
Build a centralized log analytics platform with Amazon OpenSearch Service on AWS in 20 minutes.
Streaming Data Solution for Amazon Kinesis
Real-time data streaming solution that allows you to continuously capture data for processing
Maintaining Personalized Experiences with Machine Learning
Develop and deploy personalization workloads through end-to-end automation and scheduling of updates for resources within the Amazon Personalize service.
Customers
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Moderna
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Moderna runs all its SAP S/4HANA workloads on AWS, including manufacturing, accounting, and inventory management, which enables the company to achieve greater efficiency and visibility across its operations. Moderna uses Amazon Redshift as a central repository for all the data it captures and stores backups in Amazon S3.
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Salesforce
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Salesforce created a single source of truth for customer data its Customer Data Platform using AWS services including Amazon EMR, providing marketers with a detailed view of their customers. The company creates clusters on demand based on its workloads and process data up to 2X faster than before while reducing cost by 42%.
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Intuit
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Intuit migrated to an Amazon Redshift-based solution that scales to more than 7X the data volume with zero effort and delivers 20X performance over the company's previous solution. This resulted in a 90 percent reduction in time-to-insight, and a 66 percent cost reduction.
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Pinterest
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Pinterest scaled daily log search and analytics to 1.7 TB and reduced cost by 30 percent by moving to managed analytics using Amazon OpenSearch Service (successor to Amazon Elasticsearch Service). The company scaled its log analysis capabilities to reduce operational burdens, improve security, and reduce costs.

"We built a 120TB data lake in Amazon S3, with 1500 different schemes and use AWS analytics services like Glue, Redshift, and Athena extensively. We couldn’t get these insights from a bunch of siloed databases and warehouses - we needed an S3 scale data lake."
- Bernardo Rodriguez
Chief Digital Officer, J.D. Power
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