AWS Launches Amazon Athena New pay-as-you-go interactive query service makes it easy to analyze data in Amazon S3 using Standard SQL
Atlassian, Nasdaq, and News Corp. among the many customers using Amazon Athena to get query results in seconds
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SEATTLE--(BUSINESS WIRE)--Nov. 30, 2016-- Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), today announced Amazon Athena, a serverless query service that makes it easy to analyze data directly in Amazon Simple Storage Service (Amazon S3) using standard SQL. With a few clicks in the AWS Management Console, customers can point Amazon Athena at their data stored in Amazon S3 and begin using standard SQL to run queries and get results in seconds. With Amazon Athena there are no clusters to manage and tune, no infrastructure to setup or manage, and customers pay only for the queries they run. Amazon Athena scales automatically - executing queries in parallel - so results are fast, even with large datasets and complex queries. To get started with Amazon Athena, visit https://aws.amazon.com/athena.
AWS analytics services like Amazon Redshift and Amazon EMR have made petabyte-scale analytics accessible to companies of all sizes. With Amazon Redshift, customers can perform complex queries on massive collections of structured data and get superfast performance. For unstructured data, Amazon EMR makes it fast and cost-effective to process and analyze vast amounts of data across dynamically scalable clusters using popular distributed frameworks like Apache Spark, Presto, Hive, and Pig. While these services are scalable and powerful enough to handle the largest and most complex big data applications, many customers also want to be able to very quickly run queries on data stored in Amazon S3 (e.g. web logs, clickstreams, and raw event files) without having to spin up, configure, and manage a Hadoop cluster or a data warehouse. Now, with Amazon Athena, analyzing data stored in Amazon S3 is as simple as writing SQL queries. Amazon Athena uses Presto with full standard SQL support and works with a variety of standard data formats, including CSV, JSON, ORC, and Parquet. And, while Amazon Athena is ideal for quick, ad-hoc querying and integrates with Amazon QuickSight for easy visualization, it can also handle complex analysis, including large joins, window functions, and arrays. Because Amazon Athena executes queries using compute resources in multiple Availability Zones and uses Amazon S3 as the underlying data store, it is highly available and durable with data redundantly stored across multiple facilities and multiple devices in each facility.
Over the past few years, AWS has built a comprehensive set of big data services that customers use to do everything from real-time analytics on streaming data, to petabyte-scale data warehousing, or Spark and Hadoop jobs - and its all fast, scalable, and cost-effective, said Raju Gulabani, Vice President, Databases, Analytics, and AI, AWS. For hundreds of thousands of customers, Amazon S3 is their primary data store - holding billions to trillions of objects. Customers have frequently asked us whether we could make it easy for anyone to run queries on their data in Amazon S3 without having to worry about provisioning or managing servers and clusters. Now they can. There is absolutely zero admin with Amazon Athena - anyone who can write a SQL query can analyze their data in Amazon S3. Amazon QuickSight and Amazon Athena are tightly integrated, enabling customers to visualize their Amazon Athena query results without even writing a SQL query.
We are long time customers of AWS, and use services like Amazon Redshift and Amazon EMR to support and power analytics across the company, said Paul Cheesbrough, Chief Technology Officer, News Corp. We received early access to Amazon Athena, and it has proven to be fast, easy to use, and cost effective. Weve had great feedback from our teams of engineers and analysts, especially on Amazon Athenas ability to query directly from Amazon S3, and were excited about where we go next with the service.
LiveIntent, a platform for people-based marketing and advertising focused on the email channel, helps over 1,100 brands deliver marketing and advertising to 145 million people in emails sent by 1,300 top Publishers every month. The LiveIntent platform collects and processes hundreds of millions of events per day. We are continuously challenging ourselves to build and extend the platform to provide faster and cheaper access to data, which in turn translates to better and faster insights for our customers, said Eric Raab, Executive Vice President of Engineering, LiveIntent. We found Amazon Athena to be faster and cheaper than any other solution we evaluated and decided utilize its capabilities right away. We really like that Amazon Athena has zero administration, and that we can query a multitude of formats directly from Amazon S3 with no loading required.
DataXu helps marketers understand how marketing investments can lead to profitable customer relationships using data. We process 3M+ bid requests per second, which results in a total of 3PB of incoming data every day. Even with compression and reduction, this results in 180+ Terabytes of logs per day, said Yekesa Kosuru, Vice President, Engineering, DataXu. We started using Amazon Athena as soon as we heard about it and are loving its simplicity, speed, and pay-per-query pricing model. Amazon Athena provides us with the ability to query our entire data set stored on Amazon S3, without the need to manage infrastructure. Because theres nothing to manage and we only pay per query, were actively deploying Amazon Athena throughout the company.
Gunosy is a leading Japanese provider of news curation apps. We began using Amazon Athena as soon as we could and were impressed that even in prev
