AWS Launches Amazon Redshift Spectrum

AWS Launches Amazon Redshift Spectrum

New capability allows Amazon Redshift customers to run analytic queries quickly and inexpensively against exabytes of data in Amazon S3

SEATTLE--(BUSINESS WIRE)--Apr. 19, 2017-- Today, Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced Amazon Redshift Spectrum, a new feature that allows Amazon Redshift customers to run SQL queries against exabytes of their data in Amazon Simple Storage Service (Amazon S3). With Redshift Spectrum, customers can extend the analytic power of Amazon Redshift beyond data stored on local disks in their data warehouse to query vast amounts of unstructured data in their Amazon S3 data lake - without having to load or transform any data. Redshift Spectrum applies sophisticated query optimization, scaling processing across thousands of nodes so results are fast - even with large data sets and complex queries. To get started with Redshift Spectrum, visit https://aws.amazon.com/redshift/spectrum.

Amazon Redshift is one of AWS's fastest-growing services because it allows customers to perform complex queries on petabytes of structured data stored on high-performance local disks and get superfast performance - all for a tenth of the cost of traditional data warehouses. However, as the cost of data storage has continued to drop, customers are increasingly storing vast amounts of data in Amazon S3 data lakes, including unstructured data that may never make it into a data warehouse. Now, with Redshift Spectrum, analyzing all of this data is as easy as running a standard Amazon Redshift SQL query. Redshift Spectrum directly queries data in Amazon S3, with no loading or transformation required, using the open data formats customers already use, including CSV, TSV, Parquet, Sequence, and RCFile. Since Redshift Spectrum supports the same SQL syntax of Amazon Redshift, customers can run sophisticated queries using the same Business Intelligence (BI) tools they do today. They can also run queries that span both the frequently accessed data stored locally in Amazon Redshift and their full data sets stored cost-effectively in Amazon S3. Redshift Spectrum automatically scales query compute capacity based on the data being retrieved, so queries against Amazon S3 data run fast, whether processing just a few terabytes, petabytes, or even exabytes.

Customers such as Amgen, Boingo Wireless, Electronic Arts, Hearst, Lyft, Nasdaq, Scholastic, TripAdvisor, and Yahoo! are migrating to Amazon Redshift in droves because it leverages the scale of AWS to analyze petabytes of data with ten times the performance at one-tenth the cost of old guard data warehouses. Many of these customers have asked us to extend the speed and flexibility of Amazon Redshift beyond the data warehouse to analyze all of the data they have in Amazon S3, said Raju Gulabani, Vice President, Databases, Analytics, and AI, AWS. Redshift Spectrum does just this, offering the best of both worlds by making it incredibly easy to query exabytes of data in Amazon S3 directly from Amazon Redshift. We're excited to now make exabyte-scale analytics fast, simple and accessible to companies of all sizes.

Tokyo-based NTT DOCOMO is the largest mobile service provider in Japan, serving more than 68 million customers. Our data analysis platform collects tens of terabytes of log data each day from a variety of internal and external sources to help us improve our logistics and marketing operations. Migrating to Amazon Redshift two years ago allowed us to scale to over ten petabytes of uncompressed data with a ten times performance improvement over our prior on-premises system, said Mick Etoh, Senior Vice President and General Manager of Innovation Management Department, NTT DOCOMO. Redshift Spectrum will let us expand the universe of the data we analyze to 100s of petabytes over time. This is truly a game changer, and we can think of no other system in the world that can get us there.

Time Inc. is a leading content company that engages over 150 million consumers every month through its portfolio of premium brands across platforms. As a media company, we receive a large quantity of data from a number of ad serving providers. This data comes in a variety of formats and needs to be integrated with our own internal systems in order for our teams to be able to analyze it, said Vladimir Barkov, Director of Data Architecture and Engineering at Time Inc. Redshift Spectrum enables us to directly operate on our data in its native format in Amazon S3 with no preprocessing or transformation. Our data pipeline is much simpler now, and our execution time has been lowered significantly.

Edmunds offers detailed, constantly updated information about vehicles to 20 million monthly visitors. Amazon Redshift's scalability allows us to support our ever-growing data volumes, unlike our previous, on-premises data warehouse solution, said Ajit Zadgaonkar, Edmunds's Executive Director of Operations and Infrastructure. With Redshift Spectrum, we no longer need to think about what data to retain for analysis and what to throw away. We can now run real SQL queries directly on many years of data stored cost-effectively in Amazon S3. Redshift Spectrum's fast performance across massive data sets is unprecedented.

Redfin is the next-generation real estate brokerage, combining its own full-service agents with modern technology to redefine real estate in the consumer's favor across more than 80 metros in the US. With millions of users and hundreds of millions of property listings, our website and internal systems generate a vast amount of data. Our data analytics platform has been built from the ground up on AWS, using Amazon S3 for storage, Amazon Kinesis for streaming, Amazon EMR for data processing and real-time applications, and Amazon Redshift

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