A Commitment to the AWS Cloud Platform
AtScale counts some of the largest enterprises in the world as customers, many of which have created Big Data Lakes on the Amazon Cloud platform. Amazon EMR (Elastic MapReduce) was one of the first Hadoop-as-a-Service cloud environments AtScale supported as Matt Baird, co-founder and CTO at AtScale, remembers:
Our vision has always been to remain agnostic to where the data is stored. We work with Hadoop in the cloud exactly the same way we work with Hadoop on premises. We’ve worked with Amazon EMR since day one because we’ve found that the platform’s reliability and flexibility were great assets to enterprises’ I.T. departments.”
The Hadoop-as-a-Service market has witnessed tremendous growth and market leader AWS continues to grow more rapidly than the overall market. Amazon is taking on a dominant role in the enterprise analytics arsenal and market leaders like AtScale are deepening their integration with the Amazon stack.
Beyond Hadoop in the Cloud
AWS EMR is often used as a Hadoop Data Lake, hosting large-scale transformation and processing tasks. To support long-lasting analytical workloads in the cloud, Amazon customers often deploy the Amazon Redshift platform for data warehousing workloads. Now, with data in the EMR Data Lake and the Redshift data warehouse, enterprises need a universal semantic layer that empowers user query and data analysis with best-in-class experience.
AtScale’s upcoming support will let Amazon customers benefit from the affordability, scalability and flexibility of the AWS Cloud platform while enabling enterprise Business Intelligence capabilities whether data is stored in EMR, Redshift or even on-premise.
AtScale already provides support of all on-premises Hadoop distributions and recently announced support for the Google and the Microsoft Clouds. With the added support for the Amazon Cloud, AtScale is the only company that makes enterprises “future-proof” for their Big Data analytics investments across on-premise and multi-cloud Data Lakes.
The enterprise reality is a hybrid one,” says David Menninger. “Our Data and Analytics in the Cloud benchmark research shows 44% of participants processing a hybrid of cloud and on-premises data. AtScale’s vision to provide analysis on data wherever it resides, aligns well with enterprise requirements and is reflected in its customers’ deployments.”
The AtScale Universal Semantic Layer for Amazon Redshift brings 3 key innovations to cloud users:
- AtScale Adaptive Cache™: Connecting users to large datasets often leads to query latency for usage patterns involving quick filters, pick-lists and granular data. As enterprises deploy more users on Redshift, more concurrent users create additional stress and latency on the cloud platform. Instead of falling back on data extracts or data marts, the AtScale Adaptive Cache guarantees sub second performance on virtually any data type or size and scales user concurrency without moving data.
- Hybrid Query Service™: The average enterprise has dozens of Business Intelligence tools, from MicroStrategy to Power BI to Tableau. Each tool requires its own query language, SQL or MDX. AtScale’s Hybrid Query Service makes it the industry’s only platform to support both MDX and SQL. This means, all users, regardless of their BI tools, will be able to work with the Amazon Cloud with a live connection.
- AtScale’s True Delegation™: Governance and security are top priorities to companies who want to deliver self-service analytics to their users. AtScale’s True Delegation™ ensures that every query is associated with the end-user who executes it while satisfying the most stringent data governance and access auditing policies. The Platform works seamlessly with Apache Sentry, Apache Ranger and fully supports LDAP and Kerberos.
By deploying AtScale on Amazon Redshift, enterprises can finally benefit from a highly secure, open and advanced platform for BI on Big Data on premise and in the Cloud.