The new service makes cloud data lakes 10x easier, enabling companies to leverage an open data architecture and avoid having to copy data into proprietary data warehouses
Dremio, the SQL lakehouse company, announced its cloud-native SQL-based data lakehouse service, Dremio Cloud. Purpose-built for the cloud, Dremio Cloud makes cloud data lakes 10x easier, while delivering infinite scale and industry-leading security. Dremio Cloud enables organizations of any size to leverage a no-copy open data architecture that eliminates the need to copy data into expensive and proprietary data warehouses.
Dremio Cloud reimagines the traditional data lake by combining the best of traditional data warehouses and data lakes into a SQL lakehouse, while removing the limitations of traditional data warehouses resulting from closed data architectures. Dremio Cloud enables high performance SQL workloads directly on cloud storage, eliminating the cost and complexity of copying and moving data.
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While most data lake engines take weeks or months to get into production, a user can be up and running with Dremio Cloud in five minutes. The automatic onboarding option establishes the necessary connection to the user’s AWS account, allowing data consumers to connect via their favorite tools and start querying data instantly. Dremio Cloud users have no software to install, configure or upgrade, and no infrastructure to size, manage, and monitor.
Dremio Cloud is not only easier for data teams, but also for data consumers such as analysts and data scientists. It includes Dremio’s patent-pending query acceleration technologies (C3 and data reflections™), a semantic layer, and native single-sign-on (OAuth 2.0) connectors in Tableau and Power BI. Companies can run production BI workloads directly on their cloud data lake and data scientists can benefit from high-throughput access to result sets via Apache Arrow.
Dremio Cloud was designed for the analytic workloads of all companies, ranging from Fortune 500 enterprises to early-stage startups. Dremio control plane’s cloud-native microservices and service mesh architecture provides limitless query planning capacity, while the data plane’s multi-engine, multi-replica architecture automatically scales elastically based on workload. Resources are scaled on-demand to use only what’s needed. When user demand goes to zero during idle times, customers incur zero Dremio and AWS costs. Additional financial governance capabilities provide visibility, control, and predictability of costs.
“We built Dremio to automatically handle any scale with consistent query performance so companies could achieve data democratization while only paying for what they truly need,” said Tomer Shiran, Dremio’s Founder and Chief Product Officer. “This type of cost-effective and highly performant scaling was a central design tenet of Dremio. We wanted to be sure data teams could achieve superior price-performance and trust the cost transparency of our platform.”
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Dremio was purpose-built to provide the industry’s high levels of security with multiple layers of protection, and is launching its cloud service with Service Organization Control (SOC) 2 compliance. Data is encrypted both at rest and on the wire, with state-of-the-art key management that facilitates secure communication between the clients, control plane, and data plane. Advanced role-based access control (RBAC) allows companies to define privileges on every dataset and object in the system. In addition, companies that use enterprise or social identity providers (e.g., Okta) can leverage their existing user and group definitions in Dremio.
“Dremio serves many of the world’s largest companies, including those in highly regulated industries such as financial services and healthcare,” said Thirumalesh Reddy, Dremio’s Vice President of Engineering & Security. “We assembled a world-class team of cloud security engineers and built security into every aspect of our infrastructure and product.”
Dremio Cloud will be unveiled at Subsurface Live, a two-day virtual conference focused on educating and enabling a growing community of data lake practitioners with expert-led sessions on the latest open source innovations in the cloud data lake ecosystem.
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