SaaS Data Lakes with Cloudera on AWS or Microsoft Azure

Solutions Gallery > Big Data as a Managed Service - Cazena
Solution overview
Cazena is the First SaaS Data Lake with Cloudera on AWS and Microsoft Azure. Cazena’s private SaaS Data Lakes support all analytics, at half the cost of alternatives, with no admin or DevOps required. SaaS Data Lakes accelerate outcomes by 10x for analytics, BI, data science/ML and data engineering.
SaaS Data Lakes from Cazena embed best-of-breed technologies from Cloudera, AWS, Microsoft Azure, RStudio and others. Each SaaS Data Lake is private and single-tenant, delivered ready for data ingest, storage and analytics.
Cazena’s SaaS Data Lakes includes everything: cloud, storage (AWS/Azure), Cloudera PaaS (EDH, CDP, etc.), built-in analytics tools (Hue, CDSW, RStudio, Python...), security, support and production operations. All DevOps, SecOps, upgrades, patching and performance/SLA optimization are included. SaaS Data Lakes are encrypted, monitored and compliance-certified so teams can access data quickly, with complete trust. In 2018, Cazena managed over one million workloads per month for enterprises in highly-regulated industries across the globe.
Benefits of a SaaS Data Lake
Success guaranteed at half the cost. Cazena guarantees a production-ready data lake with Cloudera deployed in less than four weeks, at half the cost of alternatives. Risk-free pilots let teams experience a SaaS Data Lake firsthand. Using Cazena is proven to deliver successful outcomes, with no risk of delays, manual errors or project failure.
Deliver a cloud data lake now, with the team you have. SaaS Data Lakes need Zero Development for deployment or ongoing operations (upgrades, patching, etc.). They are designed for enterprise requirements and drop in seamlessly to existing architectures. Enterprises can expand Cloudera to the cloud to quickly expand access to new and future capabilities -- without adding staff or taking on a major DevOps effort.
Empower all analytics and self-service. SaaS Data Lakes support all analytics (R, Python, Scala, SQL), and with built-in “workload intelligence” to deliver the best price:performance. Cazena includes built-in tools (Hue, CDSW), and makes it easy to plug-in 3rd party ML, BI, or data engineering tools for rapid self-service. A private Cazena AppCloud accelerates testing and deployment of any data and analytics tools.
Reduce risk. SaaS Data Lakes have built-in automation, the highest-grade security and 24x7 operations. Enterprises do not need new DevOps or SecOps expertise for ongoing management. Cazena is enterprise-ready and includes critical security functions such as vulnerability assessment and automatic remediation.
How SaaS Data Lakes are Used
Enterprise customers rely on Cazena for a wide variety of analytics, BI, data science, ML and data engineering use cases. Cazena’s SaaS Data Lakes accelerate new deployments, cloud migrations and expansions to AWS and Azure. Cazena customers are regularly recognized for their impressive results. Insurance innovator FairVentures was selected for as the winner of the Cloudera Data Impact Award for Cloud Success.
SaaS Data Lakes also power a growing variety of analytics applications developed by customers and partners. The ‘Powered by Cazena’ program helps SIs and analytics specialist deliver their solutions “as a service” on a Cazena SaaS Data Lake.
Start Now
Get started quickly with a risk-free, hands-on pilot of a Cazena SaaS Data Lake. Visit us online at cazena.com or email info@cazena.com to learn more.
Additional Resources
Subscribe via AWS Marketplace to the SaaS Data Lake with Cloudera on AWS – Starter Edition. Get instant access to a small Cloudera cluster on AWS, delivered ready for secure data ingest and analytics.
Key highlights
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Modernize architecture
About Cazena
Cazena makes it easy to get started with data processing in the cloud in just a few clicks, automating an otherwise long and difficult process. The service bundles high-performance compute, storage, data movers and a variety of tools in one analytic platform.