Simple, Streamlined,
& Cost-Effective
Track spending, justify business plans, and optimize your data lake costs with one easy-to-use tool.
APRIL 24 WEBINAR:
CRUSH YOUR DATA COSTS WITH COST EXPLORER
Save 42% on data lake costs on Qubole
Monitored, Managed & Cost-Controlled
Unleash Performance
Anticipating the evolution of big data, Qubole is committed to scaling, cloud adaptability, & supporting the continuous growth of ML models through trusted platforms like Spark 3.3.
Use Our Explorer to Optimize Spend Instead
Do you feel like you're constantly balancing cost savings with performance? Now you don't have to.
Qubole Cost Explorer provides granular visibility of workloads at the job, cluster, and cluster instance levels so you can optimize your costs AND performance.
Maximize Efficiency, Minimize Costs
Budget and forecast future spend based on past job/user level costs and cluster-level metrics.
An open and secure multi-cloud data lake platform for machine learning, streaming analytics, data exploration and ad-hoc analytics.
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Get Granular Visibility for Strategic Decisions
Optimize TCO on the overall portfolio by exploring resources with the highest and lowest spends.
Automate
and Innovate
Calculate dollar spend at the granular level of each big data workload for project or portfolio ROI
Sticking Your Head in the Sand?
* Source: Qubole's Business Value Engineering Team Research, comparisons against Databricks & AWS EMR.
Defy Gravity with AWS Graviton
Simple, Streamlined,
& Cost-Effective
QUBOLE’S DATA LAKE COST EXPLORER
All the Features. Half the Costs.
Pick solutions with your cost constraints in mind: AWS Graviton processors are designed to deliver you the most efficient cloud performance for your money, offering up to 3x the savings.
Simple & Flexible
Qubole’s open, simple, and secure data lake platform allows for unmatched collaboration across the entire enterprise. Working asynchronously between technical and analytical teams has never been easier.
Complete Cost Transparency Lets You:
Plan & Budget
Budget and forecast future spend based on past job/user level costs and cluster-level metrics.
Optimize Opportunities
Optimize TCO on the overall portfolio by exploring resources with the highest and lowest spends.
Build ROI Analyses
Calculate dollar spend at the granular level of each big data workload for project or portfolio ROI