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Qubole Analysis

What is Qubole?

Open data lake platform for analytics and machine learning

Location
469 El Camino Real Ste 205, Santa Clara, California 95050, United States
Employees
201-500
Founded
2011
Companies Using Product
Expedia (https://www.expedia.com/) Merkle (https://www.merkleinc.com/) Acxiom (https://www.acxiom.com/)
Customer Satisfaction
4.0
Deployment Type
Cloud
Implementation Complexity
Complex
Initial Price
$0.168 (Enterprise Edition), $0.24 (On-Demand)

Product Features & Capabilities

  • Open data lake platform for machine learning
  • Streaming analytics for real-time insights
  • Ad-hoc analytics for faster decision-making
  • Data engineering tools for scalable pipelines
  • Cloud-native architecture supporting AWS and GCP.

Other Considerations

Raised significant funding to support growth; Serves a diverse range of industries; Offers a free trial for new users.

Ongoing Support Cost

$0.168 per QCU per hour (Enterprise Edition), $0.24 per QCU per hour (On-Demand), $108 per user per month (On-Demand)

Key Disadvantages

  • Fewer ETL tools compared to competitors.
  • Cluster management issues reported by users.

Market Position

Qubole positions itself as a leader in the data lake and analytics industry by offering a cost-efficient, open, and secure platform that integrates various data engines for machine learning, streaming, and ad-hoc analytics. The company emphasizes its ability to reduce cloud data lake costs by over 50%, making it an attractive option for organizations looking to optimize their data operations. Qubole's platform supports multiple cloud environments, including AWS and Google Cloud, which helps avoid vendor lock-in and caters to a diverse range of users, including data analysts, engineers, and scientists.

The platform is designed to handle unpredictable big data workloads with features like workload-aware autoscaling and real-time spot buying, enhancing its appeal in a competitive market. Additionally, Qubole's focus on providing a unified data environment that integrates with traditional data warehouses and NoSQL databases further strengthens its market positioning as a comprehensive solution for organizations aiming to leverage big data effectively.

Key Advantages

  • Achieve 50% cost savings with built-in TCO optimizations.
  • Accelerate continuous data engineering on a single platform.
  • Offers a choice of cloud and data processing engines (Apache Spark, Presto, Hive).
  • Provides 10 times higher administrative efficiency and 50% lower cloud costs.
  • Supports end-to-end feature engineering for data scientists and efficient data pipeline management for data engineers.
  • Self-service platform designed for multiple workloads, enabling 3 times faster time to value and 10 times more users per administrator.
  • Scalability for unlimited data analysis, processing, and storage.
  • High-performance with virtually infinite resources from cloud providers.
  • Built-in security leveraging cloud provider expertise.
  • Cost efficiencies with pay-as-you-go compute and automation technologies for reduced operational costs.
  • Self-service analytics for discovery, ad hoc querying, visualization, and collaboration.

HQ Full Address

469 El Camino Real Ste 205, Santa Clara, California 95050, United States

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