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Qubole VS VeloDB

Compare Qubole VS VeloDB and see what are their differences

Qubole logo Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

VeloDB logo VeloDB

Modern Real-Time Data Warehouse
  • Qubole Landing page
    Landing page //
    2023-06-22
  • VeloDB VeloDB
    VeloDB //
    2024-01-10

VeloDB is a modern real-time data warehouse powered by open source Apache Doris for lightning-fast data analytics at scale. It ensures big data ingestion within seconds and outstanding performance in both real-time serving and interactive ad-hoc queries. It is one platform for various analytics workloads, including structured and semi-structured data processing, real-time analytics and batch processing, internal data query and federated queries of external data. It allows elastic scaling for efficient resource management. It can dynamically adjust the computing resources allocated to the workload based on the changing requirements. It supports MySQL protocol and standard SQL for easy integration with other data tools. It also provides open data API to be accessible for various external query engines.

Qubole features and specs

  • Scalability
    Qubole allows seamless scalability, adjusting resources automatically based on workload, which facilitates efficient handling of large data sets and peaks in demand.
  • Multi-cloud Support
    Qubole offers support for multiple cloud providers, including AWS, Azure, and Google Cloud, giving users flexibility and freedom to choose or shift between cloud services.
  • Unified Interface
    The platform provides a unified interface for diverse data processing engines such as Apache Spark, Hadoop, Presto, and Hive, simplifying the management of big data operations.
  • Cost Management
    Qubole includes features for cost management and optimization, such as intelligent spot instance usage, which can reduce operational costs significantly.
  • Data Security
    Qubole offers robust security features, including encryption, access controls, and compliance with various regulations, which assists in maintaining data privacy and protection.
  • Integration Capabilities
    The platform supports integration with many other tools and services, which enables a streamlined pipeline for data extraction, transformation, loading (ETL), and analysis.

Possible disadvantages of Qubole

  • Complex Setup
    For users unfamiliar with big data infrastructure and cloud platforms, the initial setup and configuration of Qubole may present a steep learning curve.
  • Cost Overruns
    Without careful management and monitoring, the automatic scaling and utilization of cloud resources can lead to unexpected and potentially high costs.
  • Dependency on Cloud Availability
    As a cloud-based platform, Qubole's performance and availability are contingent on the underlying cloud provider, which means service disruptions or performance issues in the cloud can affect Quboleโ€™s operations.
  • Vendor Lock-in
    While Qubole supports multiple clouds, migrating away from the platform to another big data solution can be complex due to dependency on Qubole-specific configurations and optimizations.
  • Support and Documentation
    Some users have reported that the quality and depth of support and documentation provided by Qubole can vary, which may affect troubleshooting and learning.
  • User Interface
    While the interface is comprehensive, some users may find it less intuitive compared to other platforms, which can hinder ease of use and efficiency.

VeloDB features and specs

No features have been listed yet.

Analysis of Qubole

Overall verdict

  • Qubole is generally considered a good platform for managing big data workloads, especially for businesses that seek flexibility and efficiency in processing and analyzing large-scale datasets. Its ability to automate and optimize workflows can lead to significant productivity gains and cost savings.

Why this product is good

  • Qubole is a cloud-based data platform that is designed to simplify and optimize big data processing. It allows data teams to manage and analyze large datasets efficiently by providing a unified interface for various data processing engines, including Apache Spark, Hive, and Presto. Its scalability, ease of integration with multiple cloud providers, automated data workflows, and support for machine learning models make it a valuable tool for organizations handling extensive data operations.

Recommended for

  • Data engineers and data scientists who need a robust platform for processing large volumes of data.
  • Organizations looking to leverage cloud-based solutions for big data processing and analytics.
  • Companies that want to integrate multiple data processing engines under a single management platform.
  • Businesses that require flexibility in scaling their data infrastructure in response to changing workloads.

Qubole videos

Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos:

  • Review - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • Review - Democratizing Data with Qubole

VeloDB videos

No VeloDB videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Qubole and VeloDB)
Data Dashboard
100 100%
0% 0
Databases
0 0%
100% 100
Big Data
100 100%
0% 0
Relational Databases
0 0%
100% 100

User comments

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What are some alternatives?

When comparing Qubole and VeloDB, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

Presto - Next generation front-of-house technology