Google Cloud BigQuery
4.4
471

Not Claimed

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly.
Developer
Google
HQ Location
Mountain View, CA
Year Founded
1998
Number of Employees
326,563
Twitter
Strengths
  • Scalability

    Ability to handle large amounts of data

  • Integration

    Seamless integration with other Google Cloud services

  • Real-time analysis

    Ability to analyze data in real-time

Weaknesses
  • Pricing

    Can be expensive for small businesses

  • Complexity

    Can be difficult to set up and use for non-technical users

  • Limited support

    Limited support for non-Google Cloud platforms

Opportunities
  • Growing demand for big data analytics solutions
  • Potential for new features and integrations to be added
  • Opportunities for partnerships with other SaaS providers
Threats
  • Competition from other big data analytics providers
  • Increased scrutiny on data privacy and security
  • Potential for new regulations to impact the use of big data analytics

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Review Distribution

  • 👍
    High - rated users

    BQ was incredibly easy to set up and get going. As a beginner, the public data sets available also make practice very easy. There are a great many other softwires available in the Google Cloud that connect directly to BQ, so the whole system is set up to expand its usefulness without needing to buy more software.I haven't run into anything about this software that I haven't liked so far. I have nothing negative to report.

  • 🤔
    Average - rated users

    Our salesforce campaigns relies heavily on data warehouse, which is the backbone of everything we do. This data set contains both row data sets and BigQuery is used to aggregate this sets by running schedule queries on it.This platform requires strong SQL skills. Huge dependency on tech team to fix queries sometime.

  • 👎
    Low - rated users

    BigQuery is highly scalable. Has great integration with GCP. BigQueryML brings much needed ML to your data without external tools. Handles very high volume of data. Pricing is pay as you go or fixed if usage is very high.It can be expensive if BigQuery is used frequently when not using fixed slots. UI has changed significantly, but it still feels a bit off at times. A heavy user of BigQuery will run into many quotas and limits sooner rather than later, and Quotas need to be increased. Some are fixed, and there are no workarounds.

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Google Cloud BigQuery Plan

Google Cloud BigQuery offers a pay-as-you-go pricing model with free and enterprise versions, charging for storage and data processing.
Free $ Free
New customers get $300 in free Google Cloud credits to spend on BigQuery with free trial sign-up. 10 GB storage Up to 1 TB queries
Standard $ 0
$0.04 - Per Slot Hour Low-cost option for standard SQL analysis Capped at 1,600 slots per reservation Max 5 reservations per admin 99.9% SLA Zonal High Availability Google Cloud Platform wide certifications (Foundational compliance). All Google Cloud Platform wide certifications including ISO 9001, ISO 27001, SOC 1 -3, PCI HIPAA compliance Google managed encryption keys Autoscaling slots Google managed encryption keys
Enterprise Plus $ 0
$0.10 - Per Slot Hour Supports mission-critical enterprise analytics Customer-managed encryption keys Support for FedRAMP, ITAR and other compliance regimes available through Assured Workloads Regional-level disaster recovery (roadmap functionality)
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