What is Google Cloud BigQuery?

BigQuery serves as a serverless, multicloud data warehouse that simplifies the handling of diverse data types, allowing businesses to quickly extract significant insights. As an integral part of Google’s data cloud, it facilitates seamless data integration, cost-effective and secure scaling of analytics capabilities, and features built-in business intelligence for disseminating comprehensive data insights. With an easy-to-use SQL interface, it also supports the training and deployment of machine learning models, promoting data-driven decision-making throughout organizations. Its strong performance capabilities ensure that enterprises can manage escalating data volumes with ease, adapting to the demands of expanding businesses.

Furthermore, Gemini within BigQuery introduces AI-driven tools that bolster collaboration and enhance productivity, offering features like code recommendations, visual data preparation, and smart suggestions designed to boost efficiency and reduce expenses. The platform provides a unified environment that includes SQL, a notebook, and a natural language-based canvas interface, making it accessible to data professionals across various skill sets. This integrated workspace not only streamlines the entire analytics process but also empowers teams to accelerate their workflows and improve overall effectiveness. Consequently, organizations can leverage these advanced tools to stay competitive in an ever-evolving data landscape.

Pricing

Price Starts At:
Free ($300 in free credits)
Price Overview:
Store 10 GiB of data and run up to 1 TiB of queries for free per month. New customers also get $300 in free credits to try BigQuery and other Google Cloud products.

No automatic charges. You only start paying if you decide to activate a full, pay-as-you-go account or choose to prepay. You’ll keep any remaining free credit.
Free Version:
Free Version available.
Free Trial Offered?:
Yes

Screenshots and Video

Company Facts

Company Name:
Google
Date Founded:
1998
Company Location:
United States
Company Website:
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Product Details

Deployment
SaaS
Training Options
Documentation Hub
Video Library
Support
24 Hour Support
Web-Based Support

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

Google Cloud BigQuery Categories and Features

XML Databases

BigQuery offers robust support for a diverse array of data formats, including XML, which makes it an excellent choice for organizations that handle XML in conjunction with other structured and semi-structured data types. The platform’s adaptability empowers users to efficiently load, query, and manipulate XML data, allowing businesses to seamlessly integrate it with various data formats for thorough analysis. With its powerful query engine, BigQuery ensures rapid processing of XML data, even when dealing with substantial datasets. New users can take advantage of $300 in free credits to explore BigQuery’s XML functionalities, providing an opportunity to assess how well the platform manages XML in combination with other formats. This functionality positions BigQuery as a highly versatile solution for a wide range of data processing requirements.

Query Engines

BigQuery boasts an exceptionally efficient query engine capable of executing large-scale queries on extensive datasets with impressive speed. Its serverless model empowers organizations to carry out high-performance queries without the burden of maintaining infrastructure or servers. The SQL-based query interface is user-friendly for most data analysts, facilitating a smooth entry into intricate data analysis tasks. New users can take advantage of $300 in complimentary credits to explore the capabilities of the query engine, allowing them to execute a range of queries and evaluate how BigQuery meets their analytical requirements. Additionally, the platform is built for scalability, ensuring that query performance stays reliable as data volumes increase.

Predictive Analytics Software

BigQuery serves as an advanced solution for predictive analytics, allowing organizations to utilize past data to anticipate future patterns and actions. By seamlessly connecting with machine learning solutions such as BigQuery ML, users can create and implement predictive models right within the platform. Thanks to its robust performance and scalability, BigQuery facilitates rapid analysis of extensive datasets, empowering businesses to derive actionable insights for informed decision-making. New users can benefit from $300 in complimentary credits to delve into BigQuery’s predictive analytics features and develop tailored models that offer significant forecasts. This capability is crucial for companies aiming to enhance their strategic initiatives and secure a competitive advantage.

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

Platform as a Service (PaaS) Provider

BigQuery operates as a Platform as a Service (PaaS), offering a fully managed solution for executing SQL queries on large datasets without the complexities of server management or infrastructure setup. This approach allows organizations to enhance their data analysis capabilities seamlessly, eliminating the need for hardware investments or maintenance efforts. Its serverless architecture enables users to concentrate on analytics, free from concerns about the infrastructure that supports it. New users can take advantage of $300 in complimentary credits to explore the features of BigQuery's PaaS, providing them with a firsthand experience of serverless technology and efficient data analysis. The platform’s capacity to adapt to varying business requirements positions it as an ideal option for fast-paced environments.

OLAP Databases

BigQuery is specifically designed for Online Analytical Processing (OLAP), enabling rapid data querying and analysis on complex, multidimensional datasets. This platform empowers organizations to execute intricate analytical queries on extensive datasets, facilitating thorough analysis across multiple business facets. With its automatic scaling capability, BigQuery efficiently manages even the most demanding OLAP workloads. New users can benefit from $300 in complimentary credits to experience firsthand how BigQuery can optimize OLAP functions, enhancing both the speed and precision of their business intelligence efforts. Additionally, its serverless design allows organizations to concentrate on their data without the burden of infrastructure management.

Marketing Analytics Software

BigQuery serves as a robust platform for conducting marketing analytics, allowing organizations to scrutinize customer interactions, evaluate campaign effectiveness, and track market developments in real-time. Its capability to handle large volumes of data swiftly, combined with seamless integration with various marketing tools, positions it as an essential asset for marketers aiming to refine their approaches. Through BigQuery, marketers can utilize data to acquire enhanced understanding of customer inclinations and market trends. New users are offered $300 in complimentary credits to delve into BigQuery’s marketing analytics functionalities, aiding them in making informed, data-driven choices that elevate the success of their campaigns. The platform also facilitates immediate data analysis, providing prompt insights into active marketing initiatives.

A/B Testing
Campaign Management
Channel Attribution
Customer Journey Mapping
Dashboard
Performance Metrics
Predictive Analytics
ROI Tracking
Social Media Metrics
Website Analytics

Machine Learning Software

BigQuery provides robust machine learning functionalities through BigQuery ML, empowering users to create, train, and deploy machine learning models right within the platform. This integration simplifies the process for organizations, eliminating the need to navigate through various tools or environments. BigQuery ML works smoothly with SQL, allowing data analysts and scientists to utilize machine learning models with tools they already know. New users can take advantage of $300 in free credits to explore BigQuery’s machine learning capabilities, enabling them to harness AI for predictive analytics and informed decision-making. The platform accommodates a wide range of machine learning algorithms, making it a flexible solution for diverse applications.

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

ETL Software

BigQuery serves as a powerful solution for executing Extract, Transform, Load (ETL) operations, allowing organizations to automate the processes of data collection, modification, and preparation for analysis. Users can leverage SQL queries to convert unrefined data into structured formats while integrating with a variety of ETL tools to enhance their workflows. The platform is designed for scalability, ensuring that even extensive datasets can be managed without issues during ETL tasks. Newcomers can benefit from $300 in complimentary credits to explore the ETL functionalities of BigQuery and witness the smooth handling of data for analytical purposes. With its robust query engine, BigQuery guarantees quick and efficient ETL processes, no matter the volume of data involved.

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Database as a Service (DBaaS) Provider

BigQuery presents a Database as a Service (DBaaS) solution that delivers comprehensive management of data storage, query processing, and infrastructure, freeing users from the burden of server or hardware management. This serverless environment is engineered for scalability, enabling businesses to efficiently manage extensive datasets without concerns over capacity or performance limitations. With its user-friendly interface and adaptability, BigQuery stands out as a top choice for organizations in search of a DBaaS offering. New users are granted $300 in complimentary credits, providing an opportunity to delve into BigQuery's functionalities and experience its DBaaS features without initial financial commitments. This model significantly reduces the need for database administration, allowing teams to concentrate on data analysis rather than system upkeep.

Database Software

BigQuery is a highly adaptable and robust database solution designed to efficiently manage both structured and semi-structured data at large volumes, making it ideal for diverse applications. It utilizes standard SQL for querying, which facilitates seamless integration with current workflows and tools. Being a fully managed service, it alleviates the burdens of database maintenance, allowing organizations to concentrate on gaining insights instead of dealing with infrastructure management. New users can take advantage of $300 in complimentary credits to explore BigQuery’s functionalities, giving them the opportunity to experiment with both operational and analytical queries to assess its effectiveness for their data storage and access requirements. Additionally, BigQuery is equipped with strong security measures, ensuring the protection of sensitive information, even when dealing with large datasets.

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Data Warehouse Software

BigQuery is a comprehensive data warehousing solution designed for businesses to securely store and analyze substantial amounts of data in a scalable framework. Its serverless design removes the complexities of managing infrastructure, allowing users to concentrate on data insights rather than system upkeep. The platform boasts an exceptionally powerful query engine that delivers rapid performance, even when handling large datasets, making it suitable for enterprises of any size. New users are welcomed with $300 in complimentary credits, providing them with the chance to explore BigQuery’s capabilities and assess how it can meet their data storage and analytical requirements. The platform's seamless scalability is particularly advantageous for organizations experiencing rapid growth.

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Data Science Software

BigQuery streamlines the data science process by allowing data scientists to efficiently query, analyze, and model extensive datasets. Its compatibility with Google Cloud's machine learning services simplifies the training and deployment of models right within the BigQuery environment. Utilizing SQL and sophisticated analytics tools, data scientists can create predictive models that support teams in making informed decisions based on data. New users receive $300 in complimentary credits to explore the data science features of BigQuery, enhancing their productivity and enabling them to extract significant insights from large datasets. This integration fosters smooth collaboration between data scientists and various business units, boosting overall efficiency.

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Data Preparation Software

BigQuery offers an extensive array of data preparation features designed to assist organizations in cleansing, transforming, and organizing their data for effective analysis. With its integrated SQL functionalities and support for a variety of ETL tools, BigQuery simplifies the process of handling unrefined data and readying it for intricate queries. The platform also allows for data partitioning and clustering, which boosts query efficiency during the preparation stage. By automating numerous repetitive tasks, BigQuery optimizes the data preparation workflow, enabling teams to focus more on analytical tasks. New users can take advantage of $300 in free credits to explore BigQuery’s data preparation capabilities and enhance their data’s readiness for analytical purposes.

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Data Management Software

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Data Engineering Tool

BigQuery serves as a vital resource for data engineers, facilitating the efficient handling of data ingestion, transformation, and analysis. Its scalable architecture and comprehensive set of data engineering capabilities empower users to create data pipelines and automate processes seamlessly. The tool's compatibility with other Google Cloud services enhances its adaptability for various data engineering needs. New users can benefit from $300 in complimentary credits to delve into BigQuery’s functionalities, allowing them to optimize their data workflows for enhanced efficiency and performance. This enables engineers to devote more time to innovation rather than the complexities of infrastructure management.

Data Clean Room Software

BigQuery provides organizations with the ability to establish and oversee data clean rooms, which are secure settings designed for handling sensitive information while adhering to privacy regulations. These clean rooms facilitate collaboration and data analysis among businesses without compromising the confidentiality of private or proprietary data. By implementing rigorous access controls and prioritizing data privacy, BigQuery creates a trustworthy space for conducting data analytics. New users can take advantage of BigQuery's data clean room features by using the $300 in complimentary credits, allowing them to explore how this secure and privacy-centric solution can address their needs for compliant data analysis. This capability is essential for sectors that must navigate strict data privacy laws, including healthcare and finance.

Data Analysis Software

BigQuery provides robust solutions for swiftly and accurately analyzing extensive datasets, empowering organizations to glean meaningful insights from their information. Its ability to handle both structured and semi-structured data makes it adaptable for various analytical needs, ranging from straightforward queries to sophisticated analytics. Whether executing intricate aggregations or conducting time-series analyses, BigQuery's scalable architecture guarantees reliable performance for diverse tasks. New users can take advantage of $300 in complimentary credits to explore the comprehensive range of data analysis tools available, facilitating quicker insights and data-informed decision-making. Additionally, the platform enables real-time analytics, allowing organizations to respond to data fluctuations as they occur.

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Columnar Databases

BigQuery operates as a columnar database, organizing data in columns instead of rows, which greatly accelerates analytic queries. This efficient design minimizes the volume of data that needs to be scanned, leading to improved query performance, particularly with extensive datasets. The column-based storage approach is especially advantageous for executing intricate analytical queries, as it enables more efficient handling of specific columns of data. New users have the opportunity to experience the benefits of BigQuery's columnar architecture with $300 in complimentary credits, allowing them to test how this structure can enhance their data processing and analytical capabilities. Additionally, the columnar format facilitates superior data compression, further boosting storage efficiency and query speed.

Business Intelligence Software

BigQuery serves as a robust business intelligence (BI) platform, allowing users to conduct intricate data queries across extensive datasets. It seamlessly connects with a range of BI tools, granting users the versatility to create insightful dashboards and detailed reports. By harnessing the built-in BI features of Google Cloud, organizations can swiftly make informed, data-driven choices with increased assurance. New users can take advantage of $300 in complimentary credits to explore BigQuery’s capabilities for BI applications and start the process of converting raw data into valuable reports that facilitate decision-making. This empowers businesses to identify trends, evaluate performance metrics, and formulate strategies grounded in real-time data insights.

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Big Data Software

BigQuery is engineered for the management and analysis of large-scale data, positioning it as an optimal solution for enterprises dealing with extensive datasets. Whether you’re working with gigabytes or petabytes of information, BigQuery offers automatic scaling and high-performance query execution, ensuring exceptional efficiency. This platform enables organizations to conduct data analysis at remarkable speeds, allowing them to maintain a competitive edge in rapidly evolving sectors. New users can take advantage of $300 in complimentary credits to test out BigQuery's extensive data processing features, gaining hands-on experience with large data management and analysis. Its serverless design removes the hassle of scaling concerns, simplifying the task of handling big data significantly.

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

AI Data Analytics Tool

Google Cloud BigQuery effortlessly connects with artificial intelligence and machine learning technologies to enable data analysis on extensive datasets. It provides sophisticated features for creating and executing machine learning models right within the platform, allowing users to utilize Google’s AI capabilities to their fullest potential. This functionality empowers organizations to utilize their data for predictive analysis, fostering more informed decision-making. New users are welcomed with $300 in complimentary credits, allowing them to investigate BigQuery's AI-enhanced functionalities without initial investment. This enables them to experiment with machine learning models and data analysis freely. Such integration establishes BigQuery as a formidable asset for companies aiming to leverage AI for innovative and data-driven advancements.

More Google Cloud BigQuery Categories

Serverless Databases

BigQuery operates as a completely serverless database, eliminating the need for users to manage hardware or plan for capacity. Its architecture automatically adjusts to accommodate any workload, guaranteeing consistent performance no matter the data volume. This optimization enables organizations to concentrate on data analysis instead of server maintenance or provisioning. New users can explore BigQuery's serverless capabilities with $300 in complimentary credits, giving them the chance to experience the advantages of a serverless database directly. This model allows users to leverage the comprehensive capabilities of BigQuery without the burdens of conventional operational management.

Google Cloud BigQuery Customer Reviews

Write a Review
  • Reviewer Name: Sakshi S.
    Position: Inside sales representative
    Has used product for: 6-12 Months
    Uses the product: Daily
    Org Size (# of Employees): 100 - 499
    Feature Set
    Layout
    Ease Of Use
    Cost
    Customer Service
    Would you Recommend to Others?
    1 2 3 4 5 6 7 8 9 10

    An Amazing cloud data warehouse

    Date: Feb 04 2024
    Summary

    Google BigQuery offers a unique scalable & cost effective cloud data warehouse optimized for big data. Excellent complement if you have large analytics workloads on GCP

    Positive

    It scales to handle massive datasets with petabyte scale query processing. Fast performance with results in seconds regardless of data size. Intuitive SQL interface familiar for analysts.

    Negative

    Being Serverless, lacks ability to persist data long term. Limited user level security, access control & governance features. Not ideal for small datasets or repetitive queries.

    Read More...
  • Reviewer Name: A Verified Reviewer
    Position: Engineering Lead
    Has used product for: Less than 6 months
    Uses the product: Daily
    Org Size (# of Employees): 26 - 99
    Feature Set
    Layout
    Ease Of Use
    Cost
    Customer Service
    Would you Recommend to Others?
    1 2 3 4 5 6 7 8 9 10

    BigQuery Review

    Date: Jan 23 2024
    Summary

    Overall, BigQuery is an exceptional tool in the realm of big data analytics. Its remarkable processing speed, scalability, and user-friendly nature make it an invaluable asset for businesses seeking to derive actionable insights from their data. The aspects that could be seen as limitations are, in many ways, opportunities for developing efficient data practices and deeper understanding of data analytics. For any organization in need of a powerful, scalable, and efficient data warehouse solution, BigQuery undoubtedly merits a five-star rating.

    Positive

    BigQuery, as Google's fully-managed, serverless data warehouse, has been a standout solution in the world of large-scale data analysis. Its most striking feature is the impressive speed with which it processes vast datasets. Leveraging the power of Google's advanced cloud infrastructure, BigQuery offers near real-time execution of complex SQL queries, a boon for businesses and analysts dealing with big data. The scalability of BigQuery is another significant advantage. It adeptly adjusts to varying data volumes without necessitating active management of the underlying infrastructure. This feature is particularly valuable for businesses experiencing variable data loads. Additionally, its user-friendly interface, coupled with seamless integration with other Google Cloud services, simplifies the data management process, making it accessible to a wide range of users.

    Negative

    While BigQuery is a robust platform, it comes with a few considerations that require attention. The pricing model, which is based on the volume of data processed, necessitates careful query planning to avoid unforeseen expenses. This aspect, however, also encourages efficient query design, which is a good practice in data management. While there is a learning curve, particularly for its more advanced features, the initial investment in learning pays off in terms of the powerful capabilities it unlocks. As for reliance on a single cloud provider, while this might be a consideration for some, Google's extensive support and the platform's integration capabilities often make this a non-issue for most users.

    Read More...
  • Reviewer Name: Anis A.
    Position: Ownership Workflow Coordinator
    Has used product for: 1-2 Years
    Uses the product: Daily
    Org Size (# of Employees): 26 - 99
    Feature Set
    Layout
    Ease Of Use
    Cost
    Customer Service
    Would you Recommend to Others?
    1 2 3 4 5 6 7 8 9 10

    Ideal for Scalable and Cost-Effective Data Analytics

    Updated: Jan 22 2024
    Summary

    For businesses of all sizes, Google Cloud BigQuery provides a robust and scalable data analytics solution. It is the perfect option for contemporary data analytics because of its serverless design, SQL-like query language, real-time capabilities, and interaction with the Google Cloud ecosystem.

    Positive

    A very scalable serverless data warehouse is Google Cloud BigQuery. Large datasets are handled by it automatically, guaranteeing excellent performance without the need for user involvement.

    Negative

    While the basics are user-friendly, optimizing queries for optimal efficiency may involve a learning curve. To improve their inquiries and cut expenses, users would need to spend some time learning best practices.

    Read More...
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