Google Cloud BigQuery

Google Cloud BigQuery

Serverless and Multi-cloud Data Warehouse

About Google Cloud BigQuery

BigQuery is a serverless and multi-cloud data warehouse designed to help users turn big data into valuable business insights. Users can query structured data without the need to store it or load it into their own systems first. BigQuery provides advanced features such as nested, repeated and compressed columnar data storage.


Key benefits of Google Cloud BigQuery

Built-in machine learning: BigQuery ML enables data scientists and data analysts to build and operationalize ML models on planet-scale structured, semi-structured, and now unstructured data directly inside BigQuery, using simple SQL—in a fraction of the time. Export BigQuery ML models for online prediction into Vertex AI or your own serving layer. Learn more about the models we currently support.

Analyze and share data across clouds: BigQuery Omni is a fully managed, multicloud analytics solution that allows for cost-effective and secure data analysis across clouds and shares results within a single pane of glass. Within BigQuery Analytics Hub, securely exchange data assets internally and across organizations without data movement and enhance analysis with commercial, public, and Google datasets.

Real-time analytics with built-in query acceleration: BigQuery has built-in capabilities that ingest streaming data and make it immediately available to query, along with native integrations to streaming products like Dataflow. Analyze large datasets interactively with BigQuery BI Engine, an in-memory analysis service that offers sub-second query response time and high concurrency. BI Engine natively integrates with Looker Studio and works with many BI tools, including Connected Sheets.

Unify, manage, and govern all types of data: Query all data types with BigQuery: structured, semi-structured and unstructured. Use BigLake to explore and unify different data types and build advanced models. Centrally discover, manage, monitor, and govern data across data lakes, data warehouses, and data marts with consistent controls with Dataplex, an intelligent data fabric that enables organizations to provide access to trusted data.

Geospatial analysis with BigQuery: BigQuery geospatial uniquely combines the serverless architecture of BigQuery with native support for geospatial analysis, so you can augment your analytics workflows with location intelligence. Simplify your analyses, see spatial data in fresh ways, and unlock entirely new lines of business with support for arbitrary points, lines, polygons, and multi-polygons in common geospatial data formats.

Spreadsheet interface: Connected Sheets allows users to analyze billions of rows of live BigQuery data in Google Sheets without requiring SQL knowledge. Users can apply familiar tools—like pivot tables, charts, and formulas—to easily derive insights from big data. Learn more about Connected Sheets in the getting started guide.

Real-time change data capture and replication: Synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency with Datastream. Datastream integrates with purpose-built and extensible Dataflow templates to pull change streams written to Cloud Storage, and create up-to-date replicated tables in BigQuery for real-time analytics.

Standard SQL: BigQuery supports a standard SQL dialect that is ANSI:2011 compliant, which reduces the need for code rewrites. BigQuery also provides ODBC and JDBC drivers at no cost to ensure your current applications can interact with its powerful engine.

Materialized Views: Accelerate query performance and reduce costs within your environment with BigQuery materialized views. It is easy to set up, effortless to use, and best of all it's real time, allowing you to quickly get answers to your questions.

Petabyte scale: Get great performance on your data, while knowing you can scale seamlessly to store and analyze petabytes to exabytes of data with ease.

Data governance and security: BigQuery's integration with security and privacy services from Google Cloud provides strong security and fine-grained governance controls, down to the column-level and row-level. Rest assured knowing your data is encrypted at rest and in transit by default.

Public datasets: Google Cloud Public Datasets offer a powerful data repository of more than 200 high-demand public datasets from different industries.


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Reviews

Overall rating

4,7 /5
(23)
Value for Money
4,4/5
Features
4,7/5
Ease of Use
4,3/5
Customer Support
3,8/5

Already have Google Cloud BigQuery?

Software buyers need your help! Product reviews help the rest of us make great decisions.

Showing 5 reviews of 23
Andres Ernesto
Andres Ernesto
Overall rating
  • Industry: Computer Software
  • Company size: 10 000+ Employees
  • Used Daily for 2+ years
  • Review Source

Overall rating

  • Value for Money
  • Ease of Use
  • Customer Support
  • Likelihood to recommend 10.0 /10

Good tool

Reviewed on 2023/11/11

I use this tool daily and it meets my expectations, easy to create jobs in the form of scheduled...

I use this tool daily and it meets my expectations, easy to create jobs in the form of scheduled queries, easy import of data from Google Sheets, integration with Google GAS and many other advantages that I have discovered

Pros

importing information from Google Sheets seems like a super advantage to me, as does the ability to execute large queries without affecting performance.

Cons

I have no complaints about the tool so far

Verified Reviewer
Overall rating
  • Industry: Logistics & Supply Chain
  • Company size: 201–500 Employees
  • Used Weekly for 2+ years
  • Review Source

Overall rating

  • Value for Money
  • Ease of Use
  • Likelihood to recommend 7.0 /10

Great serverless cloud data warehouse

Reviewed on 2022/06/20

We used BigQuery to analyze firebase events data from our mobile apps. Considering the sheer volume...

We used BigQuery to analyze firebase events data from our mobile apps. Considering the sheer volume of this dataset, querying has been mostly very fast and reliable, albeit at a high cost.

Pros

I like the serverless nature of BigQuery. It takes away most of the maintenance costs involved in maintaining and fine-tuning a data warehouse.

Cons

I didn't really like the on-demand pricing of BigQuery. Monthly costs tend to blow up excessively. I think they have a different pricing option now to resolve this though.

Alternatives Considered

Snowflake

Reasons for Switching to Google Cloud BigQuery

BigQuery has a native integration with Firebase.
Chhaya
Chhaya
Overall rating
  • Industry: Food & Beverages
  • Company size: 201–500 Employees
  • Used Weekly for 1+ year
  • Review Source

Overall rating

  • Ease of Use
  • Customer Support
  • Likelihood to recommend 8.0 /10

Get started with BigQuery, A powerful tool for analysing Big data

Reviewed on 2022/09/18

Pros

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.

Cons

This platform requires strong SQL skills. Huge dependency on tech team to fix queries sometime.

Rishikumar
Overall rating
  • Industry: Computer Software
  • Company size: Self Employed
  • Used Daily for 6-12 months
  • Review Source

Overall rating

  • Value for Money
  • Ease of Use
  • Customer Support
  • Likelihood to recommend 10.0 /10

"Google Cloud BigQuery: The Ultimate Solution for Big Data Management and Analysis"

Reviewed on 2023/01/19

My experience using Google Cloud BigQuery has been very good. It is a strong software for data...

My experience using Google Cloud BigQuery has been very good. It is a strong software for data warehousing and analytics, capable of handling large datasets efficiently. Navigation and execution of queries are fast and user-friendly. The pay-per-use pricing model is cost-effective and it offers robust features such as high performance, flexibility, and security. It is an ideal choice for companies that want to extract valuable insights from big data.

Pros

Google Cloud BigQuery is a powerful and user-friendly software for data warehousing and analytics. It can easily handle extremely large datasets, making it perfect for businesses that process and analyze massive amounts of data. The queries are executed quickly, even on large datasets, allowing for efficient data analysis and insights. The user interface is intuitive and easy to navigate, making it accessible for users of all skill levels. It integrates seamlessly with other Google Cloud products, such as Google Analytics and Google Cloud Storage, which allows for a streamlined workflow. The pricing is pay-per-use and the cost is generally lower for larger amounts of data, which makes it cost-effective. Additionally, it offers high performance, flexibility, and strong security features.

Cons

Google Cloud BigQuery is a great tool for data warehousing and analytics. One thing to keep in mind is that it can have a steep learning curve for those who are not familiar with SQL and data warehousing concepts. Additionally, it may not be as customizable as some other data warehousing and analytics tools. But overall, it offers a wide range of functionalities and a user-friendly interface, making it a great option for many use cases. I've found it to be a reliable and efficient tool for processing and analyzing large datasets.

John
Overall rating
  • Industry: Music
  • Company size: 11–50 Employees
  • Used Daily for 2+ years
  • Review Source

Overall rating

  • Value for Money
  • Ease of Use
  • Customer Support
  • Likelihood to recommend 9.0 /10

Superb, Scalable Technology

Reviewed on 2023/06/08

I really love BigQuery especially insofar as it fits within a GCP environment. It is incredibly...

I really love BigQuery especially insofar as it fits within a GCP environment. It is incredibly powerful and, given some governance, not very expensive at all. I find it cheaper and slightly easier to manage than Snowflake, though both products are incredible to use.

Pros

BigQuery is powerful, easy to set up and use, and wonderfully transparent about costs. I also prefer its mechanisms for dataset partitioning over, e.g., Snowflake's.

Cons

The BigQuery UI is not great. Saved queries are messy, and scheduled queries are very difficult to maintain (to the point that they probably should not be used at all).

Alternatives Considered

Snowflake

Reasons for Switching to Google Cloud BigQuery

It made more sense within a GCP environment.
Showing 5 reviews of 23 Read all reviews

Google Cloud BigQuery FAQs

Below are some frequently asked questions for Google Cloud BigQuery.

Google Cloud BigQuery offers the following pricing plans:

  • Starting from: US$2 000,00/month
  • Pricing model: Free Version, Subscription
  • Free Trial: Available

Free Trial: New customers get $300 in free credits to spend on BigQuery during the first 90 days. Free Usage per Month: All customers get 10 GB storage and up to 1 TB queries free per month, not charged against their credits. General Pricing: BigQuery charges for data storage, streaming inserts, and querying data, but loading and exporting data are free of charge. • Storage: $0.02 per GB, per month and $0.01 per GB, per month for long-term storage • Streaming inserts: $0.01 per 200 MB

Google Cloud BigQuery has the following typical customers:

Self Employed, 2–10, 11–50, 51–200, 201–500, 501–1 000, 1 001–5 000

Google Cloud BigQuery supports the following languages:

Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Spanish

Google Cloud BigQuery supports the following devices:

Google Cloud BigQuery integrates with the following applications:

Google Ads, Google Analytics 360, Google Campaign Manager 360, Google Cloud Bigtable, Google Cloud Compute Engine, Google Data Studio, Looker, Vertex AI

Google Cloud BigQuery offers the following support options:

Email/Help Desk, FAQs/Forum, Knowledge Base, Phone Support, Chat

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