Companies collect, store and analyze data for various reasons. Analyzing historical and real-time data can yield exciting outcomes that help organizations make informed decisions concerning the sales and growth of their business. Vast volumes of data reveal trends and 

Therefore, there is a growing demand for large data warehouses and supporting software to store, analyze, and meaningfully interpret these treasure troves of information. BigQuery is one of them.

Let’s find out its features and perks in this article.

What is BigQuery?

Google’s BigQuery effortlessly manages extensive data. BigQuery is a cloud-based, serverless, cost-effective, highly scalable, multi-cloud data warehouse with a built-in query engine.

Do You Need BigQuery for Business?

This warehouse analyzes petabytes of data within minutes. BigQuery employs a columnar storage structure and the tree architecture model, allowing faster data scanning, querying, and efficiently aggregating results. All this is possible with almost no investment in managing infrastructure and without building multiple indexes on the database.

Anyone with some knowledge of SQL queries can handle BigQuery, thus eliminating the need to hire database administrators to manage the system. 

The BigQuery database is scalable and can easily accommodate gigantic volumes of data, as needed.  BigQuery saves costs as well, as organizations pay only for what they use.

What are the features of BigQuery?

Google developed BigQuery to overcome certain hurdles that would cost a fortune to enterprises. The vital features of BigQuery as the solution for the data warehousing needs of every organization are as follows. 

1. Speed

BigQuery rapidly queries vast amounts of data in a short time. Terabytes or petabytes of data are no challenge for the highly efficient BigQuery engine. 

2. Programming access

BigQuery can be easily accessed in programs using Rest API calls, client libraries such as Java, .Net, Python, the command-line tool, or the GCP console. BigQuery features built-in capabilities for queries and database management. All operations are ACID-compliant and preserve the integrity of the manipulated data in case of a malfunction. 

3. Serverless operation

BigQuery is a serverless data warehouse. Google manages the resource allocation at the back end on cloud resources. BigQuery frees enterprises from worrying about rising infrastructure expenses and helps them stay focused on data operations. Google handles infrastructure security and manages updates and patches. 

4. Built-in ML and AI capabilities

BigQuery features ML and AI capabilities by integrating with specialized tools such as VertexAI and TensorFlow. Organizations can utilize this integration to train and execute models to use structured data. BigQuery makes it simple to query and view data with interactive queries and virtual tables. Also, BigQuery helps manage data easily as it lists the datasets, tables, or projects and provides rich resource information.

5. Real-time analytics

Organizations can quickly upload data using the high-speed streaming insertion API. This API facilitates real-time analysis of data by instantly loading the latest business data. Enterprises can promptly monitor current trends and make rapid business decisions based on analytics.

6. Logical data warehousing

BigQuery allows data from external sources using powerful federated queries. BigQuery’s connection API allows external data sources to fetch resultant data into virtual or temporary tables. Use data from any source you need to make your analysis perfect. 

7. Data security

BigQuery always encrypts data, both on the disk and in transit. Use the cloud Identity and Access Management tool to grant access to only the entities that need to access the data. Google takes care of updates and patches to the infrastructure, ensuring no breach of data from the cloud servers. 

8. Data Transfer Services

BigQuery provides data transfer services (DTS) from external sources to itself on a scheduled or fully managed basis. You can rapidly transfer data from sources such as YouTube, SaaS, Google platform, Google ads, Amazon S3, and Teradata for analysis. Having data from multiple sources merged into a single analytical platform such as BigQuery paves the way for more in-depth data analysis and helps enterprises take well-informed, precise actions for their growth. 

9. Auto backup and restore services

BigQuery provides automatic replication and restoration services for your data. No data is lost while processing. BigQuery also keeps a log of your change history for up to seven days. Enterprises can keep track of changes in the data and quickly restore data in case of any discrepancies. 

10. Spreadsheet Interface

Spreadsheets are a familiar tool in the world of analytics. They are also accessible databases that store enormous quantities of data. Google Suite provides an excellent spreadsheet tool known as Google Sheets. Google Sheets is an online spreadsheet app that allows users to create, store, and manipulate data in real-time while allowing access to multiple users. 

Data integration from Google Sheets to BigQuery is made possible in various ways. Federated queries help in querying data stored on Google Sheets. Organizations can readily save the results of analytics from BigQuery in Google Sheets for further analysis using capabilities such as filtering, pivoting, charting, and formula-based analysis.  

Why should enterprises use BigQuery?

BigQuery’s unique features make it the optimum solution for data warehousing and analytical needs. Here is a subset of benefits that BigQuery offers enterprises:

1. Ease of infrastructure setup

As BigQuery is a cloud-based tool and is serverless, there is no investment or effort required in setting up the infrastructure for your data warehouse. BigQuery provides easy data migration tools, enabling enterprises to migrate data from various external sources rapidly. 

2. Ease of use

BigQuery has many built-in features that make work easy for users. Google manages data backup, recovery, and maintenance, freeing users to load data, run analytics and use the results. BigQuery saves time and money for enterprises.

3. Performance

BigQuery handles vast amounts of data with aplomb. It analyses terabytes or petabytes of both historical and real-time data in seconds. The days of indefinitely waiting for your data to be processed are over. 

4. Seamless scalability

BigQuery manages data storage automatically. Organizations do not need to figure out the size and storage requirements of their data warehouses.

5. Accelerated data insights

BigQuery breaks down and processes your data to provide a complete and clear view with its many data tools. These tools help create precise reports and dashboards that provide meaningful insights into your raw data. 

6. Data protection

BigQuery encrypts your data both when stored and in transit. Google handles patching and updating infrastructure. BigQuery provides enterprises with the Identity and Access Management tool to help them set their policies for accessing data. All these security measures ensure that there is no breach of your data.

7. Flexible pricing

The elastic scaling feature of BigQuery enables the enterprise to spend wisely. Save wads of cash by just paying only for the resources you consume. Need more resources? No problem. BigQuery scales automatically to accommodate your request.

8. Allows Geo-expansion

BigQuery provides geo-expansion options in the US, Asia, and Europe. Stay free from the burden of setting up clusters at every location. BigQuery already provides tuned clusters no matter where the enterprise is located.


BigQuery is the best choice for every business that cares about spectacular growth, maximum profit, and low cost of operation. After all, you love to grow your business. Sign up to BigQuery now to benefit from speedy analysis and accurate, actionable insights at the lowest price possible.

Also Read: Data Stack: Decoding The Concept From Scratch!