What is Bigquery
Tags: bigdata, gcp, bigquery
Published: 2023-03-09 16:41:30

## Introduction

BigQuery is a fully managed cloud data warehouse that enables businesses to store and query massive datasets using a SQL-like language. It is a part of the Google Cloud Platform and has become one of the most popular cloud-based data warehouses in recent years. In this article, we will explore the features of BigQuery and compare it with Cassandra and DynamoDB, two other popular NoSQL databases.

## Features of BigQuery

**Scalability:** BigQuery is designed to handle massive datasets and can scale to petabytes of data. It uses a columnar storage format that allows for efficient data retrieval and compression.

**Fully managed:** BigQuery is a fully managed service, which means that Google handles all of the infrastructure and maintenance. This makes it easy to set up and use, as there is no need to worry about managing servers or software updates.

**Security:** BigQuery is designed with security in mind and offers a range of features to protect data. It provides encryption at rest and in transit, and also offers fine-grained access controls to ensure that only authorized users can access sensitive data.

**Integration with other Google Cloud services:** BigQuery integrates with other Google Cloud services such as Cloud Storage, Cloud Dataflow, and Cloud Dataproc, making it easy to load data from other sources and analyze it using BigQuery.

**SQL-like interface:** BigQuery uses a SQL-like language for querying data, which makes it easy for analysts and data scientists to use. It also offers support for standard SQL functions and syntax.

## Comparison with Cassandra and DynamoDB

Cassandra and DynamoDB are two popular NoSQL databases that are often compared to BigQuery. Here are some of the key differences between them:

**Data model:** Cassandra and DynamoDB both use a key-value data model, which is optimised for handling large volumes of unstructured data. BigQuery, on the other hand, uses a relational data model, which is better suited for structured data and SQL queries.

**Querying:** Cassandra and DynamoDB both use proprietary query languages, which can be difficult for analysts and data scientists to use. BigQuery, on the other hand, uses a SQL-like language that is familiar to most analysts.

**Scalability:** All three databases are designed to be highly scalable, but BigQuery is specifically designed to handle massive datasets and can scale to petabytes of data.

**Cost:** Cassandra and DynamoDB are both priced based on the amount of storage and read/write capacity required. BigQuery, on the other hand, is priced based on the amount of data processed by queries. This can make BigQuery more expensive for smaller datasets, but more cost-effective for larger datasets.

## Conclusion

BigQuery is a powerful cloud-based data warehouse that is designed to handle massive datasets and provide fast, SQL-like querying capabilities. While it has some similarities to Cassandra and DynamoDB, it offers a more traditional relational data model and SQL querying capabilities that make it well-suited for data analytics and business intelligence. Whether you're a data analyst or a data scientist, BigQuery offers a range of features that can help you to analyze and make sense of your data.