google-big-queryHow do Google BigQuery and Hive differ in terms of software development?

Google BigQuery and Hive are both data warehousing solutions used for software development. However, they differ in the way they are used and the language they use.

Google BigQuery is a fully managed serverless cloud data warehouse that uses standard SQL for querying data. It is designed to handle large datasets and allows for scalability and fast query processing. BigQuery also supports user-defined functions, allowing developers to create custom functions to manipulate data.

Hive is an open source data warehouse system built on top of the Hadoop distributed computing framework. It uses a query language called HiveQL, which is based on the SQL language. Hive is designed to process large amounts of data stored in a distributed file system and supports user-defined functions.

Below is an example of a query written in BigQuery and HiveQL:

BigQuery:

SELECT * FROM my_table
WHERE some_column > 100

HiveQL:

SELECT * FROM my_table
WHERE some_column > 100

The main difference between Google BigQuery and Hive is the language they use and the way they are used. BigQuery is a fully managed serverless cloud data warehouse that uses standard SQL for querying data, while Hive is an open source data warehouse system built on top of the Hadoop distributed computing framework that uses HiveQL.

Helpful links

• Google BigQuery
• Apache Hive

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