Google BigQuery vs Presto: What are the differences?
Developers describe Google BigQuery as "Analyze terabytes of data in seconds". Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.. On the other hand, Presto is detailed as "Distributed SQL Query Engine for Big Data". Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
Google BigQuery can be classified as a tool in the "Big Data as a Service" category, while Presto is grouped under "Big Data Tools".
"High Performance" is the top reason why over 17 developers like Google BigQuery, while over 9 developers mention "Works directly on files in s3 (no ETL)" as the leading cause for choosing Presto.
Presto is an open source tool with 9.29K GitHub stars and 3.15K GitHub forks. Here's a link to Presto's open source repository on GitHub.
According to the StackShare community, Google BigQuery has a broader approval, being mentioned in 160 company stacks & 41 developers stacks; compared to Presto, which is listed in 19 company stacks and 11 developer stacks.
Sign up to add or upvote prosMake informed product decisions
Sign up to add or upvote consMake informed product decisions
What is Google BigQuery?
What is Presto?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions