google-big-queryHow can I compare Google BigQuery and AWS Redshift for software development?
Google BigQuery and AWS Redshift are both cloud-based data warehouses that can be used for software development. BigQuery is a serverless, fully managed data warehouse that offers an open source SQL-like query language. Redshift is a managed data warehouse service that offers a PostgreSQL-compatible interface.
When comparing the two services, BigQuery is generally more cost-effective, as it does not require any upfront costs and charges by the amount of data stored and queried. Redshift, on the other hand, requires upfront costs and charges by the amount of data stored and the number of nodes used.
BigQuery also supports a wide range of data types including nested and repeated fields, while Redshift does not. BigQuery also has a larger query size limit than Redshift.
In terms of performance, BigQuery is generally faster than Redshift, as it is a serverless solution and does not require nodes to be provisioned.
Example code to query data from BigQuery:
SELECT * FROM `project-id.dataset.table`
This code will query all data from the specified table in the dataset.
Helpful links
More of Google Big Query
- What are the advantages and disadvantages of using Google BigQuery?
- How do I set up a Google Big Query zone?
- How can I use Google Big Query to integrate with Zephyr?
- How do I set up permissions for Google BigQuery?
- How do I use the "not in" operator in Google BigQuery?
- How can I use Google Big Query with MicroStrategy?
- How do I use Google Big Query with Zoom?
- ¿Cuáles son las ventajas y desventajas de usar Google BigQuery?
- How can I use Google BigQuery to wait for a query to complete?
- How do I use wildcards in Google BigQuery?
See more codes...