The Most Important Google Cloud Platform Databases For Web Analysis
Management Summary
Big Query
BigQuery is an enterprise data warehouse that enables the storage and querying of large datasets by processing SQL queries very quickly.
Big Query Properties
- Designed for very large amounts of data / petabyte and exabyte range / data warehouse
- BigQuery tables have a schema, which means that the individual columns of the table are precisely predefined
- For example, Google Analytics describes BigQuery Schema, among other things, that there is a field / column with the name “clientId” which has assigned the data type “STRING”
- The data can be queried using SQL
In the area of web analysis, BigQuery is mainly known because the raw data of a Google Analytics 360 version is exported into it. Firebase Analytics and Google Analytics 4 Properties now also offer the option of exporting raw data to BigQuery.
Cloud SQL
Cloud SQL is a fully managed relational database service for MySQL, PostgreSQL and SQL Server. Cloud SQL automates all data backup, replication, encryption, patching and capacity expansion.
Cloud SQL properties
- Designed for high performance / short response times
- Cloud SQL databases also typically have a schema and can be queried using SQL
Of course, the properties of BigQuery and Cloud SQL are not complete. However, it is intended to show that both GCP resources have many similarities. The main difference, however, is the performance.
With BigQuery, for example, a query of 500 MB takes between 1 – 2 seconds. 10 GB takes around 10 seconds. Whereas a query (depending on the query, of course) in Cloud SQL is often in the millisecond range.
As a rule of thumb, you could say: the larger the amount of data and the further the technology is from the end user, the more the argument is in favor of using BigQuery. On the other hand, you should probably choose Cloud SQL if the technology is close to the end user and fast response times are therefore necessary.
Google Cloud Storage
Google Cloud Storage is object storage for businesses of all sizes. Any amount of data can be stored and the data can be accessed as often as desired.
Google Cloud Storage Properties
- In contrast to the two resources above, Google Cloud Storage does not have a schema
- SQL-like queries are possible (GQL)
You can imagine Google Cloud Storage as similar to Google Drive. It is used to store – a lot of – files, but is much more powerful in terms of performance, scalability, security and access management.
The highest hierarchy level are buckets. However, these buckets cannot be nested within each other – like Google Drive folders. They are used for organization and for assigning rights.
The objects, i.e. the files and folders, are located within the buckets.
