Google Cloud Platform (GCP) provides a number of options for storing and processing data. Here are some of the main options:
- Cloud Storage: This is a highly scalable, durable, and secure object storage service that allows you to store and retrieve large amounts of data from anywhere on the internet. You can use Cloud Storage to store a variety of data types, including structured data in the form of CSV or JSON files, unstructured data such as audio or video files, and large datasets for analytics or machine learning.
- BigQuery: This is a fully managed, cloud-native data warehouse that enables super-fast SQL queries on large datasets. It’s ideal for storing and querying data that you need to analyze using SQL, and it integrates seamlessly with other GCP tools such as Data Studio and Cloud Dataproc.
- Cloud SQL: This is a fully managed relational database service that makes it easy to set up, maintain, and administer a SQL database in the cloud. It supports a number of popular database engines, including MySQL and PostgreSQL, and it can be used to store structured data such as customer information or product catalogs.
- Cloud Dataproc: This is a fully managed data processing service that makes it easy to run Apache Hadoop, Apache Spark, and other open-source data processing frameworks on GCP. It’s ideal for ETL (extract, transform, load) workflows, as it allows you to quickly and easily process large datasets and load them into storage systems like BigQuery or Cloud Storage.
- Cloud Data Fusion: This is a fully managed data integration service that makes it easy to build and maintain ETL pipelines on GCP. It provides a visual interface for designing and executing ETL workflows, and it integrates with a number of GCP and third-party data sources and sinks.