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Designing Data Warehouses on Google Cloud Platform – Google Big Query

IBM Cloud Pak for Automation

Google Big Query product is the data warehouse product within GCP.
Google Cloud Platform provides several data storage options.
It is important to choose the right option, based on the requirements for data addition, updates and querying.

Data Storage Options:

The first option we have is Cloud Storage. It is an object storage database similar to Amazon S3. Data is organized as buckets and files and can be accessed by a global URL.

The next option is Cloud SQL. It is nothing but a managed version of MySQL or PostgreSQL. It serves us as a great option for storing small- or medium-sized relational data. Also, we have Cloud Spanner.

Cloud Spanner is a GCP native RDBMS product that provides data consistency like RDBMS while having horizontal scalability like NoSQL. Cloud Spanner can be expensive though, so tread carefully.

Then comes Cloud Bigtable, which is a columnar database like Cassandra and HBase. It supports an HBase interface for compatibility.

Next, there is Cloud Datastore, which is a document database like MongoDB or Elasticsearch. In Cloud Datastore, data can be stored in flexible JSON formats. The next GCP data storage option is Cloud Memory Store, which is a key-value store like Redis and finally, there is Cloud Big Query, which is a data warehouse providing a SQL interface.

Google Big Query:

It is a database that allows storing and retrieving data using SQL. While the definition is simple it has great capabilities that are useful in setting up data warehouses on GCP and enabling skill to able analytics within the organization.

Key Big Query features:

It comes with Google Cloud Scaling and availability. It is fully managed and serverless and there is no need to provision and manage compute engines or regions for Big Query. There is no or minimal dba work required for managing Big Query and it is secure and highly available by default.

Big Query provides SQL-based data manipulation and query, and it is easy to transition from traditional RDMS products to Big Query and it has multiple interfaces to manage and query data. Big Query includes a web UI for interactive work, a command line for interactive scripting, and Rest API and SDK for programming applications.

Google Big Query is a great option for storing and analyzing data in the Google cloud platform.

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Mangai Murugan

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