Storage and Database services in Google Cloud
Introduction
Hello All, Welcome back !! Understanding Google Cloud’s storage and database services can be challenging, especially for those new to Google cloud . With so many different services to choose from, each with its own unique features and capabilities, it can be challenging to know where to start. Additionally, Google Cloud’s documentation and terminology can be overwhelming and confusing for those who are not familiar with Google cloud. However, with the right resources and guidance, even beginners can learn to use these powerful database services to their advantage.
In this blog post, I will provide an overview of Google Cloud’s Storage and database services with an amazing picture as we are humans with “Pictorial Memory”.
So, let’s dive in and explore the world of Google Cloud Storage and Databases!
Let's start with the below picture I have created for a better understanding of this topic. Based on capabilities, features, and use cases Storage and database services and classified into the below categories.
Object Storage
Google Cloud offers object storage services that allow users to store and retrieve unstructured data objects, such as images, videos, audio files, documents, and backups, in the cloud. Object storage is a type of storage architecture that stores data as objects, rather than as blocks or files. This approach provides several advantages, such as scalability, durability, and cost-effectiveness.
Google Cloud’s object storage services are designed to be highly available, durable, and secure. They provide features such as versioning, access control, lifecycle management, and object tagging, which can help users manage their data more effectively
Block Storage
Block storage is a type of storage that provides raw, unformatted block-level access to data. In Google Cloud, Persistent Disk is the primary block storage service. Here’s more information about block storage in Google Cloud:
Persistent Disk: Persistent Disk is a block storage service that provides reliable and high-performance storage for virtual machine instances in Google Compute Engine. We can use Persistent Disk to store operating system images, data, and other files that are associated with your virtual machines. Persistent Disk supports both standard and SSD storage options, as well as several different disk types to meet different performance and cost requirements. Refer link to know more about disk types and performance metrics
Local SSD: Local SSD is a temporary block storage option that’s directly attached to a virtual machine instance. It provides high-speed, low-latency access to data, making it ideal for use cases such as temporary data processing and high-performance computing. Local SSD is not persistent, which means that data is lost when the virtual machine is terminated or moved.
Relational databases
Google Cloud offers various relational database services that allow users to store, manage, and retrieve structured data in the cloud. Relational databases use a table-based data model that organizes data into rows and columns, and uses relationships between tables to represent complex data structures. Here are some of the main relational database services provided by Google Cloud:
Cloud SQL: This is a fully-managed database service that supports MySQL, PostgreSQL, and SQL Server. Cloud SQL automates many database management tasks, such as backups, replication, and scaling, and provides high availability and security.
If you have prior experience in other cloud, you can relate Cloud SQL in Google cloud with Azure SQL in Azure and RDS in AWS for overall understanding.
Use Cases- Cloud SQL is suitable for small to medium-sized databases that require low to moderate levels of performance.
Cloud Spanner: This is a globally distributed, horizontally scalable relational database service that provides strong consistency and high availability. It supports ACID transactions and SQL queries, and it can scale horizontally to handle large volumes of data and high write rates. This is Google's In-house product for relational databases.
Use cases- Cloud Spanner is ideal for large-scale, mission-critical applications that require high levels of scalability, availability, and performance, such as financial trading systems or online booking platforms.
NoSQL databases
NoSQL database services in Google Cloud Platform offer different features and capabilities to cater to different use cases and data requirements. They are fully managed and scalable, which means that users do not have to worry about managing the underlying infrastructure or the scaling of the database as the data grows.
Cloud Bigtable: Cloud Bigtable is a NoSQL, fully managed, massively scalable database service developed by Google Cloud Platform. It is designed to store and process massive amounts of structured and semi-structured data, with low latency and high throughput and is used by Google services such as Search, Maps, and YouTube.
Use cases- Cloud Bigtable is suitable to store and process time-series data, sensor data from IoT devices or to analyze log data for a web application and in various industries, including finance, healthcare, and media, for applications such as time series analysis, ad targeting
Cloud Datastore: A fully-managed NoSQL document database that offers real-time synchronization and offline support for mobile and web applications.
Cloud Memorystore: Cloud Memorystore is a fully managed, in-memory NoSQL database service that is designed to provide fast and low-latency data access for web and mobile applications. It supports Redis and Memcached protocols and offers automatic scaling, high availability, and data persistence.
Data warehouse
BigQuery is a fully-managed, serverless data warehouse service that enables users to run SQL queries against large datasets in real-time. It is designed to handle petabyte-scale data and supports both structured and semi-structured data types, including JSON and Avro.
BigQuery also offers a number of integrations with other Google Cloud services, such as Cloud Dataflow, Cloud Storage, and Google Sheets, which enable users to extract, transform, and load data from various sources and analyze it in BigQuery.
Conclusion
In conclusion, Google Cloud Platform provides a wide range of storage and database services that can help businesses manage their data and applications in the cloud. From Cloud Storage and Cloud SQL to BigQuery and Cloud Spanner, Google Cloud offers solutions for storing and processing data of all types, whether structured, unstructured, or semi-structured.
Thank you for reading.
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