In this blog, we are going to provide some clarity about the different Google Cloud Storage & Database options available on the Google Cloud Platform.
Google Cloud Platform (GCP) delivers various storage and database service offerings that remove much of the burden of building and managing storage and infrastructure.
Google Storage And Database Options
Google Cloud offers 9 storage and database options namely:
- Cloud Storage
- Cloud SQL
- Cloud Spanner
- Cloud Datastore
- Cloud Bigtable
- Persistent Disk
- Cloud Firestore (Firestore & Filestore are both two different types)
- Google Cloud Filestore
- BigQuery
Note : Check out our Blog Post on Google Cloud Functions.
Data Types: Structured & Unstructured Data
The Google storage and database services can be put into 2 categories:
1.) Structured Data
If the data can be organized in a structural format like rows and columns then it is known as structured data. It comes in various sizes, latency, and cost based on the requirement. Example: Financial data, logs, etc.
From the various offerings of Google Storage service, structured data can be stored in Cloud SQL, Cloud Spanner, Cloud Datastore, Cloud Bigtable, Cloud BigQuery, and Persistent disk.
2.) Unstructured Data
It is a sequence of bytes that could be from a video, image, or document. The data is stored as objects in buckets and no insight can be gained from unstructured data.
Google Cloud Storage and Cloud Firestore are used to store unstructured data in the Google Cloud Platform.
To know more about types of data read the blog post at Structured Data Vs Unstructured Data.
Now let’s look at each of these Google storage and database options in brief.
1.) Google Cloud Storage
Category: Object Storage, Archival Storage
Google Cloud Storage is the object storage service offered by Google Cloud. It provides some interesting features such as object versioning or fine-grain permissions (per object or bucket), that can make development easy and help reduce operational overheads. It also serves as the foundation of several different services.
Key Features
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- Scalability: Google Cloud Storage is designed to scale to meet your needs, whether you need to store a few gigabytes or petabytes of data. You can easily increase or decrease your storage capacity as needed, and pay only for what you use.
- Durability: Google Cloud Storage is designed to be highly durable, with multiple copies of your data stored across different locations for redundancy. It offers 99.999999999% (11 nines) data durability, meaning that your data is protected against data loss due to hardware failures, natural disasters, or other issues.
- Security: Google Cloud Storage offers several security features to help protect your data, including encryption at rest and in transit, access control lists, signed URLs, and more. You can also integrate with other Google Cloud services like Cloud Identity and Access Management (IAM) to manage access to your data.
- Flexibility: Google Cloud Storage offers four different storage classes – Standard, Nearline, Coldline, and Archive – to suit different use cases and data access needs. You can also use Google Cloud Storage for backup and disaster recovery, content delivery, and more.
- Integrations: Google Cloud Storage integrates with other Google Cloud services like BigQuery, Cloud Functions, and Compute Engine, as well as third-party tools and services like Apache Spark, Hadoop, and Splunk.
Cloud Storage lets you choose among four different types of storage classes: regional, Multi-regional, Nearline, and Coldline. Multi-regional and Regional are high-performance object storage, whereas Nearline and Coldline are back-ups and archival storage. All of the storage classes are accessed in analogous ways using the Cloud Storage API, and they all offer millisecond access times.
2.) Cloud Firestore
Category: Mobile App Services, non-relational
Cloud Firestore is a flexible, scalable database for mobile, web, and server development from Firebase and Google Cloud. Like Firebase Realtime Database, it keeps the data in-sync across client apps through real-time listeners and offers offline support for mobile and web so users can build responsive apps that work regardless of network latency or Internet connectivity.
Note : You Can Check our Blog Post on Google App Engine.
3.) Google Cloud Filestore
Category: File Storage
Google Cloud Filestore is widely used when it comes to performing heavy machine learning tasks, media processing, rendering, etc due to the high throughput it is highly preferred. It is generally not considered as a storage option, but a temporary drive for performing high read intensive tasks.
Key Features
- It offers low latency for file operations.
- It is a fully managed, NoOps service that is integrated with the rest of the Google Cloud portfolio.
- Users can scale file storage elastically to suit the evolving needs of their business.
- Supports storage of unstructured objects, transactions, and SQL-like queries.
4.) Persistent Disk
Category: Block Storage
Persistent disks are durable network storage devices that the instances can access like physical disks on a desktop or a server. The data on each persistent disk is distributed across several physical disks. The physical disks and the data distribution are managed by the Compute Engine to ensure redundancy and optimal performance.
Key Features
- It has built-in redundancy to protect the data against equipment failure
- It ensures data availability through datacenter maintenance events.
- Performance is predictable
- It scales linearly with provisioned capacity until the limits for an instance’s provisioned vCPUs are reached.
5.) Cloud SQL
Category: Relational Database service
Cloud SQL is a fully-managed database service that helps in setting up, maintain, manage, and administer relational databases on the Google Cloud Platform.
Key Features
- Google Storage Cloud SQL offers MySQL and PostgreSQL databases as a service.
- Automatic replication
- Managed backups
- It facilitates Vertical & Horizontal scaling
6.) Cloud Spanner
Category: Relational Database service
Cloud Spanner is a fully managed, mission-critical, relational database service. It offers transactional consistency at a global scale, schemas, SQL, and automatic, synchronous replication for high availability.
Key Features
- Regional and multiregional configurations
- Built on Google Cloud Network
- Provides on-demand backup and restore for data protection
- It supports multiple languages like C#, C++, Java, Python, etc.
7.) Cloud Bigtable
Category: Non-relational Database service
Cloud Bigtable is Google’s NoSQL Big Data database service. It is the same database powering many Google services, like Search, Analytics, Maps, and Gmail.
Key Features
- Provides high throughput with low latency
- Write data once and automatically replicate where needed with eventual consistency
- It helps in executing machine learning algorithms on the data
8.) Cloud Datastore
Category: Database service
Cloud Datastore is a highly-scalable NoSQL database. It uses a distributed architecture to automatically manage scaling. The queries scale with the size of the result set and not the size of the data set.
Key Features
- Supports Automatic Transactions
- High availability of reads and writes.
- Flexible storage and querying of data
- Massive scalability with high performance
- It is a fully managed service with no planned downtime.
9.) BigQuery
Category: Data Warehouse
BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service (PaaS) that supports querying using ANSI SQL. and also has built-in machine learning capabilities.
Key Features
- It enables data scientists and data analysts to build and operationalize ML models on structured or semi-structured data, directly inside BigQuery.
- It allows users to analyze data across clouds using standard SQL.
- Its high-speed streaming insertion API provides a powerful foundation for real-time analytics, making the latest business data immediately available for analysis.
- BigQuery automatically replicates data and keeps a seven-day history of changes, allowing users to easily restore and compare data from different times.
Google Cloud Storage & Database Decision Tree Flowchart
Check this flowchart to identify the correct storage and database service for your project requirement.
Note : You Can also Read our Blog Post on Google Cloud Services.
These are the Google Cloud Storage and Database services that can be used by the users to manage and process data.
Frequently Asked Questions
What is the difference between Cloud SQL and Cloud Spanner?
There is not much difference between Cloud SQL and Cloud spanner in terms of what they do (storing data in tables). The difference is how they handle the data on a small and big scale. Cloud Spanner is used when there is a requirement to handle massive amounts of data with an elevated level of consistency and with a big amount of data handling (+100,000 reads/write per second) as it gives much better scalability and better SLOs but is expensive than Cloud SQL. Cloud SQL can be used to store some data of your customer in a cheap way but still don't want to face server configuration.
What is the largest object size that you can store in Google Cloud Storage?
There is a maximum size limit of 5 TB for individual objects stored in Cloud Storage.
What type of database is Cloud SQL?
Cloud SQL is a fully-managed database service that helps in setting up, managing, and administering relational databases on the Google Cloud Platform.
Note : You Can Check this blog on Associate Cloud Engineer.
Related References
- GCP Associate Cloud Engineer: All You Need To Know About
- GCP Professional Cloud Architect: Everything You Need To Know
- Introduction To Google Cloud Platform
- Google Cloud Services & Tools
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