Database Comparison: AWS vs Microsoft Azure vs GCP
Full Database Service Comparison: AWS vs Microsoft Azure vs GCP
Cloudification is at its peak and is growing further as we speak. Database comparison is only a speck when it comes to determining a winner.
The large volumes of data we generate and collect grows rapidly every day.
Data can be stored across traditional on-premises databases and distributed cloud applications. This makes it more difficult to integrate using outdated approaches.
Since data processing is crucial to a business’s success, any delay and lag can have a severe impact. This is where cloud database comes in to offer reliability, security, flexibility, and most importantly, affordability.
The cloud market is dominated by Amazon AWS, Azure, and GCP. Therefore, the comparison needs to be concise and to the point to draw a winner.
Cloud Database: What You Need to Know
A cloud database, also known as a cloud-based database, is a type of database that is hosted on remote servers and accessed over the internet. Unlike traditional on-premises databases, a cloud database is managed and maintained by a third-party provider.
Moreover, it can be accessed from anywhere with an internet connection. One of the main advantages of a cloud database is scalability, as users can easily increase or decrease the amount of storage and processing power they need.
When it comes to database comparison, a cloud database offers several benefits over traditional on-premises databases. For one, it eliminates the need for expensive hardware and software, as all of the infrastructure and maintenance are handled by the provider.
This can lead to significant cost savings for the user. Additionally, cloud databases offer automatic backups and disaster recovery, which can provide peace of mind and protect against data loss.
Another advantage of a cloud database in comparison to traditional databases is flexibility. With a cloud database, users can easily scale up or down as their needs change, and can also choose from different pricing plans based on their usage. This allows for greater flexibility and cost-effectiveness than traditional on-premises databases.
In terms of security, cloud databases also offer a level of security that can be difficult to achieve with traditional on-premises databases. Cloud providers invest heavily in security measures to protect their customers’ data, and typically have teams of experts dedicated to monitoring and maintaining security.
Furthermore, when discussing database comparison, it’s also important to note that cloud databases are accessible from anywhere with an internet connection, which can be a significant advantage for businesses with employees working remotely or in multiple locations.
What Are Different Options for Running and Managing Databases?
Before the main comparison of database services between AWS, Azure, and GCP. Let’s have a quick look at different options for running and managing databases in the cloud.
1. Self-Managed Database with Virtual Machines
A self-managed database with virtual machines – something you might recall as an on-premises or private cloud database, is a type of database that is hosted and managed by the user rather than a third-party provider.
That is to say, the user is responsible for maintaining and updating the infrastructure, software, and security of the database. (See Shared Responsibility Model for more information)
When it comes to database comparison, a self-managed database with virtual machines offers several advantages over traditional on-premises databases and cloud-based databases.
One of the main advantages is control and customization, as users have complete control over the configuration and management of the database. This allows for greater flexibility in terms of performance and security.
In addition, there is another advantage – the ability to use existing hardware and software, which can be more cost-effective than purchasing new equipment or subscribing to a cloud-based service.
Moreover, self-managed databases with virtual machines can provide a level of privacy and security that may not be possible with cloud-based databases, depending on the user’s specific needs.
However, it’s important to note that with a self-managed database, the user is responsible for all aspects of maintenance and support, which can be time-consuming and costly.
On the other hand, compared to cloud-based databases, it also lacks scalability and accessibility, as it is limited to the physical location and resources of the hardware.
In a nutshell, a self-managed database with virtual machines offers greater control and customization, but it also comes with more responsibilities and limitations. It is a great option for organizations that value privacy and control but are willing to invest in the necessary resources and staff.
2. Database with Kubernetes/Containers
A database with Kubernetes or containers is also called a containerized database. Basically, it is a type of database that runs within a containerized environment.
This means that the database is packaged with its dependencies and configurations, and can be easily deployed and scaled on any infrastructure that supports containers.
Moving forward to a general cloud database comparison, a containerized database offers several advantages over traditional on-premises and cloud-based databases.
Above all, one of the main advantages is portability and flexibility. Containers allow for easy deployment and scaling of the database on any infrastructure that supports them, which makes it a great option for organizations that use multiple cloud providers or have a hybrid cloud environment.
Moreover, containerized databases provide better resource utilization, as containers allow for more efficient sharing of resources, which can lead to cost savings.
In addition, containerized databases also offer better control and management over the environment, making it easier to ensure consistency and compliance.
However, it’s important to note that containerized databases require a certain level of expertise to set up and maintain, and also need a container orchestration platform like Kubernetes to manage the containers.
So where does it stand? a database with Kubernetes or containers offers improved portability, flexibility, and resource utilization, but it also comes with more complexities in terms of setup and maintenance.
It is a great option for organizations that have a hybrid cloud environment or are looking for better control and management over their database infrastructure.
3. Fully Managed Database
A fully managed database is often referred to as a “fully-managed service” or DBaaS (database-as-a-service). It is a specific type of database that is entirely managed and maintained by a third-party provider.
This means that the user does not have to worry about the infrastructure, software, updates, backups, and security of the database, as all of these tasks are handled by the provider.
Now for database comparison, fully managed databases offer several advantages over self-managed and containerized databases. One of the main advantages is the ease of use, as users do not have to worry about the setup, maintenance, and troubleshooting of the database.
In other words, that makes it a great option for organizations that do not have the resources or expertise to manage a database in-house.
Certainly, a great advantage is that fully managed databases can be scaled up or down as needed, allowing for better cost efficiency.
Additionally, fully managed databases also often come with built-in monitoring and analytics features, which can provide valuable insights into the performance and usage of the database.
Fully managed databases also generally offer a high level of security and data protection, as the providers invest heavily in ensuring the safety and availability of the data.
It’s worth noting that fully managed databases can be more expensive than self-managed or containerized options and also may not offer the same level of control and customization as self-managed options.
So who is it for? Fully managed databases are a great option for organizations that want a hassle-free, scalable and secure option, but they come at a higher cost and with limited control over the configurations.
Database Services Comparison: AWS vs Microsoft Azure vs GCP
The table below gives you a brief overview of various database services offered by Amazon AWS, Microsoft Azure, and GCP.
|Amazon AWS||Microsoft Azure||Google Cloud (GCP)|
|RDS||Data Factory||Cloud Bigtable|
|ElastiCache||SQL Database||Cloud Spanner|
|Redshift||Database for MySQL||Cloud SQL|
|Aurora||Data Warehouse||Cloud Datastore|
|Neptune||Database for PostgreSQL|
|Database Migration Service||Server Stretch Database|
You already know that, when it comes to database services, there are three popular options: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud databases.
Each of these vendors offers a variety of database services with different features and capabilities. Now, let’s take a closer look at the database services offered by AWS, Azure, and GCP, and compare them to help you make an informed decision.
1. Amazon AWS Databases
Amazon Web Services (AWS) offers a wide range of database services, including Amazon Relational Database Service (RDS), Amazon DynamoDB, Amazon DocumentDB, and Amazon Aurora.
AWS RDS supports various relational databases such as MySQL, PostgreSQL, Oracle, and SQL Server. On the other hand, Amazon DynamoDB and Amazon DocumentDB are NoSQL databases, and Amazon Aurora is a relational database engine that is fully compatible with PostgreSQL and MySQL.
Above all, AWS databases services offer automatic backups and disaster recovery and provide a high level of security and compliance.
2. Microsoft Azure Databases
Microsoft Azure offers several database services, including Azure SQL Database, Azure Cosmos DB, and Azure Database for MySQL, PostgreSQL, and MariaDB.
Secondly, Azure SQL Database is a fully managed relational database service that is compatible with SQL Server. Azure Cosmos DB is a globally distributed, multi-model database service that supports document, key-value, graph, and column-family data models.
After that, Azure Database for MySQL, PostgreSQL, and MariaDB is also a fully managed relational database that is compatible with the corresponding open-source databases.
Finally, Azure databases also provide automatic backups and disaster recovery and offer a high level of security and compliance.
3. Google Cloud Databases
Google Cloud Platform (GCP) offers several database services, including Cloud SQL, Cloud Spanner, Cloud Bigtable, and Cloud Firestore.
Cloud SQL supports relational databases such as MySQL, PostgreSQL, and SQL Server. Cloud Spanner is a globally distributed relational database service that offers high performance and high availability.
Next to that, Cloud Bigtable is a NoSQL database service for large-scale data storage and analytics. Cloud Firestore is a NoSQL document database that supports offline data access and real-time data synchronization.
Google Cloud databases also provide automatic backups and disaster recovery and offer a high level of security and compliance.
What makes the winner, when it comes to database comparison? All three vendors, AWS, Azure, and GCP offer a wide range of database services with different features and capabilities.
It ultimately depends on the specific needs of your organization. AWS, Azure, and GCP all provide automatic backups and disaster recovery and offer a high level of security and compliance.
Moreover, it is important to evaluate the features and capabilities of each service and choose the one that best fits your organization’s needs.
If you need to see the entire list of services, take a look at the cloud services cheat sheet.
Cost Comparison of Managed Database Services by AWS, Microsoft Azure, and GCP
Finally, coming to the most important bit. The cost comparison of managed database services by AWS, Azure, and GCP. Generally, there is not much of a difference when it comes to AWS and Azure pricing. However, Google recently announced that it will reduce on-demand pricing for managed database services. This will be reduced to the equivalent of the former price alongside the full-sustained discount.
This is big news for businesses as Google Cloud is becoming a more affordable solution. However, let’s run a quick cost comparison between the three.
Amazon AWS Database Costs
As aforementioned, Amazon Web Services (AWS) offers a wide range of managed database services, including Amazon Relational Database Service (RDS), Amazon DynamoDB, and Amazon Aurora. The pricing for these services is based on the number of requests, storage, and data transfer.
- The cost for RDS varies depending on the database engine, instance type, and region.
- DynamoDB pricing is based on the number of requests and the amount of data stored.
- Aurora pricing is based on the number of Aurora Capacity Units (ACUs) consumed per second.
- AWS also offers reserved instances, which can provide significant savings compared to on-demand pricing.
Moreover, Amazon AWS allows you to achieve discounts of up to 60%. This is only possible if you pay all upfront and go for a three-year standard AWS RDS reserved instance. Keep in mind that managed database services do not qualify for the saving plans offered by AWS.
Microsoft Azure Database Costs
The pricing for Azure database services is based on the number of requests, storage, and data transfer.
- Azure SQL Database pricing is based on the number of DTUs consumed per second.
- Azure Cosmos DB pricing is based on the number of requests and the amount of data stored.
- Azure Database for MySQL, PostgreSQL, and MariaDB pricing is based on the number of vCore-hours consumed per month.
On the other hand, Azure also offers reserved instances, which can provide significant savings compared to on-demand pricing.
As for discounts, Azure offers varying discounts based on compute costs of database types. The average discount available on azure for managed database service is 36%. It can go up to 80% with hybrid benefits and no upfront payment is required.
Google Cloud Database Costs
Finally, pricing for Google Cloud databases services is based on the number of requests, storage, and data transfer.
- Cloud SQL pricing is based on the number of vCPUs, memory, and storage consumed per month.
- Cloud Spanner pricing is based on the number of nodes, storage, and data transfer consumed per month.
- Cloud Bigtable pricing is based on the number of nodes, storage, and data transfer consumed per month.
- Cloud Firestore pricing is based on the number of operations and the amount of data stored.
GCP also offers sustained use discounts, which can provide significant savings compared to on-demand pricing. With the recent changes in the managed database pricing structure, it is possible to get discounts of up to 52%. Unlike the others, these discounts apply to both; compute and memory utilization.
When it comes to cost comparison of managed database services, all three vendors, AWS, Azure, and GCP offer a wide range of options with different pricing models.
AWS and Azure offer reserved instances, while GCP offers sustained use discounts. It ultimately depends on the specific needs of your organization. However, when it comes to the best price, GCP provides sustained use discounts which can lead to cost savings compared to on-demand pricing.
Furthermore, GCP also offers a flexible pricing model that allows for more control over the cost. It is important to evaluate the cost of each service and choose the one that best fits your organization’s needs.
What Should You Consider Before Selecting a Cloud Database?
The following list shouldn’t be confused with disadvantages. On the contrary, consider these as factors that require careful evaluation before selecting a cloud service provider.
- Security Concerns,
- Knowledge of Cloud Costs,
- Difficulty Level While Integrating Data With Other Systems,
- Vendor Lock-in,
- Complexity and Time Requirement for Migrations,
- Possibility of Connection Downtime.
The Verdict – Database Comparison
Even when talking about a single aspect such as database comparison, there’s no doubt that Amazon AWS is dominating the Cloud market and Azure is the runner-up.
However, Google is only lagging because of the limited services offered. Another reason is that the platform is comparatively new.
The main point here is that Google Cloud offers the same performance, scalability, security, and flexibility as Amazon AWS and Azure. In addition, the pricing is highly competitive and this is where Google Cloud beats AWS and Azure at.
Then again, there is still time for GCP to reach its full potential. Meanwhile, there is not much of a difference in resorting to either vendor for database services.
Remember, GCP, Azure, and AWS offer different benefits based on your needs. It is important to thoroughly check which is the most suitable for your business requirements before picking a solution.
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