AWS Vs Azure Vs Google Cloud: Full Database Comparability


Fast Entry

The worldwide cloud database and DBaaS market stood at a price of round USD 12.2 billion in 2020. The market is predicted to develop at a CAGR of 15.9% within the forecast interval of 2022-2027 to realize a price of USD 29.6 billion by 2026.

Organizations at present, are coping with massive quantities of information. Whether or not it’s associated to their prospects or the services or products – knowledge is serving as a basis for making essential and strategic enterprise choices. Because the variety of knowledge will increase, organizations want entry to dependable database options to handle this knowledge and hold it secure. Therefore, the transfer to cloud databases.

What’s a cloud database?

A Cloud database is a database service constructed on a cloud infrastructure. It is sort of a conventional database – with added advantages of cloud computing.

Widespread options of a cloud database embrace:

  • Wherever, anytime accessibility – as it’s constructed and accessed by a cloud platform
  • Might be hosted with out requiring any devoted {hardware}
  • Might be managed by the group or supplied as-a-service
  • Might be accessed by vendor-provided API or a web-interface

The most important benefits of shifting to a cloud database are scalability, simple accessibility, and safety.

Sorts of databases

On this article, we are going to largely be speaking about three kinds of database choices by main cloud distributors – Amazon Net Companies (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

1. Relational Databases

Oracle defines a relational database as, “A relational database is a sort of database that shops and supplies entry to knowledge factors which can be associated to 1 one other.”

So, in a relational database administration system (RDBMS), knowledge is saved in a relational and intuitive method. Right here, every desk row is a document with a novel ID – generally known as the Key. This helps set up relationships between completely different knowledge factors.

These are structured databases.

Widespread examples embrace the scholars’ data in a faculty database or prospects’ data in an organization. Through the use of frequent columns just like the buyer ID or scholar enrollment numbers, you may extract completely different data pertaining to a selected trigger or requirement.

Relating to RDBMS, there are 4 essential properties that outline their transactions – atomicity, consistency, isolation, and sturdiness (generally known as ACID transactions). These databases use structured question language (SQL).

2. Non-relational databases

Non-relational databases don’t retailer knowledge in a relational method. In different phrases, there isn’t a tabular type of knowledge. They’re much extra versatile than relational fashions as they haven’t any mounted construction. Various kinds of knowledge will be saved on this format. They’re an ideal match when you’ll want to retailer massive quantities of non-related knowledge.

They’re typically known as NoSQL (not solely SQL) databases as properly. A NoSQL database is one that doesn’t use SQL queries.

AWS Vs Azure Vs Google Cloud: Database Comparability

Many enterprises at present are shifting from on-premises database options to cloud databases as a result of their flexibility. Gartner predicts that by 2022, 75% of all databases will probably be deployed or migrated to cloud platforms.

Nevertheless, what are the highest decisions with regards to cloud database options?

That can assist you resolve, let’s focus on the highest 3 widespread cloud database service suppliers – AWS (Amazon Net Companies), Microsoft (Azure), and Google Cloud –  their breadth of product choices, migration mechanisms, and pricing flexibilities.

Fundamental Overview – Product Breadth

1. AWS Cloud Databases

AWS presents a variety of cloud databases – purpose-built to satisfy completely different necessities. The databases are totally managed to assist companies save time spent on database administration duties like server provisioning, backups, and patching.

With options like steady monitoring, automated scaling, and self-healing storage – it helps companies give attention to utility growth.

AWS databases are identified for his or her excessive scalability. It’s appropriate for all sorts of utility growth wants. One can begin small and scale up because the enterprise grows.

1.1 Relational Databases by AWS

a) Amazon Aurora: The RDBMS service by AWS is constructed for the cloud and is totally suitable with MySQL and PostgreSQL. With Aurora, you will get the efficiency of economic grade enterprises at one-tenth the associated fee. Advantages:

  • Get help for high-performance and multi-tenant utility growth.
  • Pay just for capability consumed.
  • Get multi area scalability and skill to deploy globally distributed purposes.

It’s excellent for growing purposes like buyer relationship administration (CRM), enterprise useful resource planning (ERP), provide chain, billing purposes, and so on., for constructing SaaS (Software program-as-a-Service) purposes with versatile occasion and storage scaling.

b) Amazon RDS: Amazon Relational Database Service (Amazon RDS) is a set of high-performing managed providers that means that you can arrange, function, and scale databases within the cloud with full flexibility and price effectivity.

You possibly can select from widespread engines SQL Server, Amazon Aurora with PostgreSQL, Amazon Aurora with MySQL, MariaDB, Oracle, and PostgreSQL. It can be deployed on-premises with Amazon RDS on AWS Outposts service.

It’s excellent for constructing net purposes with excessive scalability necessities.

c) Amazon Redshift: The Amazon Redshift cloud database warehouse service is designed to assist prospects analyze exabytes of information and run complicated analytical queries.

With it, organizations can run and scale analytics inside seconds with out worrying concerning the warehouse infrastructure.

It helps break away from knowledge silos and acquire real-time predictive insights. It’s excellent:

  • For constructing and working monetary and demand forecasts purposes.
  • For simply and securely sharing knowledge amongst organizations, companions, and departments.
  • For constructing insight-driven dashboards utilizing enterprise intelligence instruments like Microsoft PowerBI, Tableau, Amazon QuickSight, and so on.

1.2 Non-relational (NoSQL) databases by AWS

a) Key-Worth

Amazon DynamoDB NoSQL database service is right for constructing and delivering apps with constant single-digit millisecond efficiency backed with automated multi-region replication.

With an SLA of 99.999%, it presents excessive safety and reliability.

Different options embrace built-in safety, in-memory caching, steady backups, knowledge import, and export instruments. It’s excellent:

  • For growing software program purposes with excessive concurrency and connection necessities.
  • For creating media metadata shops with excessive throughput.
  • For deploying procuring cart purposes.
  • For creating stock monitoring and buyer profile purposes.

b) Doc

Amazon DocumentDB (with MongoDB compatibility): Amazon DocumentDB (with MongoDB compatibility) is a completely managed doc database service with the flexibility to scale JSON workloads with ease. It might help hundreds of thousands of paperwork learn requests per second by scaling storage and compute independently. It presents 99.999999999% sturdiness with steady backup, automated replication, and strict community isolation.

Supply: AWS
  • Splendid for Content material Administration System (CMS) purposes as it may well assist enhance buyer experiences with dependable and quick entry to pictures, opinions, and so on.
  • For managing prospects’ person profiles and establishing preferences.
  • For constructing purposes that may scale to course of hundreds of thousands of person requests per second with millisecond latency.

Other than the general-purpose NoSQL databases we mentioned above, Amazon additionally presents different kinds of NoSQL databases like in-memory, graph, time collection, wide-column, and ledger. We is not going to be going into the small print of those, however right here’s a brief description for databases in these classes:

1. Amazon ElastiCache: It’s an in-memory NoSQL database service supplied by AWS that provides microsecond latency and excessive scalability for reinforcing utility efficiency. It might additionally assist organizations scale back prices and eradicate the operational overheads related to self-managed caching.

2. Amazon MemoryDB for Redis: It’s also an in-memory database that’s Redis-compatible. It might assist organizations construct purposes on Redis and entry knowledge with ultra-fast efficiency. It makes use of Multi-AZ transactional log for quick database restoration and restart.

3. Amazon Keyspaces: Apache Keyspaces (for Apache Cassandra) is a wide-column database service by AWS. It permits customers to run Cassandra workloads on AWS with ease. It’s a serverless service, so the customers have to pay just for the precise sources consumed. It’s excellent for constructing purposes that serve hundreds of requests per second with limitless throughput and storage.

4. Amazon Neptune: It’s a graph database service excellent for constructing and deploying excessive efficiency graph purposes utilizing widespread open-source APIs like openCypher, Gremlin, and SPARQL. Functions constructed on Amazon Neptune can execute greater than 100,000 queries per second.

5. Amazon Timestream: This time-series database service by AWS is right for IoT (Web of Issues) and operational purposes that makes it simple to retailer and analyze a number of occasions per day as much as 1,000 instances quicker and at little as 1/10th of the price of relational databases. It’s serverless and thus can mechanically scale up or down to regulate  efficiency or capability.

6. Amazon Quantum Ledger Database Companies (QLDB): The ledger database service by AWS might help organizations preserve an immutable, cryptographically verifiable log of information adjustments. It may be used to construct event-driven methods with QLDB ACID transactions.

2. Azure Databases

2.1 Relational Databases by Azure

a) Azure SQL Database

Azure SQL Database is a completely managed clever relational database service constructed for cloud purposes. It’s all the time updated with automated updates, provisioning, and backups. This provides extra time to innovate with the top customers. As it’s serverless, it helps excessive scalability wants and shortly adapts to altering utility necessities.

Relating to safety, it has a number of layers of safety and clever menace detection to assist hold the information safe. It has an SLA of 99.995%. The built-in AI and excessive availability are perfect for sustaining peak efficiency and sturdiness.

  • It might assist customers save with a decrease whole value of possession (as much as 80 p.c) by combining the service with Azure Hybrid Profit.
  • It makes use of At all times Encrypted expertise to guard the purposes’ knowledge. The encryption keys are hidden from the SQL database engine.
  • It helps automated scaling based mostly on workload demand.

b) Azure Database for PostgreSQL

Azure Database for PostgreSQL is a completely managed and clever Azure database that may scale utility workloads shortly and with ease and confidence. It presents SLAs as much as 99.99 p.c – making it extremely accessible.

Because the service is totally managed, it may well automate duties like upkeep, updates, and patching. It helps numerous PostgreSQL extensions like PostGIS, Cron, and PLV8 to assist builders decide their favourite platform simply.

  • Builders can leverage Hyperscale (Citus) Fundamental as a cheap different for testing and rising workloads.
  • It presents a simplified developer expertise – with personalized upkeep home windows, burstable situations, zone-redundant excessive availability, and start-stop capabilities.
  • It presents enterprise-grade safety and compliance. Information is encrypted at relaxation and in movement.

c) Azure Database for MySQL

Azure Database for MySQL is a completely managed MySQL database. It’s extremely cost-effective and simple to arrange and operates. It helps excessive scalability. It helps the automation of key database server duties like upkeep, routine updates, backups, and safety. It helps a 48 p.c decrease value of possession with options like burstable situations, paying for storage solely when the database is stopped, and so on.

  • It’s constructed with the most recent MySQL Neighborhood Version utilizing present instruments, programming languages, and drivers.
  • It helps simple provisioning and scalability with AI-powered database monitoring and optimization options.
  • It helps in constructing resilient, responsive mission-critical apps with options like user-controlled upkeep home windows, IOPS provisioning, and server parameter configuration.

d) Azure SQL Managed Occasion

SQL Managed Occasion is an clever and scalable cloud database service by Microsoft that brings collectively the capabilities of SQL Server Engine, backed with a completely managed server.

It has built-in capabilities of Azure-arc to assist convey Azure innovation and cloud advantages on-premises.

  • It’s supported by the broadest SQL server compatibility on a completely managed service.
  • It presents value financial savings of as much as 55% in comparison with pay-as-you-go pricing when reused with SQL licenses with Azure Hybrid Profit.
  • It’s constructed on acquainted instruments and provides the identical expertise as supplied by SQL Server Codebase.

e) SQL Server on Digital Machines

SQL Server on Digital Machines helps customers migrate SQL Server workloads to the cloud. It presents twin advantages to the customers – permitting them to get the efficiency and safety of SQL servers and the pliability and hybrid connectivity of Azure. With it, builders can construct purposes with decrease TCO and get free built-in safety and automatic administration by registering digital machines with the SQL Server IaaS Agent extension.

  • It presents excessive availability and catastrophe restoration advantages.
  • It presents free, built-in safety and administration.

f) Azure Database for MariaDB

Azure Database for MariaDB is an enterprise-ready, totally managed group MariaDB service that can be utilized to simply deploy purposes to the cloud. With versatile pricing, you may select between the proper sources in your workloads. The built-in excessive availability and elastic scaling might help you obtain excessive enterprise continuity.

  • Leverages Azure IP benefit for getting unparalleled safety and compliance.
  • Works with all widespread open-source frameworks and languages.
  • Automated patching, backups, and built-in monitoring and safety – at no added value.

2.2 Non-relational Databases by Azure

a) Azure Cosmos DB

Azure Cosmos DB is a well-liked NoSQL database service that’s totally managed and serverless. It’s designed to help high-performance purposes of any dimension or scale. You will get assured single-digit millisecond efficiency and 99.999 p.c availability.

With multi-region writes and knowledge replication, it helps simple quick writes and reads wherever on this planet.

  • It makes use of Azure Synapse Hyperlink to get perception over real-time knowledge with no ETL (extract, rework, load).
  • Splendid for mission-critical purposes with 99.999 p.c availability and steady backup with point-in-time restore.
  • Quick and versatile app growth with SDKs for widespread languages.

b) Azure Cache for Redis

Azure Cache for Redis is an in-memory distributed database answer that helps you construct super-fast purposes and scale them simply. It’s totally managed and therefore helps automated patching, scaling, updates, and provisioning. It presents superior throughput and efficiency to deal with hundreds of thousands of requests per second with right down to sub-millisecond latency.

3. Google Cloud databases

3.1 Relational Cloud Databases

a) Cloud SQL

Cloud SQL is a completely managed relational database service for MySQL, PostgreSQL, and SQL Server. It comprises wealthy extensions, configuration flags, and developer ecosystems. Builders can automate common time-consuming server upkeep duties like provisioning and storage capability administration. It might additionally simply combine with different Google Cloud providers like BigQuery and GKE.


  • Helps knowledge encryption at relaxation and in transit for safety and compliance.
  • Might be arrange in minutes with the assistance of normal connection drivers and built-in migration instruments.
  • Automated failover help with simple replication and backups to supply most reliability.

b) Cloud spanner

Cloud Spanner is a completely managed relational database service by Google Cloud. It presents as much as 99.999% availability with limitless scaling help. Builders can begin small and scale as per their wants. The built-in automation capabilities assist eradicate guide duties like automated sharding. It’s globally distributed and helps ACID transactions.

  • Helps international scalability with all of the options and advantages supplied by SQL queries.
  • Presents 99.999 p.c availability for multi-regional situations.

c) AlloyDB for PostgreSQL

The totally managed PostgreSQL-compatible database service by Google is right for legacy purposes and enterprise workloads. It combines the perfect of Google with widespread open-source database engines for quicker scalability and availability. It presents 4x quicker efficiency than the usual PostgreSQL for transactional workloads.

  • ML-enabled autopilot methods to handle database patching, scaling, backups, and replication.
  • Presents excessive availability with 99.99% uptime SLA.
  • Presents 100x quicker analytical queries with zero impression on efficiency.

d) Naked-Steel Answer for Oracle

The totally managed database service by Google permits customers to convey their Oracle workloads simply to Google Cloud with minimal threat. Customers can leverage full Google Cloud options with lower than 2 ms (millisecond) latency. The billing and help are supplied by Google Cloud.

  • Helps end-to-end infrastructure administration together with compute, networking, and storage.
  • Helps totally managed knowledge middle operations like knowledge monitoring, energy, cooling, good hand help, and so on.
  • Helps demanding compliance necessities with business certifications like ISO, HIPAA, PCI DSS, and so on.

e) BigQuery

BigQuery is a relational database service supplied by Google Cloud. It’s a serverless and extremely scalable multi-cloud knowledge warehouse service. It’s generally used for constructing purposes that help multi-cloud analytics, real-time processing, and machine studying. It presents excessive availability with a 99.99 p.c uptime SLA.

  • Helps machine studying fashions to be operationalized immediately inside BigQuery utilizing easy SQL.
  • Helps multi-cloud knowledge evaluation that spans throughout cloud options like AWS and Azure.
  • Helps most safety with encryption by default and customer-managed encryption keys.

3.2 NoSQL databases by Google

a) Cloud Bigtable

Cloud Bigtable is a completely managed and scalable NoSQL database service designed for giant analytical and operational workloads. It’s a key-value database supplied by Google Cloud. It presents excessive availability with 99.999% SLA. It additionally helps constant sub-10 ms latency and handles hundreds of thousands of requests per second.

  • Its widespread use circumstances embrace advert tech, personalization, fintech, digital media, and IoT.
  • It’s designed with a storage engine – excellent for machine studying purposes.
  • It can be simply linked to different Google Cloud providers like BigQuery or the Apache ecosystem.

b) Firestore

Firestore is a document-based NoSQL database service by Google Cloud. It’s designed to help the event of wealthy purposes that may be scaled to satisfy any demand with no upkeep.

It might additionally seamlessly combine with Firebase and Google Cloud providers like Cloud Capabilities and BigQuery.

  • Helps real-time utility growth with options like built-in reside synchronization and offline mode.
  • Helps always-on knowledge safety with totally customizable safety and knowledge validation.
  • Helps pay-as-you-go pricing for eliminating upfront expenditures or underutilized sources.

c) Firebase Realtime Database

It’s one other widespread document-based database service that additionally falls into the class of NoSQL databases. It permits real-time syncing for JSON knowledge. It enables you to retailer and sync knowledge between customers in real-time. The customers can even collaborate throughout a number of gadgets – net or cellular.

  • Helps the event of serverless purposes with cellular and net SDKs.
  • Helps offline use with the assistance of native cache on the gadgets.
  • Presents user-based safety with the combination of the real-time database with Firebase Authentication.

Different non-relational database providers by Google Cloud

  1. MemoryStore:

It’s an in-memory database service that may scale back latency with a extremely scalable and safe service for Redis and Memcached. It may be used to construct purposes that present sub-millisecond knowledge entry. It might automate complicated duties for open-source Redis and Memcached like failover, monitoring, patching, and so on. to allow excessive availability.

2. MongoDB Atlas on Google Cloud

This non-relational database service by Google Cloud permits customers to run a completely managed MongoDB utility knowledge platform on Google Cloud inside a couple of clicks. They simply have to arrange, scale, and function MongoDB Atlas globally.

Fast Overview of AWS Vs Azure Vs Google Cloud: Database Comparability

Migration Capabilities: AWS Vs Azure Vs Google Cloud

Second, to the breadth of product choices, you must also take into account the migration help and capabilities supplied by every supplier. Let’s discuss concerning the migration help supplied by every:

AWS Database Migration

AWS presents a complete cloud database migration service that focuses on making migration simpler and quicker with minimal downtime. The migration helps:

Homogeneous database migrations – when the supply and goal database engines are the identical or are suitable with one another. For ex:

Supply: AWS

Heterogeneous database migrations – when the supply and goal database engines are completely different. On this case, code and schema transformation happen earlier than the information migration begins. This makes it a two-step course of.

Supply: AWS

AWS database migration service can be used emigrate each into and out of the cloud for growth functions like for deploying check, growth, or staging methods on AWS. AWS additionally helps consolidated database migration – the place a number of supply databases are consolidated right into a single goal database.

Greatest benefit: With help for heterogeneous migrations, prospects can simply migrate their databases to AWS Cloud and later change to a distinct DBMS, if required.

Azure Database Migration Service

The Azure database migration service primarily focuses on easing the database migrations from on-premises to Azure. These days, the service additionally contains the flexibility emigrate from non-Microsoft databases. It helps Microsoft SQL Server, MySQL, MongoDB, and PostgreSQL migration to Azure from on-premises and different clouds.

Supply: Microsoft

Greatest Benefit: Availability of PowerShell might help prospects save effort and time by automating the migration.

Google Cloud Platform Database Migration

GCP helps migration to Cloud SQL and just lately added help for MySQL and PostgreSQL, Oracle to PostgreSQL, and SQL Server Migrations. As it’s serverless, it takes away the complexities related to managing or monitoring situations. It additionally helps steady knowledge replication that interprets to minimal downtime.

As in comparison with AWS and Azure, GCP’s migration providers are nonetheless evolving.

Greatest Benefit: Serverless – so the shoppers do not need to fret concerning the migration sources or situations.

Pricing: AWS Vs Azure Vs GCP

Pricing is a crucial issue to think about earlier than selecting a database service. Because the database providers we mentioned on this weblog are cloud-based, probably the most acquainted pricing mechanism utilized by all suppliers is the usage-based or pay-as-you-go pricing. The pricing differs from vendor to vendor. A number of components like geography, computing sources, storage capability, I/O generated, and so on. are thought of when producing your cloud database pricing. Make sure to totally perceive the pricing construction supplied by every vendor earlier than investing to keep away from overpaying.

AWS Database pricing

The AWS databases are free to strive, and the shoppers have to pay just for the providers they use – with no minimal charges. You possibly can pay for providers utilizing On-demand or Reserved Situations (RI) which we are going to focus on shortly.

AWS presents a number of occasion sorts, and every occasion is priced in another way. If we discuss concerning the AWS RDS free tier – prospects get 750 hours per thirty days of the db.t2.micro situations when working on a single availability zone.

The pricing can also be affected by the database engine buyer chooses. We mentioned these earlier within the article – Amazon Aurora, PostgreSQL, MySQL, Oracle, Microsoft SQL Server, and MariaDB. The proprietary database of AWS – Amazon Aurora comes with serverless choices. Nevertheless, the pricing of storage per gigabyte in Aurora is barely costly.

One option to save prices is to go for RI pricing. In RI, you may reserve an occasion for 1-3 years. The long-term dedication helps you get some important low cost off on the on-demand price for that occasion. AWS RDS presents three completely different RI cost choices – no upfront, all upfront, and partial upfront. The worth for on-premises deployments like Amazon RDS on Outposts pricing is completely different.

AWS additionally presents an AWS pricing calculator to assist prospects calculate their month-to-month prices with AWS. Right here is an instance estimate of Amazon Aurora.

Supply: AWS

Azure Database Pricing

Azure SQL (the Platform-as-a-Service model of Microsoft SQL Server) presents two pricing fashions to its prospects – Database Transaction Models (DTU) and vCores.

Underneath the DTU pricing mannequin, Microsoft fees in accordance with the computing sources required to run the SQL database.

Beneath is the pricing for Azure SQL based mostly on Commonplace Service Tier in Central US – calculated by hour.

The worth varies in accordance with area, foreign money, hourly/month-to-month funds. Clients have to pay further prices for further storage.

If the client opts for Azure Hybrid Profit pricing, they’ll save on prices. Equally, you can too calculate pricing for vCores simply by the web site. If the client opts for vCore – in addition they get the choice to decide on between provisioned or serverless computing tier.

The pricing, as in comparison with AWS, is less complicated in Azure. Although in AWS, the complicated pricing is as a result of breadth of choices accessible.

Google Database Pricing

The pricing construction adopted by Google Cloud is sort of less complicated and simple to know as in comparison with the opposite two suppliers – AWS and Azure. The pricing will be damaged down into licensing, CPU, reminiscence prices, storage, and networking prices. When you speak about CPU and reminiscence pricing, the pricing will appear to be the beneath:

Supply: Google Cloud

Pricing based mostly on storage and community:

Supply: Google Cloud

Pricing based mostly on Licensing:

Supply: Google Cloud

The above pricing is calculated utilizing the SQL pricing calculator.

Observe: Pricing will differ in accordance with area, month-to-month/hourly cost, and different components as specified by the service supplier. The pricing on this article is just for reference functions.

Conclusion – AWS Vs Azure Vs Google Cloud

AWS leads with regards to the breadth of product choices beneath the DBaaS. Nevertheless, as a result of presence of so many providers, prospects face points associated to pricing calculations and selecting the right service.

Microsoft and Google lag by way of product breadth and migration capabilities as in comparison with AWS. Nevertheless, buyer opinions rank GCP Cloud SQL greater with regards to ease of migration and safety.

Azure’s pricing construction is a fancy situation for a lot of prospects as per business opinions. The plus factors are excessive availability and efficiency. Additionally, as it’s a SQL database, it’s appropriate for structured knowledge solely.

All three suppliers are market leaders with regards to cloud infrastructure and database providers. So, you may decide the one which intently resonates along with your utility growth wants and the funds of the undertaking.

Disclaimer: This text goals to offer details about the particular cloud database options of various distributors as accessible within the public area in September 2022 for common informational functions solely. Distributors could change their services or products pricing and options occasionally. Up to date data ought to be verified from the respective vendor’s web site, earlier than making any buy. Although we make our greatest endeavours to make sure that the knowledge is correct and updated, we don’t assure its 100% accuracy or timeliness.


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