Software Alternatives, Accelerators & Startups

Amazon Aurora VS Google Cloud SQL

Compare Amazon Aurora VS Google Cloud SQL and see what are their differences

Amazon Aurora logo Amazon Aurora

MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.

Google Cloud SQL logo Google Cloud SQL

Google Cloud SQL is a fully-managed database service that makes it easy to set-up, maintain, manage and administer your MySQL database.
  • Amazon Aurora Landing page
    Landing page //
    2023-03-17
  • Google Cloud SQL Landing page
    Landing page //
    2023-09-18

Amazon Aurora features and specs

  • High Performance
    Amazon Aurora is designed to provide up to five times the throughput of standard MySQL and three times the throughput of standard PostgreSQL databases.
  • Scalability
    Aurora scales storage automatically, growing from 10GB up to 128TB with no downtime. This automatic scaling makes it ideal for applications with fluctuating workloads.
  • High Availability and Durability
    Aurora automatically replicates six copies of data across three availability zones and continuously backs up data to Amazon S3, ensuring durability.
  • Security
    Aurora offers multiple layers of security including network isolation using Amazon VPC, encryption at rest using keys that you create and control through AWS Key Management Service (KMS), and encryption of data in transit using SSL.
  • Fully Managed
    Aurora is fully managed by AWS, which automates time-consuming administrative tasks such as hardware provisioning, database setup, patching, and backups.
  • Compatibility
    Aurora is compatible with MySQL and PostgreSQL, making it easier to migrate existing applications to Aurora with minimal changes.

Possible disadvantages of Amazon Aurora

  • Cost
    Aurora can be more expensive than traditional RDS instances, particularly for workloads that do not fully utilize its high performance and scalability features.
  • Complexity
    The numerous features and configurations can make Aurora complex to manage and tune, especially for those who are not familiar with AWS services.
  • Vendor Lock-in
    Adopting Aurora ties you into the AWS ecosystem, which can make it difficult to migrate to other cloud providers or on-premises systems.
  • Cold Start Latency
    Aurora Serverless can experience latency during cold starts, which can be problematic for applications requiring instant scalability.
  • Limited to AWS Environment
    Aurora is only available within the AWS environment, which can be limiting if your infrastructure spans multiple cloud providers.

Google Cloud SQL features and specs

  • Fully Managed Service
    Google Cloud SQL handles maintenance, backups, and updates, allowing developers to focus on application development rather than database management tasks.
  • Scalability
    Easily scale vertically by upgrading to more powerful machine types or horizontally to handle increased workload without manual intervention.
  • High Availability
    Google Cloud SQL offers automatic failover, replication, and backup, ensuring minimal downtime and data preservation in case of failures.
  • Security
    Provides multiple layers of security including encryption at rest and in transit, along with built-in firewall rules and IAM policies for robust access control.
  • Integration
    Seamlessly integrates with other Google Cloud services like BigQuery, Compute Engine, and Google Kubernetes Engine, supporting complex architectures and workflows.

Possible disadvantages of Google Cloud SQL

  • Cost
    It can be more expensive than self-managed solutions, especially as the need for additional resources and scaling arises.
  • Vendor Lock-in
    Relying on Google Cloud SQL could create dependency on the Google Cloud ecosystem, which might complicate future migration to other platforms.
  • Customization Limitations
    Being a managed service, it has constraints on certain configurations and customizations that might be essential for specific use cases.
  • Latency
    There might be increased latency compared to on-premises solutions, particularly for applications requiring very low-latency data access.
  • Compliance
    While Google Cloud SQL complies with many regulatory standards, some industries with highly specific requirements may find it unsuitable.

Amazon Aurora videos

Introduction to Amazon Aurora - Relational Database Built for the Cloud - AWS

More videos:

  • Review - Amazon Aurora Global Database Deep Dive
  • Review - What's New in Amazon Aurora - AWS Online Tech Talks

Google Cloud SQL videos

GCP | Google Cloud SQL | Cloud SQL Features , Read Replicas & High Availability | DEMO

Category Popularity

0-100% (relative to Amazon Aurora and Google Cloud SQL)
Databases
76 76%
24% 24
Relational Databases
84 84%
16% 16
NoSQL Databases
77 77%
23% 23
Tool
100 100%
0% 0

User comments

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Social recommendations and mentions

Amazon Aurora might be a bit more popular than Google Cloud SQL. We know about 23 links to it since March 2021 and only 18 links to Google Cloud SQL. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon Aurora mentions (23)

  • Building a RAG System for Video Content Search and Analysis
    Using Amazon Bedrock to invoke Amazon Titan Foundation Models for generating multimodal embeddings, Amazon Transcribe for converting speech to text, and Amazon Aurora postgreSQL for vector storage and similarity search, you can build an application that understands both visual and audio content, enabling natural language queries to find specific moments in videos. - Source: dev.to / 25 days ago
  • Everyone Uses Postgres… But Why?
    Cloud deployment: PostgreSQL can be deployed in the cloud with AWS RDS, Amazon Aurora, Azure Database for PostgreSQL, or Cloud SQL for PostgreSQL. - Source: dev.to / 6 months ago
  • Announcing the public beta for dedicated clusters
    Today, our Postgres databases are Amazon Aurora instances. You can trust that your database will have the scalability, reliability and security that AWS is known for. With dedicated clusters you can configure both the Postgres engine version, cluster class and number of replicas for failover and query distribution. - Source: dev.to / 9 months ago
  • Vector database is not a separate database category
    As far as the big players are concerned, Google offers AlloyDB (https://cloud.google.com/alloydb) while Amazon offers Aurora (https://aws.amazon.com/rds/aurora/). - Source: Hacker News / over 1 year ago
  • Building realtime experiences with Amazon Aurora
    Aurora is a managed database service from Amazon compatible with MySQL and PostgreSQL. It allows for the use of existing MySQL code, tools, and applications and can offer increased performance for certain workloads compared to MySQL and PostgreSQL. - Source: dev.to / almost 2 years ago
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Google Cloud SQL mentions (18)

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What are some alternatives?

When comparing Amazon Aurora and Google Cloud SQL, you can also consider the following products

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

MySQL - The world's most popular open source database

Oracle DBaaS - See how Oracle Database 12c enables businesses to plug into the cloud and power the real-time enterprise.

SAP HANA - SAP HANA is an in-memory, column-oriented, relational database management system.

SQLite - SQLite Home Page

Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.