StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon RDS for Aurora vs Serverless

Amazon RDS for Aurora vs Serverless

OverviewDecisionsComparisonAlternatives

Overview

Amazon Aurora
Amazon Aurora
Stacks807
Followers745
Votes55
Serverless
Serverless
Stacks2.2K
Followers1.2K
Votes28
GitHub Stars46.9K
Forks5.7K

Amazon RDS for Aurora vs Serverless: What are the differences?

  1. Scalability: A key difference between Amazon RDS for Aurora and Serverless is the scalability options they offer. With Amazon RDS for Aurora, you can scale your database vertically by increasing the instance size or horizontally by adding replicas. On the other hand, Serverless automatically scales your database based on the workload, allowing for seamless handling of variable workloads without manual intervention.

  2. Pricing: The pricing model for Amazon RDS for Aurora and Serverless differs. Amazon RDS for Aurora is billed based on the instance size and storage usage, while Serverless is billed based on actual consumption per second. This makes Serverless a cost-effective option for applications with unpredictable or irregular traffic patterns.

  3. Capacity: In terms of capacity, there is a difference between Amazon RDS for Aurora and Serverless. Amazon RDS for Aurora allows you to choose the instance size that meets your capacity needs, while Serverless automatically scales the capacity to match the workload, providing on-demand resources as needed.

  4. Startup Time: Another important difference is the startup time of the database. With Amazon RDS for Aurora, the database instance needs to be provisioned and started before it can be accessed. In contrast, Serverless has a faster startup time as it doesn't require any upfront provisioning, allowing for quicker access to the database.

  5. Persistent Connections: Amazon RDS for Aurora supports persistent connections, which can help improve performance and reduce connection overhead. In contrast, Serverless doesn't support persistent connections, which may impact certain applications that rely on long-lived connections.

  6. Performance: When it comes to performance, Amazon RDS for Aurora and Serverless have different characteristics. Amazon RDS for Aurora offers consistent performance for steady workloads, while Serverless can handle bursty workloads efficiently by automatically scaling up and down based on demand.

In summary, Amazon RDS for Aurora and Serverless differ in terms of scalability options, pricing model, capacity management, startup time, support for persistent connections, and performance characteristics.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Amazon Aurora, Serverless

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

357k views357k
Comments

Detailed Comparison

Amazon Aurora
Amazon Aurora
Serverless
Serverless

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

High Throughput with Low Jitter;Push-button Compute Scaling;Storage Auto-scaling;Amazon Aurora Replicas;Instance Monitoring and Repair;Fault-tolerant and Self-healing Storage;Automatic, Continuous, Incremental Backups and Point-in-time Restore;Database Snapshots;Resource-level Permissions;Easy Migration;Monitoring and Metrics
-
Statistics
GitHub Stars
-
GitHub Stars
46.9K
GitHub Forks
-
GitHub Forks
5.7K
Stacks
807
Stacks
2.2K
Followers
745
Followers
1.2K
Votes
55
Votes
28
Pros & Cons
Pros
  • 14
    MySQL compatibility
  • 12
    Better performance
  • 10
    Easy read scalability
  • 9
    Speed
  • 7
    Low latency read replica
Cons
  • 2
    Vendor locking
  • 1
    Rigid schema
Pros
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    Auto scale
  • 1
    Openwhisk
Integrations
PostgreSQL
PostgreSQL
MySQL
MySQL
Azure Functions
Azure Functions
AWS Lambda
AWS Lambda
Amazon API Gateway
Amazon API Gateway

What are some alternatives to Amazon Aurora, Serverless?

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

AWS Lambda

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Azure Functions

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Google Cloud SQL

Google Cloud SQL

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

ClearDB

ClearDB

ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Azure SQL Database

Azure SQL Database

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase