Amazon RDS for PostgreSQL vs Serverless

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Amazon RDS for PostgreSQL

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Serverless

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

Amazon RDS for PostgreSQL: * Set up, operate, and scale PostgreSQL deployments in the cloud. Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS; *Serverless:** The most widely-adopted toolkit for building serverless applications. 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.

Amazon RDS for PostgreSQL can be classified as a tool in the "PostgreSQL as a Service" category, while Serverless is grouped under "Serverless / Task Processing".

"Easy setup, backup, monitoring" is the top reason why over 22 developers like Amazon RDS for PostgreSQL, while over 10 developers mention "API integration " as the leading cause for choosing Serverless.

Serverless is an open source tool with 30.9K GitHub stars and 3.43K GitHub forks. Here's a link to Serverless's open source repository on GitHub.

Netflix, Instacart, and Product Hunt are some of the popular companies that use Amazon RDS for PostgreSQL, whereas Serverless is used by Plista GmbH, Droplr, and Hammerhead. Amazon RDS for PostgreSQL has a broader approval, being mentioned in 167 company stacks & 29 developers stacks; compared to Serverless, which is listed in 117 company stacks and 44 developer stacks.

Advice on Amazon RDS for PostgreSQL and Serverless

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

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Replies (2)
David Weinberg

Good balance between easy to manage, pricing, docs and features.

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Max Musing
Founder & CEO at BaseDash · | 1 upvotes · 49.6K views

DigitalOcean's offering is pretty solid. Easy to scale, great UI, automatic daily backups, decent pricing.

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Decisions about Amazon RDS for PostgreSQL and Serverless

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

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Pros of Amazon RDS for PostgreSQL
Pros of Serverless
  • 25
    Easy setup, backup, monitoring
  • 13
    Geospatial support
  • 2
    Master-master replication using Multi-AZ instance
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    3. Simplified Management for developers to focus on cod
  • 1
    Auto scale
  • 1
    5. Built-in Redundancy and Availability:
  • 1
    Openwhisk

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What is Amazon RDS for PostgreSQL?

Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

What is Serverless?

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.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Amazon RDS for PostgreSQL?
What companies use Serverless?
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What tools integrate with Amazon RDS for PostgreSQL?
What tools integrate with Serverless?

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What are some alternatives to Amazon RDS for PostgreSQL and Serverless?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
See all alternatives