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Amazon RDS for PostgreSQL

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

Introduction: Amazon RDS for PostgreSQL and PgHero are two popular tools used in managing PostgreSQL databases. Here are the key differences between them.

  1. Managed Service vs. Dashboard Tool: Amazon RDS for PostgreSQL is a managed service provided by AWS, offering automated management and scaling of PostgreSQL databases, while PgHero is a dashboard tool that allows users to monitor, analyze, and optimize their PostgreSQL database performance.

  2. Cost Structure: Amazon RDS for PostgreSQL follows a pay-as-you-go pricing model where users are charged based on the resource usage, storage, and additional features they utilize, while PgHero is an open-source tool that is free to use, with no subscription or licensing fees.

  3. Features and Functionality: Amazon RDS for PostgreSQL offers a wide range of features including automated backups, security settings, and scaling capabilities, while PgHero focuses specifically on performance monitoring, query optimization, and database health checks.

  4. Scalability: Amazon RDS for PostgreSQL provides automated scaling options to adjust resources based on workload demands, whereas PgHero does not offer built-in scalability features and relies on manual adjustments by the users.

  5. Integration with Other AWS Services: Amazon RDS for PostgreSQL seamlessly integrates with other AWS services such as Amazon CloudWatch for monitoring and Amazon S3 for backups, while PgHero is a standalone tool with limited integration options.

  6. Level of Control: With Amazon RDS for PostgreSQL, users have limited control over the underlying infrastructure and server configurations as it is managed by AWS, while using PgHero gives users greater control and flexibility in managing their PostgreSQL databases.

In Summary, the key differences between Amazon RDS for PostgreSQL and PgHero lie in their service model, cost structure, features, scalability options, integration capabilities, and level of control over the database environment.

Advice on Amazon RDS for PostgreSQL and PgHero

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 · 50K views

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

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    Easy setup, backup, monitoring
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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 PgHero?

    Postgres performance insights made easy.

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    What companies use Amazon RDS for PostgreSQL?
    What companies use PgHero?
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    What tools integrate with Amazon RDS for PostgreSQL?
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    What are some alternatives to Amazon RDS for PostgreSQL and PgHero?
    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