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  5. Heroku Postgres vs MySQL

Heroku Postgres vs MySQL

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
Heroku Postgres
Heroku Postgres
Stacks607
Followers314
Votes38

Heroku Postgres vs MySQL: What are the differences?

  1. Deployment Process: Heroku Postgres offers a simpler deployment process compared to MySQL. With Heroku Postgres, you can easily provision and scale your database by using the Heroku CLI or the Heroku Dashboard. On the other hand, MySQL requires manual installation and configuration on your server, which involves more complexity and potential for errors.

  2. Managed Service: Heroku Postgres is a fully managed service, which means that Heroku takes care of the database infrastructure and maintenance tasks like backups, patches, and updates. On the other hand, MySQL requires manual management and administration, making it more time-consuming and requiring technical expertise.

  3. PostgreSQL vs. SQL: Heroku Postgres uses the PostgreSQL database, while MySQL uses the SQL database. Although both databases are widely used and offer similar functionality, there are some key differences. PostgreSQL has a more extensive list of advanced features, including support for complex data types, advanced indexing, and more robust transaction support. MySQL, on the other hand, is known for its simplicity and ease of use.

  4. Price Structure: Heroku Postgres offers a flexible pricing structure based on usage, allowing you to scale up or down as needed. You pay based on the resources and features you use. MySQL typically requires a more traditional licensing model, where you purchase a certain number of licenses or pay for the software upfront. This can make it less flexible and potentially more expensive, especially for smaller projects.

  5. Integration with Heroku Platform: Heroku Postgres is tightly integrated with the Heroku platform, allowing for smooth deployment and management of web applications. It provides seamless integration with other Heroku services, like the Heroku CLI, Heroku Dashboard, and Heroku Pipelines. MySQL, on the other hand, is not specifically designed for Heroku and may require additional configuration and setup.

  6. Ecosystem and Community: Both Heroku Postgres and MySQL have vibrant ecosystems and community support. However, MySQL has been around for a longer time and has a larger user base. This means that there are more resources, guides, and community-driven plugins available for MySQL. However, the PostgreSQL community is known for its technical expertise and extensive documentation.

In Summary, Heroku Postgres offers a simpler deployment process, is a fully managed service, uses PostgreSQL database, has a flexible price structure, tightly integrates with the Heroku platform, and has a strong community. MySQL, on the other hand, requires manual setup and management, uses SQL database, has a more traditional pricing model, may require additional configuration on Heroku, and has a larger user base.

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Advice on MySQL, Heroku Postgres

Kyle
Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

DecidedonPostGISPostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k
Comments
Ido
Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k
Comments
Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

  1. I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
668k views668k
Comments

Detailed Comparison

MySQL
MySQL
Heroku Postgres
Heroku Postgres

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.

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

-
High Availability;Rollback;Dataclips;Automated Health Checks
Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
129.6K
Stacks
607
Followers
108.6K
Followers
314
Votes
3.8K
Votes
38
Pros & Cons
Pros
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 490
    Open source
Cons
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes
Pros
  • 29
    Easy to setup
  • 3
    Extremely reliable
  • 3
    Follower databases
  • 3
    Dataclips for sharing queries
Cons
  • 2
    Super expensive
Integrations
No integrations available
PostgreSQL
PostgreSQL
Heroku
Heroku

What are some alternatives to MySQL, Heroku Postgres?

MongoDB

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.

PostgreSQL

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.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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