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Advice on Database Labs, Google Cloud SQL for PostgreSQL, and Heroku Postgres
Jorge Perez
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.
Replies (2)
David Weinberg
Software Developer · | 1 upvotes · 47.9K views
Good balance between easy to manage, pricing, docs and features.
Max Musing
Founder & CEO at BaseDash · | 1 upvotes · 48.1K views
DigitalOcean's offering is pretty solid. Easy to scale, great UI, automatic daily backups, decent pricing.
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Learn MorePros of Database Labs
Pros of Google Cloud SQL for PostgreSQL
Pros of Heroku Postgres
Pros of Database Labs
- Superb customer service, and ready to go out of the box1
- Fastest, most effective support desk I've ever seen1
Pros of Google Cloud SQL for PostgreSQL
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Pros of Heroku Postgres
- Easy to setup29
- Follower databases3
- Dataclips for sharing queries3
- Extremely reliable3
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Cons of Database Labs
Cons of Google Cloud SQL for PostgreSQL
Cons of Heroku Postgres
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Cons of Heroku Postgres
- Super expensive2
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What is Database Labs?
We manage an optimized Postgres image. You focus on your core app, not on becoming a database administrator.
What is Google Cloud SQL for PostgreSQL?
With Cloud SQL for PostgreSQL, you can spend less time on your database operations and more time on your applications.
What is Heroku Postgres?
Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
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What companies use Database Labs?
What companies use Google Cloud SQL for PostgreSQL?
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What tools integrate with Database Labs?
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What are some alternatives to Database Labs, Google Cloud SQL for PostgreSQL, and Heroku Postgres?
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