PostgreSQL vs Redis

• As I mentioned before, Postgres has an incredibly flexible and simple-to-use user/role management system. First, there are users--login information so that you can hand out to individual users. Then, there are roles, which specify read and/or write access to all the tables that you can assign to users. Through this system, you can easily control who can read and update which tables, and the system is very well-tested, so there's no concern with users accessing or writing to data that they shouldn't be unless your Postgres admin really messes up!
• I could write pages on this and would need to reference the Postgres manual itself to do this justice, but Postgres is dang scalable! There are so many ways to scale it. Postgres has undergone active development by some of the brightest engineers for over 30 years now, and the result is that Postgres has so many ways you can scale it besides just upping the SSD and CPU and memory speed. You can scale reads horizontally through multiple slaves that handle all the reads. You can add highly optimized indices to your tables. You can change columns to JSONB types for super fast JSON queries. You can turn on special caches to bulk writes so they don't overwhelm the disk. Between those three options and other tips and tricks experienced Postgres admins have, you can get a lot out of them. There's a reason Yahoo stuck with Postgres for decades up until their main database even past the point of 4 Petabytes and 10k writes/second!
• Postgres, simply put, has achieved super-wide industry adoption (6% market share), which means it's really easy to integrate it into your stack and hire knowledgeable developers to service Postgres. All the major database libraries of the common web frameworks that I know are out there (e.g. Rails-ActiveRecord, Spring-Hibernate, Play Scala-Slick) have out-of-the-box deep Postgres support, with no extra configuration needed to get your web app to start reading and writing to Postgres. I also know many universities in the US include Postgres in their curriculum too (e.g. UC Berkeley). It's really easy to hire either new grads or experienced software engineers for positions that require Postgres knowledge.
• If you are comparing Postgres to MySQL and you want to use JSON, know that Postgres has better performance and features on indexing JSON blobs simply because Postgres beat MySQL to the JSON game by several years. I haven't used MySQL's JSON support before, but that's what my co-workers say (and it's true that Postgres definitely started support mySQL years earlier).

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• Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
• Reliable. With a proper multi-node configuration, it can handle failover instantly.
• Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
• Fast. We process tens of thousands of RPS and it doesn't skip a beat.

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• Deployment gets difficult for folks who are habituated with commercial databases.
• We cannot write our own database engine unlike MySQL.
• PostgreSQL do not allow us to execute batch of statement. we have to embed it in a function to achieve this.

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• We had some difficulty scaling Redis without it becoming prohibitively expensive.
• Redis has very simple search capabilities, which means its not suitable for all use cases.
• Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.

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• By pushing a lot of logic into database views and triggers, PostgreSQL provides the ability to write much slimmer and more maintainable controller code, reducing development costs.
• PostgreSQL's upsert capabilities enabled us to go to scale much more easily and quickly, allowing us to increase our number of customers.

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• Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
• Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
• Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.

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