MongoDB vs PostgreSQL

• Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
• Fast performance.
• It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
• There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
• Query syntax is pretty simple to grasp and utilize.
• Aggregate functions are powerful.
• Scaling options.
• Documentation is quite good and versioned for each release.

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• 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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• I love the idea of Map-Reduce native support in MongoDB. Admittedly I have not used it as much as I would like -- it always seems to trip me up.
• Recent additions to the aggregation queries have helped reduce (no pun intended) my need to better wield the weapon that is Map-Reduce.

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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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• Much faster development time.
• Price is fantastic compared to MSSQL when you consider OS costs and the entire package.
• Only negative to me is the lack of DBA skills for it, due to it being a new player in the field. I feel like that will get better as time moves on however.

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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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