Ask HN: Posgresql JSON or MongoDB?
I am building some app where part of it will have pretty much unstructured and changing data which I would like to dump as JSON. As a primary DB I am using PostgreSQL. I have never used JSON field type, but have used MongoDB before. I don't need anything fancy, 99% of the time it will be just storing and getting the data and querying by some fields of the JSON and it is of a scale that one instance of PostgreSQL could handle, nothing epic.
My question is, is PostgreSQL JSON field comparable to using MongoDB? Are there any limits or stumbling blocks that I should now about before choosing PosgresSQL for this? And is there an easy way to view and edit that JSON field by hand like I can when using Studio 3T app for MongoDB?(I know PostgreSQL DB apps are not the greatest for some reason..)
25 comments
[ 29.2 ms ] story [ 1606 ms ] threadI know nothing about Mongo, but one thing you won't get with Postgres is indexing inequality operations on arbitrary JSON fields. (You can accelerate equality and membership on arbitrary JSON fields using GIN indexes, and you can index inequality on fields known a priori with expression indexes, but not both.)
Also note that locking is at least at a per-row granularity, there is no way to contend only part of a JSON structure. Again, not sure what Mongo does here.
Likewise, updates are at a per-row granularity. This means that – assuming your JSON is indexed – you lose the benefit of HOT updates (https://github.com/postgres/postgres/blob/master/src/backend...), which can result in a lot of vacuuming and indexing overhead if you have an update-heavy workload. Best practice here would be to place indexed and unindexed parts of the JSON objects in different columns, to regain HOT update optimization for updates to unindexed values.
https://docs.mongodb.com/manual/faq/concurrency/
However that does result in much of the tooling not being able to support all of the features, unless they simply pass you down to SQL commands. Most of this is due to the MASSIVE feature set that Postgres supports. I use JetBrains DataGrip for Postgres work (which is SQL command based) , where as for MySQL i do most work with Sequel Pro (Typical MySQL GUI).
I am working on a reporting data warehouse right now using Postgres, and we are storing all data as JSONB objects as an abstracted "Entities" which link to other "Entities", where I am trying to get some of the advantages of triple stores / graph databases, while keeping compatibility with SQL / RDBMS which our developers and systems are used to integrating with. I think postgress is the best starting point for this project, simply due to the ability to manage the DB consistency inside the DB using triggers and stored procedures. While I am dealing with many different structures, I still need to be able to have a certain "sub-schema" of properties to be able to link the data to other data, which I can enforce using PGSQL.
However if your literally looking for something to Stash and retrieve a JSON object by primay key... your not going to get that much value from Postgres. There is some benefit if you already have pgsql infrastructure, as MongoDB can have some caveats around reliability (at least with the older versions). This is not that it is difficult to set it up in a mostly reliable fashion, it just requires some attention. However it will really come down to is your requirements, knowledge of the tools and use case.
There is literally no reason to ever use Mongo for a small-medium project anymore.
If you need tooling, check out the new pgAdmin 4: https://www.pgadmin.org/
And PostgreSQL 10 which is out in September will have logical replication added, which is rather useful in engineering a high-availability database.
None of the theoretical scaling benefits of Mongo outweigh the clusterfuck of maintenance, data inconsistency, and other general problems that shitty, shitty piece of software has.
I didnt mind mongo in a couple of my previous jobs. We never noticed data issues and we did some crazy things like generating mongologs on one machine and moving them to another manually .
It seems cockroachdb, aurora and cosmos are targeting similar use cases.
IMO RDS is perfect for most use-cases. I'd strongly encourage to try it out - it's highly performant and very reliable (uhhh... well...). Aurora has a significant edge under very significant loads (i.e. >300 concurrent clients), but can be slower under typical scenarios (0-100 concurrency).
[1] http://www.visualabs.com/
For that matter you could have both a JSON and a JSONB column. If you run into data that is not well-formed JSON then you will get an error trying to insert it into a JSONB column but it will INSERT just fine in a JSON column allowing you to deal with the well-formedness problem later.
And do make use of the rich selection of JSON and JSONB functions to create indexes on your tables because nothing speeds up querying like an index that lets you filter your data and only process the important subset.
PostgreSQL has been undergoing some heavy development in recent years as more and more companies shift away from proprietary commercial databases. There are several companies offering full commercial support for PostgreSQL if you need/want that.
This development work is leading to a constant stream of improvements, both performance and new features. This alone is a good reason to choose PostgreSQL. It now embraces both the SQL schema world and the schemaless NOSQL world in one database system.
https://www.mongodb.com/compare/mongodb-postgresql