What are the advantages of using a schema-free database like MongoDB compared to a relational database?

Question

I\'m used to using relational databases like MySQL or PostgreSQL, and combined with MVC frameworks such as Symfony, RoR or Django, and I think it works great.

But la

Answer 1

My experience with Postgres and Mongo after working with both the databases in my projects .

Postgres(RDBMS)

Postgres is recommended if your future applications have a complicated schema that needs lots of joins or all the data have relations or if we have heavy writing. Postgres is open source, faster, ACID compliant and uses less memory on disk, and is all around good performant for JSON storage also and includes full serializability of transactions with 3 levels of transaction isolation.

The biggest advantage of staying with Postgres is that we have best of both worlds. We can store data into JSONB with constraints, consistency and speed. On the other hand, we can use all SQL features for other types of data. The underlying engine is very stable and copes well with a good range of data volumes. It also runs on your choice of hardware and operating system. Postgres providing NoSQL capabilities along with full transaction support, storing JSON documents with constraints on the fields data.

General Constraints for Postgres

Scaling Postgres Horizontally is significantly harder, but doable.

Fast read operations cannot be fully achieved with Postgres.

NO SQL Data Bases

Mongo DB (Wired Tiger)

MongoDB may beat Postgres in dimension of “horizontal scale”. Storing JSON is what Mongo is optimized to do. Mongo stores its data in a binary format called BSONb which is (roughly) just a binary representation of a superset of JSON. MongoDB stores objects exactly as they were designed. According to MongoDB, for write-intensive applications, Mongo says the new engine(Wired Tiger) gives users an up to 10x increase in write performance(I should try this), with 80 percent reduction in storage utilization, helping to lower costs of storage, achieve greater utilization of hardware.

General Constraints of MongoDb

The usage of a schema less storage engine leads to the problem of implicit schemas. These schemas aren’t defined by our storage engine but instead are defined based on application behavior and expectations.

Stand-alone NoSQL technologies do not meet ACID standards because they sacrifice critical data protections in favor of high throughput performance for unstructured applications. It’s not hard to apply ACID on NoSQL databases but it would make database slow and inflexible up to some extent. “Most of the NoSQL limitations were optimized in the newer versions and releases which have overcome its previous limitations up to a great extent”.