3 Matching Annotations
  1. Dec 2016
    1. The real benefit of JSONB: IndexesWe want our application to be fast. Without indexes, the database is forced to go from record to record (a table scan), checking to see if a condition is true. It’s no different with JSON data. In fact, it’s most likely worse since Postgres has to step in to each JSON document as well.

      This solves the problem of the last implementation I handled where json (not jsonb) data was stored in postgres

    1. When you’re picking a data store, the most important thing to understand is where in your data — and where in its connections — the business value lies. If you don’t know yet, which is perfectly reasonable, then choose something that won’t paint you into a corner. Pushing arbitrary JSON into your database sounds flexible, but true flexibility is easily adding the features your business needs.

      This is an old article but valuable thinking for system design.

    1. The BSON format used by MongoDB is limited to a maximum of 64 bits for representing an integer or floating point number, whereas the JSONB format used by Postgres does not have this limit. Postgres provides data constraint and validation functions to help ensure that JSON documents are more meaningful: for example, preventing attempts to store alphabetical characters where numerical values are expected. MongoDB offers automatic database sharding for easy horizontal scaling of JSON data storage. Scaling of Postgres installations has often been vertical. Horizontal scaling of Postgres is also possible, but tends to be more involved or use an additional third party solution. MongoDB also offers the possibility of increasing write throughput by deferring writing to disk. The tradeoff is potential loss of data, but this may suit users who have less need to persist their data.

      Good pros and cons of Mongo vs Postgres for JsonB