Microservices and database joins

For people that are splitting up monolithic applications into microservices how are you handling the connundrum of breaking apart the database. Typical applications that I've worked on do a lot of database integration for performance and simplicity reasons.

If you have two tables that are logically distinct (bounded contexts if you will) but you often do aggregate processing on a large volumes of that data then in the monolith you're more than likely to eschew object orientation and are instead using your database's standard JOIN feature to process the data on the database prior to return the aggregated view back to your app tier.

How do you justify splitting up such data into microservices where presumably you will be required to 'join' the data through an API rather than at the database.

I've read Sam Newman's Microservices book and in the chapter on splitting the Monolith he gives an example of "Breaking Foreign Key Relationships" where he acknowledges that doing a join across an API is going to be slower - but he goes on to say if your application is fast enough anyway, does it matter that it is slower than before?

This seems a bit glib? What are people's experiences? What techniques did you use to make the API joins perform acceptably?


  • When performance or latency doesn't matter too much (yes, we don't always need them) it's perfectly fine to just use simple RESTful APIs for querying additional data you need. If you need to do multiple calls to different microservices and return one result you can use API Gateway pattern.

  • It's perfectly fine to have redundancy in Polyglot persistence environments. For example, you can use messaging queue for your microservices and send "update" events every time you change something. Other microservices will listen to required events and save data locally. So instead of querying you keep all required data in appropriate storage for specific microservice.

  • Also, don't forget about caching :) You can use tools like Redis or Memcached to avoid querying other databases too often.


It's OK for services to have read-only replicated copies of certain reference data from other services.

Given that, when trying to refactor a monolithic database into microservices (as opposed to rewrite) I would

  • create a db schema for the service
  • create versioned* views** in that schema to expose data from that schema to other services
  • do joins against these readonly views

This will let you independently modify table data/strucutre without breaking other applications.

Rather than use views, I might also consider using triggers to replicate data from one schema to another.

This would be incremental progress in the right direction, establishing the seams of your components, and a move to REST can be done later.

*the views can be extended. If a breaking change is required, create a v2 of the same view and remove the old version when it is no longer required. **or Table-Valued-Functions, or Sprocs.