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In my experience, keeping BL out of the DB is a practical concern, not a dogmatic one. Usually there are two things: 1. Performance. Business logic is usually
by l_t 7y ago
In my experience, keeping BL out of the DB is a practical concern, not a dogmatic one.
Usually there are two things:
1. Performance. Business logic is usually horizontally scalable, databases are usually not. You want to pull as much BL out of the database as possible, and put it into stateless microservices so they can be scaled.
2. Version control and deploying changes to business logic. Business logic changes frequently. Do you want to have to be making that frequent of changes to your database? Do you have practices around safe deployment and code review for stored procedures?
I've worked at a place where there was lots of business logic (millions of LOC) stored "in the database". In this case the database was MUMPS. It can be done, and it can be pleasant. The catch is that vertical scaling is the only option, and you have to spend years building your own tooling from scratch.
I think the line between database and code is destined to become even more blurred, but not by bringing the code down into the database, but by lifting more and more database concepts up into "application space" as distributed computing becomes more normalized.
- paragraft 7y agoYeah the performance point is interesting, and I think it has merit in a well-defined scope. The idea of bringing DB concepts up is something I've seen done, but it wasn't a pleasant experience overall and I think everyone involved is regretful that we went down that path. It's a good story though. Ramble starts: The system was an enterprise-focused offering with weak product management, so in the early growth-oriented days of the company ended up saying "yes" to a lot of feature requests that we probably shouldn't have. Where this particularly impacted was the permissions system, which evolved over time from an ACL with odd warts to also include a bolted on hierarchy of users and their objects, and then a role based system, and then all sorts of enterprise-level oddities like cross-links in the hierarchy, shared subhierarchies, roles that could appear at multiple hierarchy points, virtual ACLs that behaved slightly differently etc. So potentially a large number of different access paths between a given user and resource. Years ago, when this mess was starting to expand it was decided it was too hard to model this in the DB (and really that should've been a giant red flag), so the new approach was to load each customer's dataset up into an application server that would handle the BL, crucially including the permission logic. It very much wasn't stateless, as you mention, but I'm not sure how it could've been really, given you needed so much loaded up from the DB in order to make these permission decisions. Would've avoided a lot of headache if it had... The consequence though of using this write-through in-memory cache was it became the source of truth. The chief problem this led to was that shift into application land was a bell that couldn't be unrung. Everything others in this thread have complained about seeing BL spread across all sorts of SPs in a DB happened here, just in application code (which again hints I guess that the chief problem is architectural and lack of governance, not a wrong-layer problem). Nobody could properly describe the permissions system in response to support requests without a lot of code scouring, let alone hold it in their heads. Even worse, as the application grew in size and needs, we found we still needed things we had left behind in the DB. A couple of smart devs working on the core service, because they were smart and trusted, convinced themselves that what we needed was an in-memory transaction system for managing this in-server cache (by now the core was being called the Object Cache, a name so generic that it also should've been a red flag). So a couple of years went into implementing a technically impressive reimplementation of a transaction system. Meanwhile the system as a whole was well past the point of being needed to split up into multiple services, so a grand goal was set of moving the Object Cache into a standalone service: the Object Service. Slap an OData API on it, and then leave that API open for all internal teams to hit. By this point the core team who owned this was starting to become well aware they had fallen into a bad pit of reimplementing the Postgres DB everything still sat on: transactions, generic query API, configurable in-memory indexes for each type of object, partition loading logic for the timeseries sets, user permissions etc. Worse, the generic query API (and this is what's ultimately turned me off OData/GraphQL etc for cross-team interfaces) ran into all the same problems as an SQL interface - people in other teams would always be coming up with brand new queries your indexes hadn't anticipated, forcing new work on the keepers of the cache to support. The way forward probably would've been to leave the permissions structure in place and pull as much as possible out of the service/cache into separate stanadlone services, i.e leave the objects in the object cache little more than just IDs you could look up elsewhere for actual attributes. We'll never really know though: it was recently decided to put the whole thing into maintenance mode, partially because nobody has the political will to fix the thing and its complexity. I've thought a lot about the lessons of this system and where it went wrong, and I trace it ultimately to forging ahead with a permissions system (i.e core BL) that couldn't be modelled in the DB. I think that doomed us to what I'd ultimately name second system syndrome (i.e the whole stack above slowly evolved into a poor Postgres clone). Perhaps if we had been ruthless in going to a CQRS design or similar very early on we could've pulled it off (which would again demand stateless services above) we could've pulled it off. I think a big takeway for me was to not take for granted the good things a RDBMS is giving you, especially transactionality. I think I'd bias these days towards looking for ways to scale up the powers the DB gives you (even if it involves pushing external integrations into the DB maybe via some funny FDW or transaction log integrations, or maybe using a tiered solution of DBs, one layer as the storage layer and another layer above that acting as coherent transctors, a little bit similar to Datomic's internal structure), rather than rushing toward replicating core DB functionality in application code, which can be tempting initially as the easier-looking solutions. I think I might blog about this when the system's properly retired and the involved can look back and laugh rather than cringe...