In my previous post on Object-Relational Mapping tools (ORMs), I discussed various issues that I’ve faced dealing with the common ORMs out there today, including Hibernate. This included issues related to generating a schema from POJOs, real-world performance and maintenance problems that crop up. Essentially, the conclusion is that ORMs get you most of the way there, but a balanced approach is needed, and sometimes you just want to avoid using your ORM’s toolset, so you should be able to bypass it when desired.
One huge flaw in modern ORMs that I see though is that they really want to help you solve all your SQL problems. Why would I say this is a fault? Well, I believe that Hibernate et al just try too hard and end up providing features that actually hurt developers more than they help. The main thing I have in mind when I say this is query support. Actual support for complex queries that are easily maintained is seriously lacking in ORMs and not because they’ve omitted things — it’s just because the tools they provide don’t use SQL, which was designed from the ground up for exactly this purpose.
Experiences in Hibernate
It’s been my experience that when you use features like HQL, frequently you’re thinking about saving yourself a few minutes up front, and there’s nothing wrong with this in itself, but it can cause serious problems. It’s my experience that frequently you end up wanting or needing to replace HQL with something more flexible, either because of a bug fix or enhancement, and this is where the trouble starts.
I consider myself an experienced developer and I pride myself on (usually) not breaking things — to me, that is one of the hallmarks of good developers. When you’re faced with ripping out a piece of code and replacing it wholesale, such as replacing HQL with SQL, you’re basically replacing code that has had a history that includes bug fixes, enhancements and performance tweaks. You are now responsible for duplicating every change to this code that’s ever been made and it’s quite possible you don’t understand the full scope of the changes or the niggling problems that were corrected in the past.
Note that this also applies to all the other query methods that Hibernate provides, including the Query API, and through extension, query support within the JPA. The issue is that you don’t want a solution that is brittle or limited that it has to be fully replaced later. This means that if you need to revert to SQL to get things done, there’s a good chance you should just do that in the first place. This same concept applies to all areas of software development.
So what do we aim for if the basic querying support in ORMs like Hibernate isn’t good enough?
Criteria for a Solid ORM
Basically, my personal requirements for an ORM come down to the following:
- Schema first – generate your model from a database, not the other way around. If you have a platform-agnostic way of specifying DDL for the database, great, but it’s not a deal-breaker. Generating a database from some other domain-specific language or format helps nobody and results in a poorly designed schema.
- SQL only – if you want to help me avoid writing code, then generate/expose key-based, etc. lookups for me. Don’t ask me to use your query API or some new query language. SQL was invented for queries, so let me use the right tool.
- Give me easy ways to populate my domain objects from queries. This gives me 99% of what I’ll ever need, while giving me flexibility.
- Allow me to populate arbitrary Java beans with query results – don’t tie me into your registry of known types. This way, I can get ORM style results for custom queries.
- Don’t force me into using a typical transaction container like the one Hibernate or Spring provides – they are a disaster and I’ve never see a practical use for them that made any sense. Let me handle where connections/transactions are acquired and released in my application – typically this only happens in a few places with clear semantics anyway. This can be some abstracted version of JDBC, but let me control it.
- No clever/magic behaviour in my domain objects – when working with Hibernate, I spend a good time solving the same old proxy and lazy-loading issues. They never end and can’t be solved once-and-for-all which indicates a serious design issue.
Though these points seem completely reasonable to me, I’ve not encountered any ORMs that really meet my expectations, so at Carfey we’ve rolled our own little ORM, and this grants us the flexibility of never getting in the way of any versioned ORM libraries you may be using. But we use it in other settings as well and I have to say that weekend projects and just general development with what we have is far easier and faster than Hibernate or the other ORMs I’ve used. Even what I consider to be the best “ORM” out there, jOOQ, is lacking some basic features that would be rather simple to implement. What does it provide?
A Simple Utilitarian ORM
- Java domain classes are generated from a DB schema. There’s no platform-agnostic DDL yet, but it’s on our TODO list. Beans include support for child collections, FK references, but it’s all lazy and optional – the beans support it, but if you don’t use them, there’s no impact. Use IDs directly if you want, or domain objects themselves. Persistence handles persisting dirty objects only, and saves are only done when requested – no magic flush behaviour.
- Generated domain classes are for persistence only! Stick your business logic, etc. elsewhere.
- SQL is used for all lookups, including primary key fetches and foreign key relationships. If you need to enhance a lookup, just reference, extend or steal the generated SQL.
- Methods and SQL is generated automatically from any indexed column so they are all provided for you automatically and are typesafe. This also provides a warning to the developer – if a lookup is not available in your domain class, it may perform poorly since no index exists.
- Any domain class can be populated from a custom query in a typesafe manner – it’s flexible but easy to use.
- Improved classes hide the standard JDBC types such as
Statementfor ease of use, but we don’t force any transaction semantics on you, and you can always fall back to things like direct result set handling.
- Some basic required features like a connection pool, database metadata, and soon, database slave failover.
We at Carfey don’t believe we’ve created some incredible new ORM that surpasses every other effort out there, and there are many features we’d have to add if this was a public project, but what we have works for us, and I think we have the correct approach. And at the very least, hopefully our experience can help you choose how you use your preferred ORM wisely and not spend too much time serving the tool instead of delivering software.
As a final note, if you have experience with ORMs that meet my list of requirements above and you’ve had good experiences with it, we’d love to hear about it and would consider it for future Carfey projects.
1 thought on “Problems with ORMs Part 2 – Queries”
I have a similar opinion of ORMs and a similar wish list. I currently tend to use Apache Commons DbUtils, which is a SQL handling library rather than an ORM. I’m adding a few features to it via an extension that uses JPA’s annotations to enable more powerful mapping: https://github.com/mwanji/DbUtils-JPA.
I was thinking about using JPA’s @ManyToOne, etc. to add relation-mapping to DbUtils. How do you handle relations in Cafey? My initial project-specific attempts have led to code that feels uncomfortably complex.
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