Just saw this comparison between JPA and JDO by DataNucleus themselves:- http://www.datanucleus.org/products/accessplatform_2_1/jdo_jpa_faq.html An eye-opener.
People claiming JDO is dead is not without merit. Here is what I read in the book Pro EJB 3 Java Persistence API: "Shortly thereafter Sun announced that JDO would be reduced to specification maintenance mode and that the Java Persistence API would draw from both JDO and the other persistence vendors and become the single supported standard going forward.". The author Mike Keith is the co-specification leader on EJB3. Of course he is a big supporter of JPA, but I doubt he is biased enough to lie.
It is true that when the book was published, most major vendors were united behind JPA rather than JDO, even though JDO does have more advanced technical features than JPA. It is not surprising because big players in the EE world such as IBM/Oracle are also big RDBMS vendors. More customers are using RDMBS than non-RDMBS in their projects. JDO was dying until GAE gave it a big boost. It makes sense because GAE data store is not relational database. Some JPA features does not work with bigtable such as aggregation queries, Join queries, owned many-to-many relationships. BTW, GAE supports JDO 2.3 while only support JPA 1.0. I will recommend JDO if GAE is your target cloud platform.
For the record, it is Google App Engine (GAE), so we play with the Google rules not with the Oracle/Sun rules.
Under it, JPA is not suitable for GAE, it is unstable and it does not work as expected. Neither Google is willing to support it but the bare minimum.
And for other part, JDO is quite stable in GAE and it is (in some extend) well documented by Google.
However, Google does not recommend any of them.
http://code.google.com/appengine/docs/java/datastore/overview.html
Low-level API will give the best performance and GAE is all about performance.
For example, add 10 entity
Python :68ms
JDO :378ms
Java Native :30ms
In race between JDO vs JPA I can only agree with the datanucleus posters.
First of all, and also most importantly, the posters of datanucleus know what they are doing. They are after all developing a persistent library and are familiar with data models other than the relational, e.g. Big Table. I am sure that id a developer for hibernate were here, he would have say: "all our assumptions when building our core libraries are tightly coupled to relational model, hibernate is not optimized for GAE".
Secondly, JPA is unquestionably in more widespread use, being a part of the official Java EE stack helps a bit, but that does not necessarily mean that it is better. In fact, JDO, if you read about it, corresponds to a higher level of abstraction than JPA. JPA is tightly coupled to the RDBMS data model.
From a programming stand point, using the JDO APIs is a much better option, because you are conceptually compromising a lot less. You can switch, theoretically to any data model of your desire, provided the provider you use supports the underlying database. (In practice you rarely achieve such a high level of transparancy, because you will find yourself setting your primary keys on GAE's object and you will be tying yourself to a specific database provider, e.g. google). it will still be easier to migrate though.
Thirdly, you can use Hibernate, Eclipse Link, and even spring with GAE. Google seems to have made a big effort to allow you to use the frameworks you are used to building your applications on. But what people realize when they build their GAE applications as if they were running on RDBMS is that they are slow. Spring on GAE is SLOW. You can google Google IO videos on this topic to see that it is true.
Also, adhering to standards is a good sensible thing to do, in principle I applaud. On the other hand, JPA being part of the Java EE stack makes people, at times, lose their notion of options. Realize, if you will, that Java Server Faces is also part of the Java EE stack. And it is an unbelievably tidy solution for web GUI development. But in the end, why do people, the smarter people if I may say so, deviate from this standard and use GWT instead?
In all of this, I have to sate that there is one very significant thing going for JPA. That is Guice and its convenient support for JPA. Seems that google was not as smart as usual in this point and are content, for now in not supporting JDO. I still think that they can afford it, and eventually Guice will engulf JDO as well,... or maybe not.
What I think is terrible about using JDO at the time of writing this is that the only implementation vendor is Datanucleus and the drawbacks of that is the lack of competition which leads to numerous issues like:
extensionsStackOverflowI'm always hoping for someone to start implementing the JDO specification themselves, may be then they'll offer something more and hopefully more free attention to the community and not always bothering about being paid for support, not saying that Datanucleus authors only care about commercial support, but I'm just saying.
I personally consider Datanucleus authors has no obligation whatsoever to Datanucleus itself nor it's community. They can drop the whole project at anytime and no one can judge them for it, it's their effort and their own property. But you should know what you are getting into. You see, when one of us developers look for a framework to use, you cannot punish or command the framework's author, but on the other hand, you need your work done ! If you had time to write that framework, why would you look for one in the first place ?!
On the other hand, JDO itself has some complications like objects life cycle and stuff which isn't very intuitive and common (I think).
Edit: Now I know also JPA enforces the object life cycle mechanism, so it looks like its inevitable to deal with persisted entities life cycle states if you wish to use a standard ORM API (i.e. JPA or JDO)
What I like most about JDO is the ability to work with ANY database management system without considerable effort.
Neither!
Use Objectify, because is cheaper (use less resources) and is faster. FYI: http://paulonjava.blogspot.mx/2010/12/tuning-google-appengine.html
Objectify is a Java data access API specifically designed for the Google App Engine datastore. It occupies a "middle ground"; easier to use and more transparent than JDO or JPA, but significantly more convenient than the Low-Level API. Objectify is designed to make novices immediately productive yet also expose the full power of the GAE datastore.
Objectify lets you persist, retrieve, delete, and query your own typed objects.
@Entity
class Car {
@Id String vin; // Can be Long, long, or String
String color;
}
ofy().save().entity(new Car("123123", "red")).now();
Car c = ofy().load().type(Car.class).id("123123").now();
ofy().delete().entity(c);
