Currently We have an enterprise application that works with spring and JPA.
Today we are planning our next generation server.
We are debating whether to use spring-data in our project? It seems to increase productivity and development times.
Are there any alternatives to spring-data to consider? Why not using spring and JPA alone?
What do you suggest?
Bear in mind we are starting to develop from scratch so no constraints are available other than:
we use mysql and mongoDB
we code in java
we will develop client side code in GWT.
Currently we have a layered architecture.
We have a Service layer and a manager layer, which takes care for persisting and business logic. Whoever built that didn't see a good reason to insert the third DAO layer.
There are some technical benefits of Spring Data over Spring + JPA, which in a pure SQL environment, I think give Spring Data an advantage:
Spring Data uses the same CrudRepository interface for all implementations, so you'll have less effort to switch between JPA to MongoDB
Spring Data saves you writing the same methods again and again. You just add the method to the interface and it'll generate it for you (e.g. UserRepository.findByUsername())
You can save boilerplate on REST implementations for JPA, MongoDB and others (see http://projects.spring.io/spring-data-rest/)
If you wanted to experiment with other persistence or indexing services, then there are Spring Data implementations for both mature and newer technologies such as for Neo4j, Hadoop, Solr, ElasticSearch, fuzzydb.
Given that you use MySQL and MongoDB, I think Spring Data is a strong candidate, as it allows developers to code to a single data access API (Spring Data) instead of two (JPA and the MongoDB Java Client).
Regarding the existing architecture, it sounds as though your manager layer is implementing either a Rich Domain pattern, or Active Record.
Spring Data is in my view very well suited to Rich Domain when combined with injection of services using Spring's #Configurable.
Lastly, I'd say that Spring Data also gives a significant advantage when needing to implement services for things like Spring Security and Spring Social, which use MongoDB or others instead of SQL.
We did this in the fuzzydb sample webapp that can be found here. (Disclaimer: I'm the currently sole recent committer on fuzzydb, and haven't touched it for a number of years, but we did have a live service, www.fridgemountain.com, based on that code, but neglected to promote it)
Related
Im not sure if i can use Spring Data JDBC also for complex models. My doubts arise especially cause in the Spring Data JDBC (3.0) documentation is written:
"There is a simple model of how to map entities to tables. It probably only works for rather simple cases. If you do not like that, you should code your own strategy. Spring Data JDBC offers only very limited support for customizing the strategy with annotations." https://docs.spring.io/spring-data/jdbc/docs/3.0.0/reference/html/#jdbc.why
I was expecting Spring Data JDBC is also working for more complex cases.
The limitations that rise from this simple model affect mostly legacy projects where you have a database that you maybe can't even change.
Spring Data JDBC is not intended to map an arbitrary database model to an arbitrary Java domain model, but to use a Domain Driven Design approach and construct the database accordingly.
But even in the cases where you hit the limitations of Spring Data JDBC you can always fall back on Springs JdbcTemplate without any conflict with the rest of your model which gets persisted by Spring Data JDBC.
The same is not true for JPA. Of course you can use JdbcTemplate with JPA as well, but you now have to very different approaches to persistence in your application which can and will interact in interesting ways due to JPA caching and dirty checking.
I therefore think Spring Data JDBC is an excellent choice for large application and complex models.
It's limitations will push you in the direction of better defined smaller modules and less complex models.
Is it possible to use Hibernate and RDBMS(Mysql, Postgres etc) with ReactiveCrudRepository instead of CrudRepository? I have tried some samples with Spring Data Jpa and Hibernate, but couldn't get it done. I was only able to find a few samples on ReactiveCrudRepository for MongoDB and cassandra.
Is it possible to use Hibernate and Mysql with ReactiveCrudRepository instead of CrudRepository?
TL;DR:
Not with Hibernate and MySQL, but with R2DBC and Postgres, Microsoft SQL Server or H2.
Take a look at Spring Data R2DBC.
Long Version
Why not JPA?
With Hibernate/JPA included this won't happen in the foreseeable future.
JPA is based on the idea that you load part of your data model into memory, manipulate the resulting object model and let JPA transform these changes.
All this within a single transaction.
This is kind of the opposite how one deals with a reactive store where you try to make atomic changes and try to decouple the loading, processing and storing and all this without blocking.
Why not JDBC?
So we have to look at the technology level below JPA: JDBC.
But JDBC is still blocking: You send a SQL statement to your database and then JDBC will block until you get the result.
And again this goes against the idea of reactive: Never block.
One could wrap this in a thread pool to mitigate this to some extent, but that is more of a workaround than a solution.
Why R2DBC?
There are some suitable drivers for some databases that could be used for reactive repositories.
But they are proprietary and thereby not a good basis for something that really should eventually work across all (relevant) relational databases.
For some time the Spring Data team hoped that ADBA would fill that gap.
But discussions on the mailing list made it clear that ADBA was not aiming for reactive but only for asynchronous.
Again not what we needed for a reactive repository abstraction.
So early in 2018 various people living at the intersection or reactive and relational decided that we need a standard for reactive database access.
R2DBC (Reactive Relational Database Connectivity)
is a proposal for such a standard.
The hope is that it either helps convincing Oracle to move ADBA to a reactive approach or if that doesn't happen it becomes the standard itself.
And with already three implementations available chances for the second option look promising.
R2DBC itself is mainly an SPI, i.e. an API that is to be implemented by database providers.
The SPI is designed in a way that puts minimal requirements on implementers.
But this also makes R2DBC somewhat cumbersome to use.
The idea is that other libraries will step up and build libraries designed for usability on top of that SPI, as it happened with JDBC.
Spring Data R2DBC
Spring Data R2DBC is one such library and it offers what you asked for: Support for ReactiveCrudRepository although it is independent of JPA/Hibernate and there is no support for MySQL yet.
State of the projects
Both R2DBC and Spring Data R2DBC didn't have a production release yet and it will take at least several months to get there.
Spring Data R2DBC just released the first milestone.
See the release article for its current capabilities.
R2DBC is on its 6th milestone. See the release article for details.
See also this answer: Why does Spring not provide reactive (non-blocking) clients for relational databases?
Original answer as a reference for archeologists:
As of now (Jan 2017) it is not possible.
The currently relevant release for the reactive part of Spring Data is Spring Data Kay M1 (You can check if there is a newer version available on the project home page)
And a blog post from the Spring Data team about that release and specifically the reactive parts in it starts with (emphasis mine):
Spring Data Kay M1 is the first release ever that comes with support for reactive data access. Its initial set of supported stores — MongoDB, Apache Cassandra, and Redis — all ship reactive drivers already, which made them very natural candidates for such a prototype.
The reason is that there is no standard non-blocking way to access a relational database. So only those that support this kind of API are supported right now.
One could implement a ReactiveCrudRepository using JPA or JDBC and delegate the work to a thread pool. This would provide an async API on the outside, but would still consume the resources for the Threads and block between independent data accesses, so only a small part of the benefits of the reactive approach would get realized.
Hibernate started a new Hibernate Reactive subproject for reactive streams support which provides Hibernate/JPA similar APIs to access RDBMS. But unfortunately at the moment, Spring Data does not support it. So there is no a ReactiveCrudRepoisoty for Hibernate Reactive.
But you can integrate Hibernate with Spring yourself and get reactive support.
Define a persistence.xml file, note the provider class must be specified as the one in Hibernate Reactive.
Declare a Mutiny.SessionFactory bean.
Then inject it in your repository class.
I have created a complete example demos Hibernate Reactive + Spring.
Update: Till now Spring team has no plan to support it, if you are willing to taste other framework, check Quarkus and Micronaunt, both have seamless Hibernate Reactive support. Check my Quarkus Hibernate Reactive example and Micronaut Hibernate Reactive example.
According to quote from previous answer
One could implement a ReactiveCrudRepository using JPA or JDBC and delegating the work to a thread pool. This would provide an async API on the outside, but would still consume the resources for the Threads and block between independent data accesses, so only a small part of the benefits of the reactive approach would get realized.
James Ward claims it can be non-blocking. I mean I asked him:
yeah ok, but isn't ScalikeJDBC-Async doing exactly the same? just putting query invocation into another thread pool?
and he replied
No because ScalalikeJDBC-Async uses https://github.com/mauricio... which is actually a non-blocking (NIO) JDBCish database driver.
source
So you can be reactive by replacing hibernate + spring data with postgresql-async (should work with mysql).
you could try with quarkus framework and panache mongo hibernate reactive repositories. https://quarkus.io/guides/mongodb-panache .It is easy manage a reactive repository over mongoDB, It is later but hope helps.
I recently worked on a project which uses Spring Data REST with Spring Boot. While it is GREAT to harness the power of Spring Data REST and build a powerful web service in no time, I have come to regret one thing: how tightly coupled the "presentation" layer (JSON returns) is to the underlying data structure.
Sure, I have used Projections and ResourceProcessors to manipulate the JSON, but that still does not completely sever ties with the database structure.
I want to introduce Controllers to the project, to integrate some of the "old" ways of building a web service in Spring. But how should I draw the line? I don't want to eradicate Spring Data REST from my project.
I am sure many of you have faced similar decisions, so any advice would be most appreciated!
I was advised to develop Neo4j extension because of poor performance due to the many calls to the Neo4j REST interface introduced by Spring Data Neo4j. For the good start I was able to run simply Neo4j extension from Neo4j documentation:
http://docs.neo4j.org/chunked/stable/server-unmanaged-extensions.html
Now I have to move some logic from my web service to Neo4j extension to make communication between them as small as possible. However, my web service is based on Spring Data Neo4j as well as Spring Data JPA, so to reuse my actual code I would like to use also Spring Data in my extension. I have found this documentation:
http://docs.spring.io/spring-data/data-neo4j/docs/current/reference/html/reference_neo4j-server.html
but it is not clear for me and there is no working example. Is there any sample code with such integration?
There is a great example on using SDN in an unmanage extension, see http://inserpio.wordpress.com/2014/04/30/extending-the-neo4j-server-with-spring-data-neo4j/.
I have not used Spring Data before but I've used Hibernate ORM a number of times for MySQL based application. I just don't understand which framework to choose between the two for a MongoDB based application.
I've tried searching for the answer but I can't find the answer which does a comparison between the two in a production environment. Has anyone found problems working with these two frameworks with MongoDB ?
Disclaimer: I am the lead of the Spring Data project, so I'll mostly cover the Spring Data side of things here:
I think the core distinction between the two projects is that the Hibernate OGM team chose to center their efforts around the JPA while the Spring Data team explicitly did not. The reasons are as follows:
JPA is an inherently relational API. The first two sentences of the spec state, that it's an API for object-relational mapping. This is also embodied in core themes of the API: it talks about tables, columns, joins, transactions. Concepts that are not necessarily transferable into the NoSQL world.
You usually choose a NoSQL store because of its special traits (e.g. geospatial queries on MongoDB, being able to execute graph traversals for Neo4j). None of them are (and will be) available in JPA, hence you'll need to provide proprietary extensions anyway.
Even worse, JPA features concepts that will simply guide users into wrong directions if they assume them to work on a NoSQL store like they were defined in JPA: how should a transaction rollback be implemented reasonably on top of a MongoDB?
So with Spring Data, we chose to rather provide a consistent programming model for the supported stores but not try to force everything into a single over-abstracting API: you get the well-known template implementations, you get the repository abstraction, which works identical for all stores but lets you leverage store-specific features and concepts.
Disclaimer: I'm one of the Hibernate OGM developers so I'll try to provide some of the reasons behind it.
Hibernate OGM provides Java Persistence (JPA) support for NoSQL solutions. It reuses Hibernate ORM’s engine but persists entities into a NoSQL datastore instead of a relational database. It also aims to provide access to specific datastore features when JPA does not have a good fit.
This approach is interesting for several reasons:
Known semantic and APIs. Java developers are already familiar with JPA, this means that one won't have to learn lower level API. It also supports both HQL and native backend-queries.
Late backend choice. Choosing the right NoSQL datastore is not trivial. With Hibernate OGM you won't have to commit to a specific NoSQL solution and you will be able to switch and tests different backends easily.
Existing tools and libraries. JPA and Hibernate ORM have been around for a while and you will be able to reuse libraries and tools that uses them underneath.
Most of JPA logical model fits. An example of a good fit is #Embedded, #EmbeddedCollection and #Entity (that can be a node, document or cache based on the datastore of choice). Admittedly, annotation names might be strange because you will also have to deal with #Table and #Column.
JPA abstracts persistence at the object level, leaving room for a lot of tricks and optimizations. We have several ideas planned, like polyglot persistence: storing data in several data stores and use the best one for a specific read job.
The main drawback is that some of the concepts of JPA are not easily mapped to the NoSQL world: transactions for example. While you will have access to transaction demarcation methods, you won't be able to rollback on data stores that don't support transactions natively (transactions, in this case, will be used to group operations and try to optimize the number of calls to the db).
Also, if your dataset is by nature non domain model centric, then Hibernate OGM is not for you.
One can Just go with SpringData. If you recall Spring ORM also uses some JPA things such as Entity, Transaction and provided best commination of things from JPA and Hibernate APIs a. Spring community will take care in future versions if JPA is getting more matured for NoSQL.
Though it is not the main reason. Most of reasons are described by #Oliver Drotbohm.
Read more documentation of SprinData and further analyse your data model, scalability on continuity/growth of data store, find best fit for your solution and consider suggestion given by #Davide.
Many cases SpringData has got more success rate than JPA while integrating with MongoDB.