Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed last month.
Improve this question
I am using Java language.I have to use ORM framework with MongoDb as Database.I have two options Morphia or Spring Data Mongo support.As far i am able to get details , it has been found Spring Data Mongo is better to use since:
1)It provides better DAO out of box inbuilt classes.
2)It has larger community base.
Are there any performance based differences between the two.And if there which one is better in which condition.Also i have requirement of multitenancy .After little search i found that there is very simple custom implementation in Spring Data Mongo to do the same.But in Morphia it is somewhat difficult.Does achieving multitenancy in Morphia diificult(where we need to write a lot of boiler plate code)
I have been using Spring-data and I guess I feel somehow it lags as far as maturity is concerned.
It's good for all the practical purposes but the features mongo provides in it's full glory, Spring-data is slow to map that as a driver specially when it comes to aggregation.
As far as performance goes, Spring-data doesn't lag imo.
Sometime I get weird behaviors. Some of their annotation silently doesn't work at some places and for my life I cannot figure out why?
But as an overall implementation it's quite helpful in the way that it provides a robust structure on which your application can grow. It also is easy if you are coming from SQL background since you can draw a parallel between jdbcTemplate and mongoTemplate (though one needs to be cautious)
I seriously considered using Morphia, but dropped the idea since spring-data was providing a more structured ways. Looks like in Morphia we would have to implement some structure on our own which has pros and cons but You usually want to avoid doing it. Since there is a risk of boiler-plate codes, there is a learning curve for 'your' structure for new members.
On the pros side, I am sure Morphia provides more extensiblity leading you to enjoy the ability to suck most out of mongo features. It also is lightweight compared to Spring data.
Morphia is the way to go. Pretty stable, very good Play integration and offers access to all Mongo driver features if you need more torque. Reference resolution, entity embedding are working as expected. You get lifecycle annotations too, which are pretty useful for boilerplate persistence code.
I personally like spring-data because of the hades project... You don't need to implement the DAOs. You just write the interface and spring data automatically provides it to you. However Spring Data Mongodb implementation seems a little buggy in my initial trial. If you have hard dates and is working on a production quality product, probably it is wise to choose Morphia.
Related
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 3 years ago.
Improve this question
Iam looking for a performant way and readable way to implement a full-text-search. I have a lot of requirements for the serach. See this list below.
Requirements
Peformance
My database growing up very fast. Load all data into HEAP an doing some .stream()-magic is not an option. The search should be performed by the DBMS.
Readability
I need easy a solution. A complex query like this How to implement simple full text search in JPA (Spring Data JPA)? (see option #2) is also not a solution. I would need some JOINs and the resulting query is to complex.
The overhead with an "index-field" is also not possible (to much joined data).
Concurrency
The application need to be scalable (with n-instances), so a solution with Lucene is not very good here is an example
no mixing of technologies
I dont want to mix the logic into different systems. This means, the whole search-logic should be defined in Java. A combination of the Java-Logic with views or sql-functions should be avoided.
Discovered options yet
QueryDsl
This is my old solution. But its very complex and produced a lot of problems with the automated generated classes.
Lucence
I like this. But there only one big problem: The index. Keep the index up2date on all instances is going a bit too overkill.
Very long #Query
The resulting query getting to complex to handle it.
Java.stream()...
// kinda
getAllUsers().stream()
.filter(user -> user.getName().contains(searchTerm)
|| user.getSex().contains(searchTerm)
|| user.getAge().toString().equals(searchTerm)
|| ...)
I have to much data to do that. So this solution will also not scale well.
Specification Interface
My preferred solution. But maybe there are other (and better) solutions?
SearchFiled or similar
Too many JOINS. Too much data.
?
Question
What are your expericenes with full-text-search in a Spring-Boot-Application? Do you know a solution that met my requierements?
If you have reached till Lucene, then a step further is Solr. I haven't used the options you have mentioned above, but I have certainly worked with Solr and can safely say that it is worth a try, for speed and ease of use.
Out of the four constraints you have put, the first three are taken care of, I feel with Solr.
Performance: Solr is a proven candidate in this area.
Readability: I assume you mean readability of code. Though this depends upon the code and design are done, the Solr part is quite friendly to code, understand and maintain because of the lack of JOIN and other RDBMS concepts.
Concurrency: From the official documentation at lucene.apache.org/solr:
Both Lucene and Solr were designed to scale to support large implementations with minimal custom coding.
and that Solr can do the following in this regard:
distributing an index across multiple servers
replicating an index on multiple servers
merging indexes
no mixing of technologies: With the option of using Solr, you have at least two technologies: Java and Solr. I am not sure if you wanted to keep your solution to pure Java/JEE. If that is the case, then this may not satisfy that need.
However, this requirement:
The search should be performed by the DBMS.
is surely not taken care of.
Also, can't think of a way other than a custom design for this:
Keep the index up2date on all instances is a bit overkill.
A warning: It may take some time to get a good grasp on Solr if you are new to it.
you may consider apache solr for searching
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 6 years ago.
Improve this question
Recently, I have started working on mongo. As the whole concept of mongodb is schemaless and document-oriented, how can I transition relationships to entities?
I have used hibernate ORM in java for mapping objects to tables. Is there a need to do the same for mongodb?
Things which restrict me from using OGM:
Once the Java Entity is mapped to a collection in mongo, will the concept of mongo being schemaless still be valid. In this case I have to map member variables to keys of that collection. Also if a mongo collection is supposed to contain nested objects or an array of objects, then what?
Hibernate has launched their OGM for NoSQL databases recently (January 2015).
Could anyone help me out with the decision to choose OGM for mongo?
Edit: Kundera is no longer maintained. Please use alternatives.
Of course, ORMs are easy to use and many of them allow us to use SQL or JPQL for querying in a similar way like RDBMS but ORMs have their own limitation and yeah they will add a little bit of overhead too(in terms of performance). That's why using Native MongoDB Java Driver is preferred.
For NOSQL databases, choosing an ORM purely depends upon the use case. An ORM will map your table(Collection in the case of MongoDB) to an Entity Object. You added, you can keep a map in entity which will allow your design to become a little bit of schemaless. Most of the time our data is almost structured so ORMs can be used. But if you have completely versatile and unstructured data go for Java Driver. Check Mongo's documentation.
Also, there are other stable ORM tools like Kundera, Spring Data. You should explore them.
PS:
This answer is for ORMs vs native driver not on Hibernate ORM
I am a Kundera developer
I would recommend a OGM framework like Tinkerpop, or if you need something a bit higher level and more similar to Hibernate then consider Ferma. Ferma sits on top of Tinkerpop and uses annotations to define Java classes that resemble an Entity in JPA and Hibernate. The difference is Ferma and Tinkerpop is built specifically for graph databases rather than trying to stuff it into a framework designed for traditional Relational Databases.
One nice feature of Ferma and Tinkerpop is that while built for Graph Databases they still work on Relational Databases. There are several drivers for Tinkerpop that allow it to work on virtually every major Graph Database and Relational Database on the market. It can also use in-memory drivers that exist natively in Tinkerpop and therefore doesn't need to be backed by any database at all. Its an extremely flexible platform that has a lot of benefits when it comes to modular and flexible code.
For reference here is the description of the Ferma project.
The Ferma project was originally created as an alternative to the
TinkerPop2 Frames project. Which at the time lacked features needed by
the community, and its performance was cripplingly slow. Today Ferma
is a robust framework that takes on a role similar to an
Object-relational Model (ORM) library for traditional databases. Ferma
is often referred to as a Object-graph Model (OGM) library, and maps
Java objects to elements in a graph such as a Vertex or an Edge. In
short it allows a schema to be defined using java interfaces and
classes which provides a level of abstraction for interacting with the
underlying graph.
And also the description of the Tinkerpop project.
Apache TinkerPop™ is a graph computing framework for both graph
databases (OLTP) and graph analytic systems (OLAP).
Note: I am one of the author's of Ferma.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 8 years ago.
Improve this question
My team is working on a medium size application (OLTP style). We were interested by switching to JPA instead of only using JDBC queries. Mostly for performance and practical reason. I'm not looking for a tutorial that shows me how to create a persistence.xml or Entity class in Eclipse. What i would like to know is what would be the steps to convert all the database queries into the JPA format. I know that the whole application must use JPA.
Many programmers has worked on this project over the years, so not everyone has the same SQL knowledge or the same programming skills. So there must be in this application 1000+ customs queries, using multiple tables (something that native JPA does not support very well), or query that is selecting only a few fields in a table... This is getting a bit out of control and i think that JPA would create a nice toolbox to make sure that everyone is going the same direction.
What should i look for to make sure that i'm not going into a process (convertion) that will never end ? Some sort of guideline.
(Again, i'm not looking for programming exemples, nor Eclipse tutorial.)
Thanks!
First step is convert you database schema into database model using JPA, you need to be clear what are the table, sequences, database objects that you are using in your existing application and start modeling all the schema with JPA you should consider use JPA annotation.
The step above will determine what will be your entities, embeddables and mapped superclass, their properties and the relationships they have, this step is very crucial as your logic will depends on the correctness of this model.
Then start looking for all the queries that are involved in your project, as you said that you have 1000+ queries consider use two scenario, convert all of them in JPQL queries or use a mix between native queries and named queries, I really prefer to convert all in JPQL unless are very database dependent. A step you must follow is find all of them, probably are some existing tool that convert from SQL to JPQL but I believe is better idea make by your own.
Once you have queries and model for the database start the creation of your new DAO using JPA and EntityManager stuff, I should recommend extract the interface for your exisiting DAO and start moving to a JPA implementation using the same interface, this will avoid break some code on your own, don't forget unit and IT test for your new DAO.
Also with the above approach you could start moving the application module by module, DAO or by DAO does not require to move full application at once. This will give you a kind of process in which you will see some progress each time you finish a new DAO or module.
Not sure what you mean about programming examples, I think those are the required steps but each project is different from each other, so consider this as some kind of guidelines.
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 7 years ago.
Improve this question
I currently have an application, where it's primary performance issue is using file-based database consisted of JSON responses.
I'd like to rewrite my application to use SQLite database feature.
Since I'm lazy, I'd like to use some kind of ORM.
So far I have found only two big ORM libraries:
ORMLite
GreenDAO ORM
DB4O
ActiveAndroid
My primary goal is to raise performance on working with data as much as possible
But I've found two possible issues with those libraries.
ORMLite uses annotations, which is big performance issue in pre-honeycomb due to this bug
GreenDAO is using some kind of code generator, and that would slow me down on development as I would have to write generator, and then use generated code. And I don't very like this idea.
DB4O is JPA, which I've always considered as slow and heavy on memory usage, therefore unsuitable for low-end devices (remember the Android API v7)
ad #ChenKinnrot:
The estimated load should be sufficient to think about using an ORM.
In my case it is about 25-30 unique tables, and at least 10 table joins (2 - 4 tables at a time). About 300-500 unique fields (columns)
So my questions are:
Should I use ORM/JPA layer in Android application?
If so, what library would you recommend me to use? (and please add some arguments too)
I've used ORMLite and found it straightforward once you got the hang of it (a few hours), quite powerful and didn't cause any performance problems (app tested in Gingerbread on HTC desire and HTC Hero).
I will be using it again in any projects I need to use a DB for.
A ORM layer is appealing.
However, in practice I either write simple ORM myself or use the Content Provider paradigm, which does not cooperate well with ORM.
I have looked into some existing ORM libraries (mainly ORMLite ,activeAnroid) but they all scared me away
as they seems not so easy to get started.
"We're talking about 25-30 unique tables, and at least 10 table joins.
About 300-500 unique fields (columns)"
If you have fixed and limited patterns of how the data will be queried, I would recommend to write the ORM/sql yourself.
My 2 cents.
If you are worried about your app's performance, I'd recommend greenDAO. It will save you from writing lots of boring code, so code generation should not be an issue. In return, it will generate also entities and DB unit tests for you.
I got some knowledge to share so:
ORM by definition is slower than writing your own sql, it's suppose to simplify the coding of data access, and provide a generic solution, generic = runs slower than you write your queries, if you know sql well.
The real question is how good performance you want to get, if it's the best possible, don't consider any data mapping framework, only sql generation framework that will help you write stuff faster, but gives you full control of everything.
If you don't want to get the most out of the sql db, use orm, I got no experience with this orm you mentioned, so I can't say what to choose.
And your DB is not so big and complex so the time you'll save with orm is not an issue.
In my experience, I had a lot of benefits from using ORM engines. However, there was the case when I had to deal with performance problems.
I had to load about 10 000 rows from the database, and with a standard implementation (I was using ORMLite), it took about 1 minute to complete (depends on the device CPU).
When you need to read a lot of data from the database, you can execute plain SQL and parse the results yourself (in my case, I only needed to query for 3 columns from the table). ORMLite also allows you to retrieve raw-results. By this, the performance has increased by 10 times. All 10 000 rows were loaded in 5 seconds or less!
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 9 years ago.
Improve this question
In the last time I heard a lot of complaining about Hibernate. And indeed I have some painful experiences with Hibernate too. So I read about Ebean and Siena.
Both have interesting approaches. Unfortunately, database access layers are very easy to write, but if your project grows and you have to handle great database-tables, you know if they are good or not. So it's really difficult to evaluate such a tool. Hibernate is well known and you could be sure that you can solve your problem with it. Sometime you need to learn a lot, but you can solve it.
How is it with Ebean? Are there any real world applications? Which databases are supported? Is it reliable?
After searching a little bit more I see that there are a lot more ORM-frameworks, so is there at least one reliable one?
Rob (Ebean Committer) here.
Ebean is about 4+ years old now. I would say it is fairly mature now. The supported DB's include Oracle, MySql, Postgres, H2 and SQL Server (and recently SQLite). Ebean is doing stuff that other ORM's are not such as Autofetch (automatic query tuning) so I'm not how that fit's into a 'maturity rating'. IMO the Ebean community is relatively small though so you probably need to hit the Ebean google group to engage them.
Any real world applications? Yes, but you are best to ask the Ebean community about that really. Certainly there is good support for batch processing (batch size, turn of cascading persist for a transaction etc) and large query support that I don't see in JPA etc (you might get something similar with Hibernate's Sessionless support).
Hopefully this might answer some small parts of your question anyway.
Cheers, Rob.
I'm currently a developer of Siena but not since very long. Let me explain why I became a developer on this project?
I went to Siena because I wanted to use Play+GAE and Siena appeared to be a good start for GAE DB and I really wanted to avoid JDO/JPA.
Then, I began to really appreciate Siena for its straightforward, light and easy approach and so simple APIs. It doesn't pretend to be the all-in-one abstraction layer like JDO and the greatest standard DB API like JPA. It really made me think of DB APIs from Python/Ruby and it really fits my point of view: I want a simple DB API which allows me to solve the great majority of my problems and when I have a more complex problem, I will use the lower layer APIs but certainly not an abstraction layer such as hibernate.
The possibility to make my code work on GAE DB or JDBC was also a good aspect. Once again, Siena doesn't pretend to provide exactly the same things in both worlds because SQL and NoSQL are not really compatible (but ORM is neither really compliant to SQL model :) ).
But once again, it is quite practical to be able to rely on the same APIs in several DBs.
Finally, the library is ONE jar and you don't have to retrieve the whole universe to use it.
So, I became progressively a committer on Siena because I wanted to take part of this nice little adventure.
Now siena team is working on a new version keeping the same simple APIs, bringing new interesting features and really improving all the backend code to make it even easier to extend for new DB support.
Siena is a pragmatic API driven by user experiences and that's why I like it ;)
Pascal
We've had really great experience with MyBatis, which is not an ORM per se, but another class of persistence manager, an SQL Mapper. Using it you start with SQL statements and direct it on how to map result rows into POJOs. It's conceptually easy to understand and tune with not much magic going on inside. It's ideal if you are comfortable with SQL or need to work with an established schema.
Besides Ebean and Siena:
You can try JIRM which is focused on CRUDing immutable objects (yes I'm the author).
There is also jOOQ and Joist.
I feel that JIRM minimizes the number of DTO's because the domain objects are immutable and do not inherit, implement and/or are not "enhanced/instrumented". Such is not the same with Siena and Ebean.
Also because the objects are Immutable there is more of a focus on per column updating instead of the whole object which makes more sense given today's AJAX interfaces (compared to the old POST the whole bean model).
What about using EB3, with for instance JBoss (www.jboss.org)?