Automatic mapping from schema to code, database and GUI - database

There are different systems (for different environments, languages) which helps to map schema to data structures in code, in databases, and do automatic glue code between them - ORM, etc.
Is there any common name/abbreviation (like ORM) for systems that in addition do mapping to user interface (in automatic/semi-automatic ways)?
Are there such systems? Of course it would require to select GUI templates for different parts of schema, maybe add a little logic at some places (declarative approach is preferable).
I remember that something similar was available at MS Access - it could automatically create UI Forms from schema or even queries. But I wonder if there are similar systems? (doesn't matter if it web GUI or desktop GUI).
I guess there can be library/framework for do this (Python, C#, Java, C++, PHP, etc), or stand-alone apps like MS Access.

You seem to be talking about scaffolding. Scaffolding is a way to display a very basic user interfaces (GUI) normally based on a database structure. Depending on the language, framework and implementation it may also provide basic Create, Read, Update, Delete (CRUD) actions on the GUI.
It is often frowned upon for anything other than a very rapid prototype. In fact, 99% of the time you will save more time and be better off learning a framework and doing things "properly".
Having said that, web frameworks seem to be the kings of scaffolding.
Ruby on Rails
Django
CakePHP
C#/ASP.NET
My advice would be to pick a well supported framework which favours convention over configuration and follow through some tutorials. You'll most likely end up in a better place.

Related

Why would i need to add scripting engine in my standalone applications

I would like to know in which scenarios would embedding scripting language in my C projects help me.
I have heard about lua which the developers embed in their projects to extending their software applications but why developers prefer to extend their applications using some scripting engine rather then the primary language?
This mostly comes down to who ends up using your applications and what they are using it for. If the application needs no per-user customization, then there's no need for scripting. New functionality can be added normally as part of the application.
However, like in game engines, if the users need to create/script custom behaviour into the application there has to be some way for them to do so. You could try to make your users write their scripts in the language of the application, however in the case of C and many other languages, this requires the code for the application to be recompiled (Not to mention the fact that your users might not be programmers and could benefit from a more high level scripting language).
By adding a scripting engine, you allow your users to add their own (limited) functionality to the application without needing to understand or recompile the entire codebase.
tl;dr Scripting engines make sense if your users need routinely to add custom behaviours to the application.
Regarding your "scenario" question : adding a script engine to your standalone (C or C++ for instance) application is the most direct way to combine the performance of a dedicated engine with the expertise of your power users.
No matter the field of you standalone application, thanks to the ability to write scripts, a power user will usually be able to get the most of it by creating dedicated or project-centric workflow.
The script interface brings a safe and secure environment that is suited for such users whose primary skills is generally not to deal with C/C++.
This leads to your second question : a script API perfectly (using Lua or Squirrel, for instance) makes sense if the primary language needs low-level programming skills. Typically, and application written in C++ will require your power users to write plugins using a C++ SDK.
On the opposite, if your standalone application is written in Python, the benefit of embedding Lua is far from obious in my opinion.

What factors to consider when choosing a Multi-model DBMS? (OrientDB vs ArangoDB)

I am looking to dip my hands into the world of Multi-Model DBMS, I have no particular use cases, just want to start learning.
I find that there are two prominent ones - OrientDB vs ArangoDB, but was unable to find any meaningful comparison, unopinionated between them. Can someone shed some light on the difference in features between the two, and any caveats in using one over the other? If I learn one would I be able to easily transition to the other?
(I tagged FoundationDB as well, but it is proprietary and I probably won't consider it)
This question asks for a general comparison between OrientDB vs ArangoDB for someone looking to learn about Multi-model DBMS, and not an opinionated answer about which is better.
Disclaimer: I would no longer recommend OrientDB, see my comments below.
I can provide a slightly less biased opinion, having used both ArangoDB and OrientDB. It's still biased as I'm the author of OrientDB's node.js driver - oriento but I don't have a vested interest in either company or product, I've just necessarily used OrientDB more.
ArangoDB and OrientDB are both targeting a similar market and have a lot of similarities:
Both are multi-model, you can use them to store documents, graphs and simple key / values.
Both have support for Gremlin, but it's firmly a second class citizen compared to their own preferred query languages.
Both support server-side "stored procedures" in JavaScript. In both systems this comes via a slightly less than idiomatic JavaScript API, although ArangoDB's is a lot better. This is getting fixed in a forthcoming version of OrientDB.
Both offer REST APIs, both aim to be usable as an "API Server" via JavaScript request handlers. This is a lot more practical in ArangoDB than OrientDB.
Both are distributed under a permissive license.
Both are ACID and have transaction support, but in both the transactions are server-side operations - they're more like atomic batches of commands rather than the kinds of transactions you might be used to in a traditional RDBMS.
However, there are a lot of differences:
ArangoDB has no concept of "links", which are a very useful feature in OrientDB. They allow unidirectional relationships (just like a hyperlink on the web), without the overhead of edges.
ArangoDB is written in C++ (and JavaScript), whereas OrientDB is written in Java. Both have their advantages:
Being written in C++ means ArangoDB uses V8, the same high performance JavaScript engine that powers node.js and Google Chrome. Whereas being written in Java means OrientDB uses Nashorn, which is still fast but not the fastest. This means that ArangoDB can offer a greater level of compatibility with the node.js ecosystem compared to OrientDB.
Being written in Java means that OrientDB runs on more platforms, including e.g. Raspberry PI. It also means that OrientDB can leverage a lot of other technologies written in Java, e.g. OrientDB has superb full text / geospatial search support via Lucene, which is not available to ArangoDB.
OrientDB uses a dialect of SQL as its query language, whereas ArangoDB uses its own custom language called AQL. In theory, AQL is better because it's designed explicitly for the problem, in practise though it feels quite similar to SQL but with different keywords, and is yet another language to learn while OrientDB's implementation feels a lot more comfortable if you're used to SQL. SQL is declarative whereas AQL is imperative - YMMV here.
ArangoDB is a "mostly-memory" database, it works best when most of your data fits in RAM. This may or may not be suitable for your needs. OrientDB doesn't have this restriction (but also loves RAM).
OrientDB is fully object oriented - it supports classes with properties and inheritance. This is exceptionally useful because it means that your database structure can map 1-1 to your application structure, with no need for ugly hacks like ActiveRecord. ArangoDB supports something fairly similar via models in Foxx, but it's more like an optional addon rather than a core part of how the database works.
ArangoDB offers a lot of flexibility via Foxx, but it has not been designed by people with strong server-side JS backgrounds and reinvents the wheel a lot of the time. Rather than leveraging frameworks like express for their request handling, they created their own clone of Sinatra, which of course makes it almost the same as express (express is also a Sinatra clone), but subtly different, and means that none of express's middleware or plugins can be reused. Similarly, they embed V8, but not libuv, which means they do not offer the same non blocking APIs as node.js and therefore users cannot be sure about whether a given npm module will work there. This means that non trivial applications cannot use ArangoDB as a replacement for the backend, which negates a lot of the potential usefulness of Foxx.
OrientDB supports first class property level and database level indices. You can query and insert into specific indexes directly for maximum efficiency. I've not seen support for this in ArangoDB.
OrientDB is the more established option, with many high profile users. ArangoDB is newer, less well known, but growing fast.
ArangoDB's documentation is excellent, and they offer official drivers for many different programming languages. OrientDB's documentation is not quite as good, and while there are drivers for most platforms, they're community powered and therefore not always kept up to date with bleeding edge OrientDB features.
If you're using Java (or a Java bridge), you can embed OrientDB directly within your application, as a library. This use case is not possible in ArangoDB.
OrientDB has the concept of users and roles, as well as Record Level Security. This may be a killer feature for you, it is for me. It also supports token based authentication, so it's possible to use OrientDB as your primary means of authorizing/authenticating users. OrientDB also has LDAP integration. In contrast, ArangoDB support only a very simple auth option.
Both systems have their own advantages, so choosing between them comes down to your own situation:
If you're building a small application, and you're a web developer optimizing for developer productivity, it will probably be easier to get up and running quickly with ArangoDB.
If you're building a larger application, which could potentially store many gigabytes or terabytes of data, or have many thousands of concurrent users, or have "enterprise" use cases, or need fine grained security controls, OrientDB is the one for you.
If you're storing RDF or similarly structured linked data, choose OrientDB.
If you're using Java, just choose OrientDB.
Note: This is (my opinion of) the state of play today, things change quickly and I would not underestimate the ruthless efficiency of the awesome team behind ArangoDB, I just think that it's not quite there yet :)
Charles Pick (codemix.com)

Simplest way to develop an app that can use multiple types of databases?

I have a project for a class which requires that if a database is used, options exist for the user to pick a database to use which could be of a different type. So while I can use e.g. MySQL for development, in the final version of the project, the user must be able to choose a database (Oracle, MySQL, SQLite, etc.) upon installation. What's the easiest way to go about this, if there is an easy way?
The language used is up to me as long as it's supported by the department's Linux machines, so it could be Java, PHP, Perl, etc. I've been researching and found info on ODBC, JDBC, and SQLJ (such as this) but I'm quite new to databases so I'm having a hard time figuring out what would be best for my needs. It's also possible there may not be a simple enough way to do this; the professor admitted he's not a database guy either and he seemed to think it would be easy without having a clear idea of what it would take.
This is for a web app, but it ought to be fairly straight forward, using for example HTML and Javascript on the client side and Java with a MySQL database on the server side. No mention has been made of frameworks so I think they're too much. I have the option of using Tomcat or Apache if necessary but the overall idea is to keep things simple, and everything used should be able to be installed/changed/configured with just user level access. So something like having to recompile PHP to use ODBC would be out, I think.
Within these limitations, what would be the best way (if any) to be able to interact with an arbitrary database?
The issue I think you will have here is that SQL is not truely standard. What I mean is that vendors (Oracle, MySQL etc) have included types and features that are not SQL standard in order to "tie you in" to their DB, such as Oracle's VARCHAR2 and so on.
When I was at university, my final year project was to create an application that allowed users to create relational databases using JDBC with a Java front-end.
The use of JDBC was very simple but the issue was finding enough SQL features/types that all the vendors have in common. So they could switch between them without any issues. A way round this is to implement modules to deal with vendor specific issues and write ways to translate between them. So for example you may develop a database for MySQL with lots of MySQL specific code in that, but then you may want to use Oracle and then there are issues, which you would need to resolve.
I would spend some time looking at what core SQL standard all the vendors implement and then code for these features. But I think the technology you use wouldn't be the issue but rather the SQL you create.
Hope this helps, apologies if its not helpful!
Well, you can go two ways (in Java):
You can develop your own classes to work with different databases and load their drivers in JDBC. This way you will create a data access layer for yourself, which takes some time.
You can use Hibernate (or other ORMs). This way Hibernate will take care of things for you and you only have to know how to use Hibernate. Learning Hibernate may take some time, but when you get used to it, it can be very useful for your future projects.
If you want to stick Java there Hibernate (which wouldn't require a framework). Hibernate is fairly easy to use. You write HQL which gets translated to the SQL needed for the database you're using.
Maybe use an object relational mapper (ORM) or database abstraction layer (DAL). They are designed to provide a standard API to multiple database backends, making it possible to switch between different backends with minimal or no changes to your code. In Python, for example, a popular ORM is SQLAlchemy, and an excellent DAL is the web2py DAL (it's part of the web2py framework but can be used as a standalone DAL outside the framework as well). There are many other options in other languages as well.
use a framework with database abstraction layer and orm . try symfony or rails
There are a lot of Object relational database frameworks, unless you prefer jdbc. For simple/small applications this should work fine.

ActiveRecord for Erlang

I am continuing to delve into Erlang. I am thinking of starting my next web project using Erlang, and at this stage the only thing I will really miss from Ruby on Rails is ActiveRecord.
Is there a good alternative technology for Erlang?
Update:
The closest I have come to a solution is to ErlyDB, a component of ErlyWeb.
ErlyDB is a database abstraction layer
generator for Erlang. ErlyDB combines
database metadata and user-provided
metadata to generate functions that
let you perform common data access
operations in an intuitive manner. It
also provides a single API for working
with different database engines
(although currently, only MySQL is
supported), letting you write portable
data access code.
Well, the major advantages of ActiveRecord (as I see it) are:
You can persist your objects in a relational database nearly transparently.
You can search the database by any attribute of your objects.
You can validate objects when persisting them.
You can have callbacks on deleting, updating, or inserting objects.
With Mnesia:
You can persist any Erlang data absolutely transparently.
Using pattern matching, you can search the database by any attribute of your data or their combination.
QLC gives you a nice query interface for cases when pattern matching isn't enough.
No solutions for validating and callbacks, however...
So, what else do you have in ActiveRecord that is lacking in Mnesia?
I don't think there really is at the time of this writing. That may be because the kinds of systems being written in erlang and the type of people writing them don't really call for Relational Databases. I see much more code using mnesia, CouchDB, Tokyo Cabinet and other such alternative database technologies.
That's not to say someone might not want to create something like active record. It's just hasn't really been a need yet. Maybe you will be the first? :-)
You might be interested in Chicago Boss's "BossRecords":
http://www.chicagoboss.org/api-record.html
They are quite explicitly modeled on the Active Record pattern, and use a lot of compiler magic to make the syntax squeaky clean. BossRecords support save/validate as well as has_many/belongs_to associations. Attributes in your data model are made available through generated functions (e.g. "Employee:first_name()").
Some googling reveals libs / clients / wrappers for Couchdb described "ActiveRecord like libraries like CouchFoo", and advise to steer clear:
http://upstream-berlin.com/2009/03/31/the-case-of-activerecord-vs-couchdb/
http://debasishg.blogspot.com/2009/04/framework-inertia-couchdb-and-case-of.html#
as to your comment on "not suited for web apps yet", I think the pieces are there: mochiweb, couch, yaws, nitrogen, erlyweb. There's some powerful tools, very different paradigm, certainly, from rails, django and PHP.

Is LINQ an Object-Relational Mapper?

Is LINQ a kind of Object-Relational Mapper?
LINQ in itself is a set of language extensions to aid querying, readability and reduce code. LINQ to SQL is a kind of OR Mapper, but it isn't particularly powerful. The Entity Framework is often referred to as an OR Mapper, but it does quite a lot more.
There are several other LINQ to X implementations around, including LINQ to NHibernate and LINQ to LLBLGenPro that offer OR Mapping and supporting frameworks in a broadly similar fashion to the Entity Framework.
If you are just learning LINQ though, I'd recommend you stick to LINQ to Objects to get a feel for it, rather than diving into one of the more complicated flavours :-)
LINQ is not an ORM at all. LINQ is a way of querying "stuff", and can be more or less seen as a SQL-like language extension for different things (IEnumerables).
There are various types of "stuff" that can be queried, among them SQL Server databases. This is called LINQ-to-SQL. The way it works is that it generates (implicit) classes based on the structure of the DB and your query. In this sense it works much more like a code generator.
LINQ-to-SQL is not an ORM because it doesn't try at all to solve the object-relational impedance mismatch. In an ORM you design the classes and then either map them manually to tables or let the ORM generate the database. If you then change the database for whatever reason (typically refactoring, renormalization, denormalization), many times you are able to keep the classes as they are by changing the mapping.
LINQ-to-SQL does nothing of the sort. Your LINQ queries will be tightly coupled to the database structure. If you change the DB, you will probably have to change the LINQ as well.
LINQ to SQL (part of Visual Studio 2008) is an OR Mapper.
LINQ is a new query language that can be used to query many different types of sources.
LINQ itself is not a ORM. LINQ is the language features and methods that exist in allowing you to query objects like SQL.
"LINQ to SQL" is a provider that allows us to use LINQ against SQL strongly-typed objects.
I think a good test to ascertain whether a platform or code block displays the characteristics of an O/R-M is simply:
With his solution hat on, does the developer(s) (or his/her code generator) have any direct, unabstracted knowledge of what's inside the database?
With this criterion, the answer for differing LINQ implementations can be
Yes, knowledge of the database schema is entirely contained within the roll-your-own, LINQ utilizing O/R-M code layerorNo, knowledge of the database schema is scattered throughout the application
Further, I'd extend this characterization to three simple levels of O/R-M.
1. Abandonment.
It's a small app w/ a couple of developers and the object/data model isn't that complex and doesn't change very often. The small dev team can stay on top of it.
2. Roll your own in the data access layer.
With some managable refactoring in a data access layer, the desired O/R-M functionality can be effected in an intermediate layer by the relatively small dev team. Enough to keep the entire team on the same page.
3. Enterprise-level O/R-M specification defining/overhead introducing tools.
At some level of complexity, the need to keep all devs on the same page just swamps any overhead introduced by the formality. No need to reinvent the wheel at this level of complexity. N-hibernate or the (rough) V1.0 Entity Framework are examples of this scale.
For a richer classification, from which I borrowed and simplified, see Ted Neward's classic post at
http://blogs.tedneward.com/2006/06/26/The+Vietnam+Of+Computer+Science.aspx
where he classifies O/R-M treatments (or abdications) as
1. Abandonment. Developers simply give up on objects entirely, and return to a programming model that doesn't create the object/relational impedance mismatch. While distasteful, in certain scenarios an object-oriented approach creates more overhead than it saves, and the ROI simply isn't there to justify the cost of creating a rich domain model. ([Fowler] talks about this to some depth.) This eliminates the problem quite neatly, because if there are no objects, there is no impedance mismatch.
2. Wholehearted acceptance. Developers simply give up on relational storage entirely, and use a storage model that fits the way their languages of choice look at the world. Object-storage systems, such as the db4o project, solve the problem neatly by storing objects directly to disk, eliminating many (but not all) of the aforementioned issues; there is no "second schema", for example, because the only schema used is that of the object definitions themselves. While many DBAs will faint dead away at the thought, in an increasingly service-oriented world, which eschews the idea of direct data access but instead requires all access go through the service gateway thus encapsulating the storage mechanism away from prying eyes, it becomes entirely feasible to imagine developers storing data in a form that's much easier for them to use, rather than DBAs.
3. Manual mapping. Developers simply accept that it's not such a hard problem to solve manually after all, and write straight relational-access code to return relations to the language, access the tuples, and populate objects as necessary. In many cases, this code might even be automatically generated by a tool examining database metadata, eliminating some of the principal criticism of this approach (that being, "It's too much code to write and maintain").
4. Acceptance of O/R-M limitations. Developers simply accept that there is no way to efficiently and easily close the loop on the O/R mismatch, and use an O/R-M to solve 80% (or 50% or 95%, or whatever percentage seems appropriate) of the problem and make use of SQL and relational-based access (such as "raw" JDBC or ADO.NET) to carry them past those areas where an O/R-M would create problems. Doing so carries its own fair share of risks, however, as developers using an O/R-M must be aware of any caching the O/R-M solution does within it, because the "raw" relational access will clearly not be able to take advantage of that caching layer.
5. Integration of relational concepts into the languages. Developers simply accept that this is a problem that should be solved by the language, not by a library or framework. For the last decade or more, the emphasis on solutions to the O/R problem have focused on trying to bring objects closer to the database, so that developers can focus exclusively on programming in a single paradigm (that paradigm being, of course, objects). Over the last several years, however, interest in "scripting" languages with far stronger set and list support, like Ruby, has sparked the idea that perhaps another solution is appropriate: bring relational concepts (which, at heart, are set-based) into mainstream programming languages, making it easier to bridge the gap between "sets" and "objects". Work in this space has thus far been limited, constrained mostly to research projects and/or "fringe" languages, but several interesting efforts are gaining visibility within the community, such as functional/object hybrid languages like Scala or F#, as well as direct integration into traditional O-O languages, such as the LINQ project from Microsoft for C# and Visual Basic. One such effort that failed, unfortunately, was the SQL/J strategy; even there, the approach was limited, not seeking to incorporate sets into Java, but simply allow for embedded SQL calls to be preprocessed and translated into JDBC code by a translator.
6. Integration of relational concepts into frameworks. Developers simply accept that this problem is solvable, but only with a change of perspective. Instead of relying on language or library designers to solve this problem, developers take a different view of "objects" that is more relational in nature, building domain frameworks that are more directly built around relational constructs. For example, instead of creating a Person class that holds its instance data directly in fields inside the object, developers create a Person class that holds its instance data in a RowSet (Java) or DataSet (C#) instance, which can be assembled with other RowSets/DataSets into an easy-to-ship block of data for update against the database, or unpacked from the database into the individual objects.
Linq To SQL using the dbml designer yes, otherwise Linq is just a set of extension methods for Enumerables.

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