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  • Are document-oriented databases any more suitable than relational ones for persisting objects?

    - by Owen Fraser-Green
    In terms of database usage, the last decade was the age of the ORM with hundreds competing to persist our object graphs in plain old-fashioned RMDBS. Now we seem to be witnessing the coming of age of document-oriented databases. These databases are highly optimized for schema-free documents but are also very attractive for their ability to scale out and query a cluster in parallel. Document-oriented databases also hold a couple of advantages over RDBMS's for persisting data models in object-oriented designs. As the tables are schema-free, one can store objects belonging to different classes in an inheritance hierarchy side-by-side. Also, as the domain model changes, so long as the code can cope with getting back objects from an old version of the domain classes, one can avoid having to migrate the whole database at every change. On the other hand, the performance benefits of document-oriented databases mainly appear to come about when storing deeper documents. In object-oriented terms, classes which are composed of other classes, for example, a blog post and its comments. In most of the examples of this I can come up with though, such as the blog one, the gain in read access would appear to be offset by the penalty in having to write the whole blog post "document" every time a new comment is added. It looks to me as though document-oriented databases can bring significant benefits to object-oriented systems if one takes extreme care to organize the objects in deep graphs optimized for the way the data will be read and written but this means knowing the use cases up front. In the real world, we often don't know until we actually have a live implementation we can profile. So is the case of relational vs. document-oriented databases one of swings and roundabouts? I'm interested in people's opinions and advice, in particular if anyone has built any significant applications on a document-oriented database.

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  • New Whitepaper: Advanced Compression 11gR1 Benchmarks with EBS 12

    - by Steven Chan
    In my opinion, if there's any reason to upgrade an E-Business Suite environment to the 11gR1 or 11gR2 database, it's the Advanced Compression database option.  Oracle Advanced Compression was introduced in Oracle Database 11g, and allows you to compress structured data (numbers, characters) as well as unstructured data (documents, spreadsheets, XML and other files).  It provides enhanced compression for database backups and also includes network compression for faster synchronization with standby databases.In other words, the promise of Advanced Compression is that it can make your E-Business Suite database smaller and faster.  But how well does it actually deliver on that promise?Apps 12 + Advanced Compression Benchmarks now availableThree of my colleagues, Uday Moogala, Lester Gutierrez, and Andy Tremayne, have been benchmarking Oracle E-Business Suite Release 12 with Advanced Compression 11gR1.  They've just released a detailed whitepaper with their benchmarking results and recommendations.This whitepaper is available in two locations:Oracle E-Business Suite Release 12.1 with Oracle Database 11g Advanced Compression (Note 1110648.1) (requires My Oracle Support access)Oracle E-Business Suite Release 12.1 with Oracle Database 11g Advanced Compression (Applications Benchmark website, PDF, 500K)

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  • how non-programmer become developer

    - by Sarang
    Every year there are different types of freshers getting recruited. But, our IT field is not only limited to IT Engineers & Computer Engineers. It is full of all different types of engineers. What is a way an engineer can be a proper developer ? I am asking this because, whatever engineering the student gone for, one can be shifted to IT development if he/she has some particular qualities within. What are those quelities required to be in a developer or required to be implemented to be developer ?

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  • how to do database updates in each release

    - by Manoj R
    Our application uses database (mostly Oracle), and database is at the core. Each customer has its own database, with its own copy of application. Now with each new release of our product, we also need to update the database schema. These changes are adding new tables, removing columns, manipulating data etc. How do the people handle this? Are there any standard processes for this? EDIT:- The main issue is the databases are huge with many tables and more of huge amount of data. We provide the scripts and some utilities to manipulate the data. How to handle the failures and false negatives? More of looking for this kind articles. http://thedailywtf.com/Articles/Database-Changes-Done-Right.aspx

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  • Amazon SOA: database as a Service

    - by Martin Lee
    There is an interesting interview with Werner Vogels which is partly about how Amazon does Service Oriented Architecture: For us service orientation means encapsulating the data with the business logic that operates on the data, with the only access through a published service interface. No direct database access is allowed from outside the service, and there’s no data sharing among the services. I do not understand that. Why do they need to 'wrap' a database into some layer if it already can be consumed as a service by other service through database adaptors? Does Amazon do that just because they need to expose the database to third parties or because of anything else? Why "no direct database access is allowed"? What are the advantages of such an architectural decision?

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  • Which database to use and system/db administration by layman [closed]

    - by blah
    So my friend and I got briliant ;) idea for a business. Since it is not predictable whether it will work out or not, we decided to keep cost as low as possible to start with, in particular not to hire anyone. If it will work out as expected it will generate enough profit to hire professionals in few months. But for the first few months we'll be doing everything by ourselfs. He's a business/finance major, and I'm a software developer, so obviously I have to take care of IT :) It will be a webapp, written in python/django. My questions regarding this project: 1) What database should I choose? I'm experienced with oracle, and have been working with SQL Server for a while, but both of them are too expensive(at least now). It's a developer experience, I've never done any dba stuff. I'm looking for something free(as in beer). Looks like MySql or PostgreSQL are most popular in this sector. I would appreciate any comments on which db to choose. I'm open to any suggestions(it doesn't have to be MySql or Postgre). Here's what I know about data: It will be almost dates and numbers, a little bit of text. Searched mainly by dates. Data will almost never be updated, mostly inserted and browsed. From 30k to 300k new records/month. 2) Servers. My idea is to rent two dedicated servers. During normal operation one would be a web server(debian/apache), other would be a db server(debian/?). My recovery plan is to install everything on both, and in case of trouble with one of machines just run everything on the other one. Does it even makes sense? Any other tips appreciated. Thanks.

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  • When should we use weak entities when modelling a database?

    - by Songo
    This is basically a question about what are weak entities? When should we use them? How should they be modeled? What is the main difference between normal entities and weak entities? Does weak entities correspond to value objects when doing Domain Driven Design? To help keep the question on topic here is an example taken from Wikipedia that people can use to answer these question: In this example OrderItem was modeled as a weak entity, but I can't understand why it can't be modeled as a normal entity. Another question is what if I want to track the order history (i.e. the changes in it status) would that be a normal or weak entity?

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  • Single database, multiple system dependency

    - by davenewza
    Consider an environment where we have a single, core database, with many separate systems using this one database. This leads to all of these systems have a common dependency, which ultimately introduces coupling between them. This means that we cannot always evolve systems independently of each other. Structural changes to the database (even if only intended for one, particular system), requires a full sweep test of ALL systems, and may require that other systems be 'patched' and subsequently released. This is especially tricky when you want to have separate teams working on different projects. What is a good 'pattern' to help in avoiding such coupling? I would imagine that a database should be exclusively depended on by one system. If other systems require data for whatever reason, they should request such from an API service of some kind. A drawback of this approach which comes to mind is performance: routing data between high-throughput systems through service calls is much slower than through a database connection.

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  • Best C# database communication technique

    - by user65439
    A few days ago I read a reply to a question where people said that the days of writing queries within your c# code are long gone. I'm not sure what the specific person meant with the comment but it got me thinking. At the company I'm currently working at we maintain an assembly containing all the queries to the database (let's call it Queries), this assembly is reference by a QueryService (Retrieve the correct queries) assembly which in turn is referenced by a UnitOfWork assembly (The database connector classes, we have different connector classes for SQL, MySQL etc.). We use these three assemblies to perform operations on our database and all queries/commands are written in our C# code. Is there a better way to communicate with the database and is there a better way to communicate with different database types?

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  • Design Pattern for Complex Data Modeling

    - by Aaron Hayman
    I'm developing a program that has a SQL database as a backing store. As a very broad description, the program itself allows a user to generate records in any number of user-defined tables and make connections between them. As for specs: Any record generated must be able to be connected to any other record in any other user table (excluding itself...the record, not the table). These "connections" are directional, and the list of connections a record has is user ordered. Moreover, a record must "know" of connections made from it to others as well as connections made to it from others. The connections are kind of the point of this program, so there is a strong possibility that the number of connections made is very high, especially if the user is using the software as intended. A record's field can also include aggregate information from it's connections (like obtaining average, sum, etc) that must be updated on change from another record it's connected to. To conserve memory, only relevant information must be loaded at any one time (can't load the entire database in memory at load and go from there). I cannot assume the backing store is local. Right now it is, but eventually this program will include syncing to a remote db. Neither the user tables, connections or records are known at design time as they are user generated. I've spent a lot of time trying to figure out how to design the backing store and the object model to best fit these specs. In my first design attempt on this, I had one object managing all a table's records and connections. I attempted this first because it kept the memory footprint smaller (records and connections were simple dicts), but maintaining aggregate and link information between tables became....onerous (ie...a huge spaghettified mess). Tracing dependencies using this method almost became impossible. Instead, I've settled on a distributed graph model where each record and connection is 'aware' of what's around it by managing it own data and connections to other records. Doing this increases my memory footprint but also let me create a faulting system so connections/records aren't loaded into memory until they're needed. It's also much easier to code: trace dependencies, eliminate cycling recursive updates, etc. My biggest problem is storing/loading the connections. I'm not happy with any of my current solutions/ideas so I wanted to ask and see if anybody else has any ideas of how this should be structured. Connections are fairly simple. They contain: fromRecordID, fromTableID, fromRecordOrder, toRecordID, toTableID, toRecordOrder. Here's what I've come up with so far: Store all the connections in one big table. If I do this, either I load all connections at once (one big db call) or make a call every time a user table is loaded. The big issue here: the size of the connections table has the potential to be huge, and I'm afraid it would slow things down. Store in separate tables all the outgoing connections for each user table. This is probably the worst idea I've had. Now my connections are 'spread out' over multiple tables (one for each user table), which means I have to make a separate DB called to each table (or make a huge join) just to find all the incoming connections for a particular user table. I've avoided making "one big ass table", but I'm not sure the cost is worth it. Store in separate tables all outgoing AND incoming connections for each user table (using a flag to distinguish between incoming vs outgoing). This is the idea I'm leaning towards, but it will essentially double the total DB storage for all the connections (as each connection will be stored in two tables). It also means I have to make sure connection information is kept in sync in both places. This is obviously not ideal but it does mean that when I load a user table, I only need to load one 'connection' table and have all the information I need. This also presents a separate problem, that of connection object creation. Since each user table has a list of all connections, there are two opportunities for a connection object to be made. However, connections objects (designed to facilitate communication between records) should only be created once. This means I'll have to devise a common caching/factory object to make sure only one connection object is made per connection. Does anybody have any ideas of a better way to do this? Once I've committed to a particular design pattern I'm pretty much stuck with it, so I want to make sure I've come up with the best one possible.

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  • Pros/Cons of document based database vs relational database

    - by damian
    I've been trying to see if I can accomplish some requirements with a document based database, in this case CouchDB. Two generic requirements: CRUD of entities with some fields which have unique index on it ecommerce web app like eBay (better description here). And I'm begining to think that a Document-based database isn't the best choice to address these requirements. Furthermore, I can´t imagine a use for a Document based database (maybe my imagination is too little). Can you explain me if I am asking pears to an elm when I try to use a Document based database for this requirements?

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  • Postgresql - one database for everyone, or one-database per customer

    - by user337876
    I'm working on a web-based business application where each customer will need to have their own data (think basecamphq.com type model) For scalability and ease-of-upgrades, I'd prefer to have a single database where each customer gets a filtered version of the data. The problem is how to guarantee that they stay sandboxed to their own data. Trying to enforce it in code seems like a disaster waiting to happen. I know Oracle has a way to append a where clause to every query based on a login id, but does Postgresql have anything similar? If not, is there a different design pattern I could use (like creating a view of each table for each customer that filters)? Worse case scenario, what is the performance/memory overhead of having 1000 100M databases vs having a single 1Tb database? I will need to provide backup/restore functionality on a per-customer basis which is dead-simple on a single database but quite a bit trickier if they are sharing the database with other customers.

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  • SQL Server replication - how to sync tables from internal database to read-only website database

    - by frankadelic
    I have an internal SQL Server 2005 database "ADMIN_DATA" that is used by admin users. We would like to sync three of the database tables in ADMIN_DATA out to another SQL Server 2005 database "WEB_DATA", which is used by a public web app. WEB_DATA is read-only - only SELECT statements are allowed, while ADMIN_DATA is updated all the time. What is the best solution? How can this be accomplished with minimal custom coding and/or changes to database tables? Notes: ADMIN_DATA and WEB_DATA are different physical machines and on different subnets. The syncing operation doesn't need to be instantaneous.

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  • VS2010 ultimate DataBase Project + SQL Server 2008: Updating Project from Database

    - by josecortesp
    Hello everyone, this is a quick question: I have this Database Project in a Web app solution with the real database. I want to update the database using SQL server managment studio, and then update the corresponding VS project. This can be done? I know that you can update the scripts in the project, but I'm not the SQL kind of guy, i rather do this changes using Mangment studio... Thanks in advance

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  • Server database -> client database update based on version

    - by user296191
    Hi, What is the recommended method of collecting items in a server database, versioning the database then deploying only the version differences to a client ? Should it by a field in the table (ie. Version: 3.3.9876) against each record ? Should it be DateTime (server based) in each record ? And whats the best way to just deploy the changes to a client with an older version of the database ? Is it a DUMP to a file with a Bulk import of some description ? Open to comments.. Suggestions. Database can be anything (firebird, mysql, sqlserver, sqlite)... Any info greatly appreciated.

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  • Transferring a flat file database to a MySQL database

    - by Jon
    I have a flat file database (yeah gross I know - the worst part is that it's 1.4GB), and I'm in the process of moving it to a MySQL database. The problem is that I'm not sure how to go about doing this - and I've checked through every related question on here but none relate to what I want to do, nor how my database is currently setup. My current flat file database is setup to where a normal MySQL row is its own file, and a MySQL table would be the directory. So for example if you have a user named Jon, there would be a file for the user in a directory named /members/. Within that file would be various information for the user including the users id, rank etc - all separated by tabs, all on separate lines (userid\t4). So here's an example user file: userid 4 notes staff notes: bla bla staff2 notes: bla bla bla username Example So how can I convert the above into their own rows and fields in MySQL? And if possible, could I do thousands of these files at once? Thanks.

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  • Rating System Database Structure

    - by Harsha M V
    I have two entity groups. Restaurants and Users. Restaurants can be rated (1-5) by users. And rating fromeach user should be retrievable. Resturant(id, name, ..... , total_number_of_votes, total_voting_points ) User (id, name ...... ) Rating (id, restaurant_id, user_id, rating_value) Do i need to store the avg value so that it need not be calculated every time ? which table is the best place to store avg_rating, total_no_of_votes, total_voting_points ?

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  • Database that consumes less disk space

    - by Hugo Palma
    I'm looking at solutions to store a massive quantity of information consuming the less possible disk space. The information structure is very simple and the queries will also be very simple. I've looked at solutions like Apache Cassandra and relations databases but couldn't find a comparison where disk usage is mentioned. Any ideas on this would be great.

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  • Database Modelling - Conceptually different entities but with near identical fields

    - by Andrew Shepherd
    Suppose you have two sets of conceptual entities: MarketPriceDataSet which has multiple ForwardPriceEntries PoolPriceForecastDataSet which has multiple PoolPriceForecastEntry Both different child objects have near identical fields: ForwardPriceEntry has MarketPriceDataSetId (foreign key to parent table) StartDate EndDate SimulationItemId ForwardPrice PoolPriceForecastEntry has PoolPriceForecastDataSetId (foreign key to parent table) StartDate EndDate SimulationItemId ForecastPoolPrice If I modelled them as separate tables, the only difference would be the foreign key, and the name of the price field. There has been a debate as to whether the two near identical tables should be merged into one. Options I've thought of to model this is: Just keep them as two independent, separate tables Have both sets in the one table with an additional "type" field, and a parent_id equalling a foreign key to either parent table. This would sacrifice referential integrity checks. Have both sets in the one table with an additional "type" field, and create a complicated sequence of joining tables to maintain referential integrity. What do you think I should do, and why?

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  • Why is it bad to use boolean flags in databases? And what should be used instead?

    - by David Chanin
    I've been reading through some of guides on database optimization and best practices and a lot of them suggest not using boolean flags at all in the DB schema (ex http://forge.mysql.com/wiki/Top10SQLPerformanceTips). However, they never provide any reason as to why this is bad. Is it a peformance issue? is it hard to index or query properly? Furthermore, if boolean flags are bad, what should you use to store boolean values in a database? Is it better to store boolean flags as an integer and use a bitmask? This seems like it would be less readable.

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  • Properly populating tables in an Object Relational database

    - by chaosTechnician
    I've got a homework assignment that requires that I use Oracle 10g Express to implement an Object Relational database to track phone billing data. I have a superclass of Communications with subclasses of Call, Text, and Data. I'm hitting a snag with properly populating these tables so that I can find the appropriate data in the various tables. My Types and Tables are declared as such: create type CommunicationType as object ( -- column names here ) not final; create type CallType under CommunicationType ( -- column names here ); create type TextType under CommunicationType ( -- column names here ); create type DataType under CommunicationType ( -- column names here ); create table Communications of CommunicationType ( -- Primary and Foreign key constraints here ); create table Calls of CallType; create table Texts of TextType; create table Datas of DataType; When I try to insert data into one of the subclasses, its entry doesn't appear in the superclass. Likewise if I insert into the superclass, it doesn't show up in the appropriate subclass. For example, insert into Calls values (CallType( -- Values -- )); doesn't show any data in Communications. Nor does insert into Communications values (CallType( -- Values -- )); show anything in Calls. What am I doing wrong?

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  • Database Modelling - Conceptually different entities with near identical fields

    - by Andrew Shepherd
    Suppose you have two sets of conceptual entities: MarketPriceDataSet which has multiple ForwardPriceEntries PoolPriceForecastDataSet which has multiple PoolPriceForecastEntry Both different child objects have near identical fields: ForwardPriceEntry has StartDate EndDate SimulationItemId ForwardPrice MarketPriceDataSetId (foreign key to parent table) PoolPriceForecastEntry has StartDate EndDate SimulationItemId ForecastPoolPrice PoolPriceForecastDataSetId (foreign key to parent table) If I modelled them as separate tables, the only difference would be the foreign key, and the name of the price field. There has been a debate as to whether the two near identical tables should be merged into one. Options I've thought of to model this is: Just keep them as two independent, separate tables Have both sets in the one table with an additional "type" field, and a parent_id equalling a foreign key to either parent table. This would sacrifice referential integrity checks. Have both sets in the one table with an additional "type" field, and create a complicated sequence of joining tables to maintain referential integrity. What do you think I should do, and why?

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