What is a Multimedia Database?

A multimedia database is a database that hosts one or more primary media file types such as .txt (documents), .jpg (images), .swf (videos), .mp3 (audio), etc. And loosely fall into three main categories:

Static media (time-independent, i.e. images and handwriting)
Dynamic media (time-dependent, i.e. video and sound bytes)
Dimensional media (i.e. 3D games or computer-aided drafting programs- CAD)
All primary media files are stored in binary strings of zeros and ones, and are encoded according to file type.

The term "data" is typically referenced from the computer point of view, whereas the term "multimedia" is referenced from the user point of view.

Types of Multimedia Databases

There are numerous different types of multimedia databases, including:

The Authentication Multimedia Database (also known as a Verification Multimedia Database, i.e. retina scanning), is a 1:1 data comparison
The Identification Multimedia Database is a data comparison of one-to-many (i.e. passwords and personal identification numbers
A newly-emerging type of multimedia database, is the Biometrics Multimedia Database; which specializes in automatic human verification based on the algorithms of their behavioral or physiological profile.
This method of identification is superior to traditional multimedia database methods requiring the typical input of personal identification numbers and passwords-

Due to the fact that the person being identified does not need to be physically present, where the identification check is taking place.

This removes the need for the person being scanned to remember a PIN or password. Fingerprint identification technology is also based on this type of multimedia database.

Difficulties Involved with Multimedia Databases

The difficulty of making these different types of multimedia databases readily accessible to humans is:

The tremendous amount of bandwidth they consume;
Creating Globally-accepted data-handling platforms, such as Joomla, and the special considerations that these new multimedia database structures require.
Creating a Globally-accepted operating system, including applicable storage and resource management programs need to accommodate the vast Global multimedia information hunger.
Multimedia databases need to take into accommodate various human interfaces to handle 3D-interactive objects, in an logically-perceived manner (i.e. SecondLife.com).
Accommodating the vast resources required to utilize artificial intelligence to it's fullest potential- including computer sight and sound analysis methods.
The historic relational databases (i.e the Binary Large Objects - BLOBs- developed for SQL databases to store multimedia data) do not conveniently support content-based searches for multimedia content.
This is due to the relational database not being able to recognize the internal structure of a Binary Large Object and therefore internal multimedia data components cannot be retrieved...

Basically, a relational database is an "everything or nothing" structure- with files retrieved and stored as a whole, which makes a relational database completely inefficient for making multimedia data easily accessible to humans.

In order to effectively accommodate multimedia data, a database management system, such as an Object Oriented Database (OODB) or Object Relational Database Management System (ORDBMS).

Examples of Object Relational Database Management Systems include Odaptor (HP): UniSQL, ODB-II, and Illustra.

The flip-side of the coin, is that unlike non-multimedia data stored in relational databases, multimedia data cannot be easily indexed, retrieved or classified, except by way of social bookmarking and ranking-rating, by actual humans.

This is made possible by metadata retrieval methods, commonly referred to as tags, and tagging. This is why you can search for dogs, as an example, and a picture comes up based on your text search term.

This is also referred to a schematic mode. Whereas doing a search with a picture of a dog to locate other dog pictures is referred to as paradigmatic mode.

However, metadata retrieval, search, and identify methods severely lack in being able to properly define uniform space and texture descriptions, such as the spatial relationships between 3D objects, etc.

The Content-Based Retrieval multimedia database search method (CBR), however, is specifically based on these types of searches. In other words, if you were to search an image or sub-image; you would then be shown other images or sub-images that related in some way to your the particular search, by way of color ratio or pattern, etc.

What is Data Management?

Data Management is a broad field of study, but essentially is the process of managing data as a resource that is valuable to an organization or business. One of the largest organizations that deal with data management, DAMA (Data Management Association), states that data management is the process of developing data architectures, practices and procedures dealing with data and then executing these aspects on a regular basis.


There are many topics within data management, some of the more popular topics include data modeling, data warehousing, data movement, database administration and data mining.

Data Modeling

Data modeling is first creating a structure for the data that you collect and use and then organizing this data in a way that is easily accessible and efficient to store and pull the data for reports and analysis. In order to create a structure for data, it must be named appropriately and show a relationship with other data. It also must fit appropriately in a class. For instance, if you have a database of media, you might have a hierarchal structure of objects that include photos, videos, and audio files. Within each category, you can classify objects accordingly.

Data Warehousing

Data warehousing is storing data effectively so that it can be accessed and used efficiently. Different organizations collect different types of data, but many organizations use their data the same way, in order to create reports and analyze their data to make quality business decisions. Data warehousing is usually an organizational wide repository of data, however for very large corporations in can encompass just one office or one department.

Data Movement

Data movement is the ability to move data from one place to another. For instance, data needs to be moved from where it is collected to a database and then to an end user, but this process takes quite a bit of logistic insight. Not only do all hardware, applications and data collected need to be compatible with one another, they must also be able to be classified, stored and accessed with ease within an organization. Moving data can be very expensive and can require lots of resources to make sure that data is moved efficiently, that data is secure in transit and that once it reaches the end user it can be used effectively either to be printed out as a report, saved on a computer or sent as an email attachment.

Database Administration

Database administration is extremely important in managing data. Every organization or enterprise needs database administrators that are responsible for the database environment. Database administrators are usually given the authority to do the following tasks that include recoverability, integrity, security, availability, performance and development & testing support.

Recoverability is usually defined as a way to store data as a back up and then test the back ups to make sure that they are valid. The task of integrity means that data that is pulled for certain records or files are in fact valid and have high data integrity. Data integrity is extremely important especially when creating reports or when data is used for analysis. If you have data that is deemed invalid, your results will be worthless.

Database security is an essential task for database administrators. For instance, database administrators are usually in charge of giving clearance and access to certain databases or trees in an organization. Another important task is availability. Availability is defined as making sure a database is up and running. The more up time, usually the higher level of productivity. Performance is related to availability, it is considered getting the most out of the hardware, applications and data as possible. Performance is usually in relation to an organizations budget, physical equipment and resources.

Finally, a database administrator is usually involved in database development and testing support. Database administrators are always trying to push the envelope, trying to get more use out of the data and add better performing and more powerful applications, hardware and resources to the database structure. A database that is administered correctly is not only a sign of competent database administrator, but it also means that all end users have a huge resource in the data that is available. This makes it easy to create reports, conduct analysis and make high quality decisions based on data that is collected and used within the organization.

Data Mining

Another important topic regarding data management is data mining. Data mining is a process in which large amounts of data are sifted through to show trends, relationships, and patterns. Data mining is a crucial component to data management because it exposes interesting information about the data being collected. It is important to note that data is primarily collected so it can be used to find these patterns, relationships and trends that can help a business grow or create profit.

While there are many topics within data management, they all work together from the beginning where data is collected to the end of the process where it is sifted through; analyzed and formatted where specialists can then make quality decisions based upon it.

What is Data Mining?

Data mining is usually defined as searching, analyzing and sifting through large amounts of data to find relationships, patterns, or any significant statistical correlations. With the advent of computers, large databases and the internet, it is easier than ever to collect millions, billions and even trillions of pieces of data that can then be systematically analyzed to help look for relationships and to seek solutions to difficult problems. Besides governmental uses, many marketers use data mining to find strong consumer patterns and relationships. Large organizations and educational institutions also data mine to find significant correlations that can enhance our society.


While data mining is amoral in the fact that it only looks for strong statistical correlations or relationships, it can be used for either good or not so good purposes. For instance, many government organizations depend on data mining to help them create solutions for many societal problems. Marketers use data mining to help them pin point and focus their attention on certain segments of the market to sell to, and in some cases black hat hackers can use data mining to steal and scam thousands of people.

How does data mining work? Well the quick answer is that large amounts of data are collected. Usually most entities that perform data mining are large corporations and government agencies. They have been collecting data for decades and they have lots of data to sift through. If you are a fairly new business or individual, you can purchase certain types of data in order to mine for your own purposes. In addition, data can also be stolen from large depositories by hackers by hacking their way into a large database or simply stealing laptops that are ill protected.

If you are interested in a small case study on how data mining is collected, used and profited off of, you can look at your local supermarket. Your supermarket is usually an extremely lean and organized entity that relies on data mining to make sure that it is profitable. Usually your supermarket employs a POS (Point Of Sale) system that collects data from each item that is purchased. The POS system collects data on the item brand name, category, size, time and date of the purchase and at what price the item was purchased at. In addition, the supermarket usually has a customer rewards program, which also is input into the POS system. This information can directly link the products purchased with an individual. All this data for every purchase made for years and years is stored in a database in a computer by the supermarket.

Now that you have a database with millions upon millions of data fields and records what are you going to do with it? Well, you data mine it. Knowledge is power and with so much data you can uncover trends, statistical correlations, relationships and patterns that can help your business become more efficient, effective and streamlined.

The supermarket can now figure out which brands sell the most, what time of the day, week, month or year is the most busiest, what products do consumers buy with certain items. For instance, if a person buys white bread, what other item would they be inclined to buy? Typically we can find its peanut butter and jelly. There is so much good information that a supermarket can use just by data mining their own data that they have collected.

What is a Data Warehouse?

A data warehouse is a place where data is stored for archival purposes, analysis purposes and security purposes. Usually a data warehouse is either a single computer or many computers (servers) tied together to create one giant computer system.


Data can consist of raw data or formatted data and can be on various types of topics including an organization's sales, salaries, operational data, summaries of data including reports, copies of data, human resource data, inventory data, external data to provide simulations and analysis, etc.

Besides being a store house for large amounts of data, they must possess systems in place that make it easy to access the data and use it in day to day operations. A data warehouse is sometimes said to be a major part in a decision support system. A way for an organization to use data to come up with facts, trends or relationships that can help them make effective decisions or create effective strategies to accomplish their goals.

There are many different models of data warehouses including Online Transaction Processing which is a warehouse built for speed and ease of use. Another type of data warehouse is called Online Analytical processing, this type of warehouse is more difficult to use and adds an extra step of analysis within the data. Usually it requires more steps which slows the process down and much more data in order to analyze certain queries.

In addition to this model, one of the more common data warehouse models include a data warehouse that is subject oriented, time variant, non volatile and integrated. Subject oriented means that data is linked together and is organized by relationships.

Time variant means that any data that is changed in the data warehouse can be tracked. Usually all changes to data are stamped with a time date and with a before and after value, so that you can show the changes through out a period of time.

Non volatile means that data is never deleted or erased. This is a great way to protect your most crucial data. Because this data is retained, you can continue to use it in a later analysis. Finally, the data is integrated, which means that a data warehouse uses data that is organizational wide instead of from just one department.

Besides the term data warehouse, a term that is frequently used is a data mart, data marts are smaller, less integrated data housings. They might be just a database on human resources records or sales data on just one division.

With improvements in technology, as well as innovations in using data warehousing techniques, data warehouses have changed from Offline Operational Databases to include an Online Integrated data warehouse.

Offline Operational Data Warehouses are data warehouses where data is usually copied and pasted from real time data networks into an offline system where it can be used. It is usually the simplest and less technical type of data warehouse.

Offline Data Warehouses are data warehouses that are updated frequently either daily, weekly or monthly and that data is then stored in an integrated structure, where others can access it and perform reporting.

Real Time Data Warehouses are data warehouses where it is updated each moment with the influx of new data. For instance, a Real Time Data Warehouse might incorporate data from a Point of Sales system and is updated with each sale that is made.

Integrated Data Warehouses are data warehouses that can be used for other systems to access them for operational systems. Some Integrated Data Warehouses are used by other data warehouses, allowing them to access them to process reports, as well as look up current data.

So why should you or your organization use a Data Warehouse? Here are some of the pros and cons of using this type of structure for data.

The number one reason why you should implement a data warehouse is so that employees or end users can access the data warehouse and use the data for reports, analysis and decision making. Using the data in a warehouse can help you locate trends, focus on relationships and help you understand more about the environment that your business operates in.

Data warehouses also increase the consistency of the data and allows it to be checked over and over to determine how relevant it is. Because most data warehouses are integrated, you can pull data from many different areas of your business, for instance human resources, finance, IT, accounting, etc.

While there are plenty of reasons why you should have a data warehouse, it should be noted that there are a few negatives of having a data warehouse including the fact that it is time consuming to create and to keep operating.

You might also have a problem with current systems being incompatible with your data. It is also important to consider future equipment and software upgrades; these may also need to be compatible with you data.

Finally, security might be a huge concern, especially if your data is accessible over an open network such as the internet. You do not want your data to be viewed by your competitor or worse hacked and destroyed.

What are Java Databases?

hsqldb

HSQLDB is the leading SQL relational database engine written in Java. HSQLDB has a JDBC driver and supports a rich subset of ANSI-92 SQL (BNF tree format) plus SQL 99 and 2003 enhancements. HSQLDB offers a small (less than 100k in one version), fast database engine which offers both in-memory and disk-based tables. Embedded and server modes are available. Additionally, it includes tools such as a minimal web server, in-memory query and management tools (can be run as applets) and a number of demonstration examples.


The product is currently being used as a database and persistence engine in many Open Source Software projects and even in commercial projects and products. In it's current version it is extremely stable and reliable. HSQLDB is best known for its small size, ability to execute completely in memory and its speed.

This feature-packed software is completely free under our licenses , based on the standard BSD license. Yes, that's right, completely free of cost or onerous restrictions and fully compatible with all major open source licenses. Java source code and extensive documentation always included.

Berkeley DB Java Edition

Berkeley DB JE is a high performance, transactional storage engine written entirely in Java. Like the highly successful Berkeley DB product, Berkeley DB JE executes in the address space of the application, without the overhead of client/server communication. It stores data in the application's native format, so no runtime data translation is required. Berkeley DB JE supports full ACID transactions and recovery. It provides an easy-to-use interface, allowing programmers to store and retrieve information quickly, simply and reliably.

Berkeley DB JE was designed from the ground up in Java. It takes full advantage of the Java environment. The Berkeley DB JE API provides a Java Collections-style interface, as well as a programmatic interface similar to the Berkeley DB API. The architecture of Berkeley DB JE supports high performance and concurrency for both read-intensive and write-intensive workloads.

Berkeley DB JE is different from all other Java databases available today. Berkeley DB JE is not a relational engine built in Java. It is a Berkeley DB-style embedded store, with an interface designed for programmers, not DBAs. Berkeley DB JE's architecture employs a log-based, no-overwrite storage system, enabling high concurrency and speed while providing ACID transactions and record-level locking. Berkeley DB JE efficiently caches most commonly used data in memory, without exceeding application-specified limits. In this way Berkeley DB JE works with an application to use available JVM resources while providing access to very large data sets.

The Berkeley DB JE architecture provides an underlying storage layer for any Java application requiring high performance, transactional integrity and recoverability.

IBM Cloudscape

IBM Cloudscape is a pure, open source-based Java relational database management system that can be embedded in Java programs and used for online transaction processing (OLTP). A platform-independent, small-footprint (2MB) database, Cloudscape integrates tightly with any Java-based solution.

What is JDBC?

JDBC (Java Data Base Connectivity) is an API (Application Programming Interface) for connecting to databases from the Java environment.


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JDBC is an alternative to ODBC. JDBC's Java interface is more comfortable to Java programmers than ODBC's C language interface.
JDBC is included with both J2SE and J2EE.
If no JDBC driver is available for your needs, a JDBC-ODBC bridge may be used to connect to an ODBC driver via the JDBC API. Java 2 includes a JDBC-ODBC bridge for Solaris and Microsoft Windows.

Where can I get an Oracle ODBC Driver?

The Oracle ODBC Drivers Dowload Page is the source for official Oracle ODBC drivers.


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The Easysoft ODBC Oracle Driver improves on the stock Oracle ODBC drivers by providing improved performance and easier maintenance.
OpenLink Software provides both Single-Tier and Multi-Tier Oracle ODBC drivers.
DataDirect Connect for ODBC is a replacement Oracle ODBC driver which provides improved performance and easier maintenance.
Attunity provides a data adapter which includes an