- Relational Database For Os X 10
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- Relational Database Vs Non Relational
- Relational Database For Os X Factor
- Relational Database For Mac Os X
Jul 22, 2013 A non-relational database is a database that does not incorporate the table/key model that relational database management systems (RDBMS) promote. These kinds of databases require data manipulation techniques and processes designed to provide solutions to.
Love it or hate it, Mac OS X ships with Unix under its hood. As a user, I worry the Mac experience could degrade into editing brittle text configuration files and typing obscure and unforgiving commands. As a programmer, I’m overjoyed because we Mac users now have access to certain industrial-strength software. Avira for mac os x lion. This is the type of software that drives Fortune 500 companies, calculates extremely complex chemical reactions, and generates the movies we watch. Since I don’t make movies and I’m not a scientist, I’m most interested in the business side of this software. In particular, I’m interested in relational databases.
- Relational database users use a relational database management system to manage these databases. An RDBMS can be defined as a database program that allows database users to perform different queries on relational database data. It’s the software that allows you to add data, update the database, search for values, and retrieve information.
- Apr 16, 2002 Mac OS X System & Mac Software. Relational Database. Thread starter QuackingPenguin; Start date Apr 15, 2002 1; 2; Next. 1 of 2 Go to page. QuackingPenguin Banned.
- Apr 05, 2001 It's an SQL92 Relational Database in it's own right, and can also act as a 'Virtual Database'. This means that you can install it on Mac OS X, and link in tables from multiple back end databases transparently. This gives Mac users access to multiple heterogenous databases across multiple environments transparently.
On the classic Mac OS, FileMaker Pro and 4D dominate the database scene. I’m partial to the newcomer Valentina, while other folks swear by Helix RADE or Frontier [for context, see Matt Neuburg’s articles on these last two. -Adam]. Unfortunately, none of these databases qualify as 'industrial strength.' Don’t get me wrong: they do their jobs well, but they lack the qualities that many database professionals crave: SQL and ACID. But before we dive into those two acronyms, let me introduce you to the relational database model. In the next installment of this article, we’ll look at some of the relational databases that become available to Macintosh users under Mac OS X.
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Relational Databases — Although there are many different types of databases (free form, hierarchical, network and object relational to name a few), the relational database model is the favorite of businesses.
Introduced by mathematician Dr. E. F. Codd in the early 1970s, the model is simple (though most books like to obscure it behind mathematical jargon). Imagine a spreadsheet where you keep a list of your customers:
Notice that you have three columns of information, with each column dedicated to holding a certain nugget of information. You have four customers, each represented by a distinct row.
The relational model calls this data layout a 'table;' a relational database contains one or more tables. Although similar in concept to a spreadsheet, a table is different in that each column can hold only one type of data. For example, it would be illegal to put text into the 'CUSTOMER_ID' column – it can hold only numbers. Also, unlike a spreadsheet, the relational model doesn’t allow cells to hold formulas (each cell must stand alone and can’t refer to another cell).
If you’re used to thinking of databases as a bunch of index cards (as in FileMaker), here’s a helpful guide: a table is analogous to a stack of cards, a row is analogous to a single card (a record), and a column represents a single field on a card.
Now, let’s say you want to keep track of your customers’ purchases. You whip up another table:
You can add rows to this table as customers make purchases. Each purchase has a 'CUSTOMER_ID' column, which can be used to relate a purchase with a customer. For instance, in this table we know that Purchase #1 was made by Customer #1.
Let’s explore how these relationships can work. Given a PURCHASE_ID, it’s easy for us to retrieve the purchaser’s email address. Suppose we’re interested in the fourth purchase; its CUSTOMER_ID field is set to 3. By scanning our customer list for customers with an ID set to 3, we discover a Michael Spindler, email address <[email protected]>.
Relationships can also work the other way: given a CUSTOMER_ID, we can work backwards to compile a list of purchases made. Let’s start off with Steve Jobs, who has a CUSTOMER_ID of 1. Now we scan our purchase list, where we discover three rows with matching CUSTOMER_ID fields: purchases 1, 3, and 5.
By following good design rules when setting up your tables, your database will have little or no duplicate data and will accept only valid data. Another perk is that nothing in your database is tied to a specific program – if you outgrow your current database program, you can move to another without much effort.
Finally, relational databases are very scalable. You can start off on a $400 PC running Linux and migrate the same database to $400,000 IBM big iron. The only difference is speed and reliability. You can see why businesses like relational databases.
Now that you know the general idea about relational databases, we can decode the SQL and ACID acronyms I mentioned earlier.
SQL — SQL stands for Structured Query Language, and is correctly pronounced by spelling out its letters ('ess cue el'). Some folks pronounce it 'sequel,' however this is incorrect: there was a language named SEQUEL that was SQL’s forerunner. A minority pronounce SQL as 'squeal,' which never truly caught on, probably for the same reason SCSI was never pronounced 'sexy' – it sounded silly in the boardroom. ('We’ll need to attach a sexy drive to our squeal server.' Sure you’re going to say that to the big boss.)
SQL is the standard language used to communicate with relational databases. Because it’s actually a full language, users, developers, and software programs can use it to create, alter, and delete tables and the rows of information they contain. The use of a standard language opens relational databases up to a wide variety of interfaces and access methods that would have to be written from scratch individually for other types of databases. That accounts for one of the limitations of traditional Macintosh databases.
Like HTML, SQL is a declarative language. It contains no variables or loops, and is easy to learn even for the non-programmer. With a non-declarative language, you must spell out the steps necessary to complete a task. A declarative language, on the other hand, simply allows you to state the desired end-result. SQL is an older language, and although it is case insensitive, convention capitalizes almost everything. Here’s a valid SQL statement to create the customer table discussed above:
This command creates a table named CUSTOMER with three columns: CUSTOMER_ID, NAME and EMAIL. The CUSTOMER_ID column is defined to hold a number, while the NAME and EMAIL columns are respectively defined to contain 100 and 200 characters.
It’s easy to enter information into a table using the INSERT verb:
Space prohibits me from detailing the syntax for altering and deleting rows and tables, but it’s just as easy as creating and inserting tables and rows.
The key SQL verb is SELECT, which allows you to access and filter information from the database. For example, we can look up a customer’s email address like so:
Here’s the result you get back:
The result takes the form of a table. Granted, in this case it’s a table with only one column, but it’s a table nonetheless.
As a final example, given a name, the following query displays all of a customer’s purchases. It’s okay if you don’t understand it, I just wanted to show off a little of what you can do with SQL.
Here’s the result:
The ACID Test — ACID stands for 'Atomicity, Consistency, Isolation, and Durability.' These are the features that separate the pros (Oracle, PostgreSQL) from the minor leaguers (FileMaker Pro, 4D). When your business rides on the quality of your information, ACID is the feature set that helps you sleep at night.
Atomicity (pronounced 'atom-ih-sit-ee') comes from the word atom and its original meaning: that which is indivisible. In a database, that means that multiple operations are all bundled up into one indivisible transaction. Either all of the transaction’s operations take place, or none of them do. This helps to ensure the database is in a valid state at all times. Alpha nex 5.
Consistency is the principle that only operations that meet all the database’s validity constraints are allowed. The end effect of this is that illegal operations aren’t allowed, whether they are external (perhaps users enter invalid data) or internal (perhaps a disk fills up and a required row can’t be added).
In this wild Web world, databases have to deal with multiple concurrent modifications. But what happens when Alice’s transaction is modifying the table that Bob’s transaction is reading? Isolation ensures that Bob’s transaction sees the table as it existed before Alice’s transaction started or after it completed, but never the intermediate state.
Finally, Durability is the principle that once a transaction is completed, a mere system crash won’t wipe it out. In the real world, this means that transactions aren’t considered completed until the all the information has been written to a disk.
What’s Available? In the next installment of this article, I’ll cover the merits of a handful of database applications that can be run under Mac OS X, such as MySQL, FrontBase, and speculation about Oracle’s possible entry into the Mac field.
Relational Database For Os X 10
[Jonathan 'Wolf' Rentzsch is the embodiment of Red Shed Software and runs a monthly Mac programmer get-together in Northwest Illinois.]
What a Relational Database Is
A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables. In a relational database, each row in the table is a record with a unique ID called the key. The columns of the table hold attributes of the data, and each record usually has a value for each attribute, making it easy to establish the relationships among data points.
A Relational Database Example
Here’s a simple example of two tables a small business might use to process orders for its products. The first table is a customer info table, so each record includes a customer’s name, address, shipping and billing information, phone number, and other contact information. Each bit of information (each attribute) is in its own column, and the database assigns a unique ID (a key) to each row. In the second table—a customer order table—each record includes the ID of the customer that placed the order, the product ordered, the quantity, the selected size and color, and so on—but not the customer’s name or contact information.
These two tables have only one thing in common: the ID column (the key). But because of that common column, the relational database can create a relationship between the two tables. Then, when the company’s order processing application submits an order to the database, the database can go to the customer order table, pull the correct information about the product order, and use the customer ID from that table to look up the customer’s billing and shipping information in the customer info table. The warehouse can then pull the correct product, the customer can receive timely delivery of the order, and the company can get paid.
How Relational Databases Are Structured
The relational model means that the logical data structures—the data tables, views, and indexes—are separate from the physical storage structures. This separation means that database administrators can manage physical data storage without affecting access to that data as a logical structure. For example, renaming a database file does not rename the tables stored within it.
The distinction between logical and physical also applies to database operations, which are clearly defined actions that enable applications to manipulate the data and structures of the database. Logical operations allow an application to specify the content it needs, and physical operations determine how that data should be accessed and then carries out the task.
To ensure that data is always accurate and accessible, relational databases follow certain integrity rules. For example, an integrity rule can specify that duplicate rows are not allowed in a table in order to eliminate the potential for erroneous information entering the database.
The Relational Model
In the early years of databases, every application stored data in its own unique structure. When developers wanted to build applications to use that data, they had to know a lot about the particular data structure to find the data they needed. These data structures were inefficient, hard to maintain, and hard to optimize for delivering good application performance. The relational database model was designed to solve the problem of multiple arbitrary data structures.
The relational model provided a standard way of representing and querying data that could be used by any application. From the beginning, developers recognized that the chief strength of the relational database model was in its use of tables, which were an intuitive, efficient, and flexible way to store and access structured information.
Over time, another strength of the relational model emerged as developers began to use structured query language (SQL) to write and query data in a database. For many years, SQL has been widely used as the language for database queries. Based on relational algebra, SQL provides an internally consistent mathematical language that makes it easier to improve the performance of all database queries. In comparison, other approaches must define individual queries.
Benefits of Relational Databases
The simple yet powerful relational model is used by organizations of all types and sizes for a broad variety of information needs. Relational databases are used to track inventories, process ecommerce transactions, manage huge amounts of mission-critical customer information, and much more. A relational database can be considered for any information need in which data points relate to each other and must be managed in a secure, rules-based, consistent way.
Relational databases have been around since the 1970s. Today, the advantages of the relational model continue to make it the most widely accepted model for databases.
Data Consistency
The relational model is the best at maintaining data consistency across applications and database copies (called instances). For example, when a customer deposits money at an ATM and then looks at the account balance on a mobile phone, the customer expects to see that deposit reflected immediately in an updated account balance. Relational databases excel at this kind of data consistency, ensuring that multiple instances of a database have the same data all the time.
It’s difficult for other types of databases to maintain this level of timely consistency with large amounts of data. Some recent databases, such as NoSQL, can supply only “eventual consistency.” Under this principle, when the database is scaled or when multiple users access the same data at the same time, the data needs some time to “catch up.” Eventual consistency is acceptable for some uses, such as to maintain listings in a product catalog, but for critical business operations such as shopping cart transactions, the relational database is still the gold standard.
Commitment and Atomicity
Relational databases handle business rules and policies at a very granular level, with strict policies about commitment (that is, making a change to the database permanent). For example, consider an inventory database that tracks three parts that are always used together. When one part is pulled from inventory, the other two must also be pulled. If one of the three parts isn’t available, none of the parts should be pulled—all three parts must be available before the database makes any commitment. A relational database won’t commit for one part until it knows it can commit for all three. This multifaceted commitment capability is called atomicity. Atomicity is the key to keeping data accurate in the database and ensuring that it is compliant with the rules, regulations, and policies of the business.
ACID and Relational Databases
Four crucial properties define relational database transactions: atomicity, consistency, isolation, and durability—typically referred to as ACID.
- Atomicity defines all the elements that make up a complete database transaction.
- Consistency defines the rules for maintaining data points in a correct state after a transaction.
- Isolation keeps the effect of a transaction invisible to others until it is committed, to avoid confusion.
- Durability ensures that data changes become permanent once the transaction is committed.
Stored Procedures and Relational Databases
Relational Database For Os X 1
Data access involves many repetitive actions. For example, a simple query to get information from a data table may need to be repeated hundreds or thousands of times to produce the desired result. These data access functions require some type of code to access the database. Application developers don’t want to write new code for these functions in each new application. Luckily, relational databases allow stored procedures, which are blocks of code that can be accessed with a simple application call. For example, a single stored procedure can provide consistent record tagging for users of multiple applications. Remote for mac os x. Stored procedures can also help developers ensure that certain data functions in the application are implemented in a specific way.
Relational Database Vs Non Relational
Database Locking and Concurrency
Conflicts can arise in a database when multiple users or applications attempt to change the same data at the same time. Locking and concurrency techniques reduce the potential for conflicts while maintaining the integrity of the data.
Locking prevents other users and applications from accessing data while it is being updated. In some databases, locking applies to the entire table, which creates a negative impact on application performance. Other databases, such as Oracle relational databases, apply locks at the record level, leaving the other records within the table available, helping ensure better application performance.
Concurrency manages the activity when multiple users or applications invoke queries at the same time on the same database. This capability provides the right access to users and applications according to policies defined for data control.
What to Look for When Selecting a Relational Database
The software used to store, manage, query, and retrieve data stored in a relational database is called a relational database management system (RDBMSf). The RDBMS provides an interface between users and applications and the database, as well as administrative functions for managing data storage, access, and performance.
Several factors can guide your decision when choosing among database types and relational database products. The RDBMS you choose will depend on your business needs. Ask yourself the following questions:
Relational Database For Os X Factor
- What are our data accuracy requirements? Will data storage and accuracy rely on business logic? Does our data have stringent requirements for accuracy (for example, financial data and government reports)?
- Do we need scalability? What is the scale of the data to be managed, and what is its anticipated growth? Will the database model need to support mirrored database copies (as separate instances) for scalability? If so, can it maintain data consistency across those instances?
- How important is concurrency? Will multiple users and applications need simultaneous data access? Does the database software support concurrency while protecting the data?
- What are our performance and reliability needs? Do we need a high-performance, high-reliability product? What are the requirements for query-response performance? What are the vendor’s commitments for service level agreements (SLAs) or unplanned downtime?