Чем oracle отличается от ms sql

Oracle vs SQL Server – Difference Between Them

Oracle database is an RDMS system from Oracle Corporation. The software is built around the relational database framework. It allows data objects to be accessed by users using SQL language. Oracle is a completely scalable RDBMS architecture which is widely used all over the world.

Oracle is one of the biggest vendor in the IT market and the shorthand name of its flagship RDBMS product, that was formally called Oracle Database.

What is Microsoft SQL server?

MS SQL server is a database product of Microsoft. It allows users to SQL queries and execute them. It is among the most stable, secure and reliable database solutions. It supports wide variety of transaction processing, analytics, and business intelligence applications in corporate IT environments.

Difference between SQL Server and Oracle

Early History of Microsoft SQL:

In 1987, Microsoft partnered with Sybase Solutions for developing DBMS which may compete with other IT giants like IBM and Oracle. Both these companies agreed that Sybase will have all the selling rights and profit earned from the product designed for the Non-Microsoft platform.

Microsoft, on the other hand, will have rights to the database product designed for Microsoft Platforms. In 1989 the first database server product version was released.

After that, Microsoft purchase all the rights from Sybase and they changed the name to MS SQL Server. Till date, 30 versions of MS SQL, has been released.

Early History of Oracle:

Oracle Corporation has a distance long journey to become the multinational technology company that it has at the current time.

In 1977 the Oracle Organisation was founded by two developers, Larry Ellison and Bob Miner. Both had prior experience in developing database software for different organizations.

In the year 1978, they were able to build a first RDBMS using SQL. This software is known as Oracle Relational Database Management System.

Oracle became the first company to sell the RDBMS software and within 1982 had yearly revenue of $2.5 million.

Oracle vs SQL Server

By Priya Pedamkar

Difference Between Oracle and SQL Server

Oracle provides a relational data management system for internal use called as Oracle server. The framework is based on the relational database. The data objects can be assessed by the users using the SQL language. We can scale Oracle based on the requirement, and it is used widely all over the world. Microsoft developed a SQL server that allows users to write queries and execute them based on their needs. Any processes such as transactions, analytics, and business intelligence are handled in corporate environments using SQL. Online support is provided in SQL, and also warning messages are displayed for errors.

Oracle

The Oracle database feature to be used for enterprise grid computing helps in the creation of modular servers and storage where the storage mechanism is achieved by creating logical and physical structures. The Database can be accessed only using a client-side program. The server-side memory structure is referred to as the SGA (System Global Area), which is responsible for holding cache information related to SQL commands, data buffers, log history, and user-specific information. Scaling, rerun production workloads for both batch and online real-time user, support for virtualization techniques, VMWare support, high availability, and uninterrupted processing makes it a beautiful and elegant database to be used.

Web development, programming languages, Software testing & others

SQL Server

The SQL Server Database Engine controls data storage, security, and processing. The relational engine processes queries and commands, and the storage engine present in it is responsible for managing database files, pages, tables, data buffers, indexes, and transactions. Triggers, views, stored procedures and other database objects are the ones that are taken care of by the Database Engine. This can be used for deploying, building, and managing applications located on-prem or on the cloud. The data present inside it is usually connected, avoids redundancy, thereby providing greater data integrity. The newer version has built-in performance tuning metrics, real-time operational analytics, data visualization strategies hybrid cloud support using which the database administrators can run the same application on either on-prem or on the cloud as they deem fit to lower organizational cost.

Head To Head Comparison Between Oracle and SQL Server (Infographics)

Below is the top 14 difference between Oracle vs SQL Server

Key Difference between Oracle and SQL Server

Both Oracle vs SQL Server are popular choices in the market; let us discuss some of the major Difference:

The language used in SQL Server and Oracle RDBMS is different even when they both use different forms of Structured Query Language. MS server used transact SQL whereas Oracle makes use of PL/SQL Procedural Language and a Structured Query Language. The main difference lies in the variables, syntax, and procedure handling, along with built-in functions. The provision of grouping procedures together into packages is something that is not available with MS SQL Server.

The other major feature between these two databases is the capability of transaction control. A transaction is defined as a group of operations and tasks to be treated as a single unit. MS SQL will, by default, commit and execute each command/task as a unit and roll backing is difficult. The commands to make this process a lot more efficient are BEGIN TRANSACTION, COMMIT, ROLLBACK, END TRANSACTION, etc. In the case of Oracle, every database connection is a new connection treated as a new transaction. All the changes are made in memory, and nothing is actually done explicitly unless an external COMMIT command is not used.

Database objects organization is different for both the databases. In the case of MS SQL, all the database objects such as views, tables, and procedures are sorted by database names. The logins assigned to the users are granted access to specific objects and databases. The file in an SQL server is of a private, unshared disk type, whereas in the case of Oracle, all this is arranged as per schemas and shared among the relevant users. Every schema and users’ accesses are governed by the roles and permissions assigned to that group.

Oracle vs SQL Server Comparison Table

Let us discuss the comparison between Oracle vs SQL Server are as follows:

Conclusion

In this Oracle vs and SQL Server article, we have seen that both are powerful RDBMS options, and there is a multitude of differences that help in exploring the right fit for your organization, but they are almost similar in most of ways. Choosing the right database is of extreme importance for the company, and therefore a thorough analysis is a must before actually adopting it. Stay tuned to our blog for more articles like these. Databases are the primary asset of any organization as they keep all the essential and important data of an organization. The data, which is in a structured format, is commonly stored with what is popularly known as the RDBMS (Relational Database Management System). This is a normalized format where the values are stored in column and row format. Popular RDBMS are MS Access, MySQL, Sybase, and Oracle and SQL server are also among widely used databases. There are also many similarities and quite many differences between Oracle vs SQL server. We will be looking at a broader and a detailed aspect in this Oracle vs SQL server post.

Recommended Articles

This has been a guide to the top difference between Oracle and SQL Server. Here we also discuss the key differences with infographics and comparison table. You may also have a look at the following articles to learn more.

SQL Server vs. Oracle Database: What You Need to Know

By Doug Breaker

The world of big data is expanding by the second. Businesses large and small are struggling to manage the information under their command. This data includes sales figures, marketing campaign statistics, customer preferences and behavior, and more. Hidden away in this data are many potentially valuable insights that can help your company and your employees perform better.

According to a 2016 survey by HubSpot, the average organization now oversees 163 terabytes of information . That’s enough space to store 40,000 feature-length movies on DVD.

For companies that grow and scale, finding the best way to efficiently handle this information is challenging. Most large enterprises have traditionally stored their data in a relational database management system (RDBMS).

Microsoft SQL Server and Oracle Database are two of the most popular, time-tested options for relational database management in large enterprises. Because they’re both very strong alternatives, making the choice between SQL Server and Oracle isn’t always easy. You’ll need an in-depth analysis of each one’s capabilities, as well as your goals and needs as an organization.

In this article, we’ll go over everything you need to know when comparing Oracle vs. SQL Server. We’ll start with an overview of relational databases, and then discuss the facts about both alternatives and the pros and cons of using them.

What is an RDBMS?

Different types of databases have their own methods of organizing and connecting information. A relational database management system (RDBMS) uses the concept of relational databases to manage data..

Relational databases are databases that organize information in tables with columns and rows. Big data experts refer to this approach as the “relational model.”

Familiar with spreadsheet applications such as Microsoft Excel? You already have a good idea of what the relational model looks like. Excel lacks the performance and sophistication of a true relational database. Yet like a relational database, Excel uses rows and columns to store information in tables.

Example: University Student Database

Let’s say that you want to store data about the students at a particular university. This data includes their name and contact information, as well as the classes that they’re taking.

There are multiple ways to organize information under the relational model. For example, one table could hold the students’ personal information. You could also have one table for each class offered at the university.

The “Students” table will have columns such as:

• first_name
• last_name
• birthdate
• address
• phone_number
• student_ID

Each column can only contain a specified data type, such as a string, integer, or date. Each row of the table contains the information of a different student.

Let’s also suppose that we have a “Geology101” table. This table contains information about all students who are taking the Geology 101 class.

Note that students can have the same first and last name, but not the same ID number. This means that we should use the “student_ID” field to uniquely identify students, not their names.

Besides the “student_ID” column, the “Geology101” table might also have columns for the student’s exam results, homework scores, and final grade.

Nearly all relational database management systems use SQL (Structured Query Language) , a domain-specific language for storing, accessing, and manipulating information stored in relational databases.

SQL queries are commands that obtain information from a relational database. In general, basic SQL queries use three clauses: SELECT, FROM, and WHERE.

• SELECT specifies the columns that you want to receive in the results.
• FROM specifies the table that you want to query.
• WHERE specifies the conditions that each entry in the table must meet to appear in the results.

Suppose that you want the student IDs of all students enrolled in Geology 101 who received a grade below C on the first midterm. The corresponding SQL query would look like:

WHERE midterm1 < 70;

This query searches the “midterm1” column in the “Geology101” database to find entries that are less than 70 (i.e., a grade below C). It then returns the corresponding entry in the same row under the “student_ID” column.

If you instead want all information about all students enrolled at the university, you could use the simple SQL query:

The asterisk * keyword selects all fields in the database. Note that the WHERE clause is optional in this example.

Relational vs. Non-relational Databases

Relational databases are the most common paradigm for organizing large amounts of information. However, they are by no means the only one.

“Non-relational databases” (also called NoSQL databases) organize data in a manner other than the traditional rows and columns of a relational database. They may take the form of keys and values, graphs, documents, or several other paradigms.

Relational databases are typically only capable of working with structured data . This is information that has been neatly organized into discrete standardized fields.

Non-relational databases, however, excel at working with semi-structured data . This is information that is not organized in fields or records. However, semi-structured data still contains some degree of hierarchy so that you can understand the relations between different entries.

When scaling databases to dozens or hundreds of servers, non-relational databases tend to have better performance. Meanwhile, relational databases are simple and familiar, and perform well for most situations.

Some of the most popular non-relational databases are:

• MongoDB
• Apache Cassandra
• Apache HBase
• Redis
• Neo4j

Meanwhile, the four most popular relational databases are:

• Microsoft SQL Server
• Oracle Database
• MySQL
• IBM DB2

In the rest of this piece, we’ll analyze the pros and cons of two of these relational databases: SQL Server and Oracle Database.

What is SQL Server?

Microsoft SQL Server is an RDBMS developed by Microsoft. First released in 1989, SQL Server now comes in more than a dozen different editions and flavors, each suited for a different purpose and use case. The four main editions of SQL Server 2017 are:

• Enterprise Edition: Includes the core SQL Server database engine as well as add-on services. SQL Server 2017 Enterprise can support databases as large as 524 petabytes (524 million gigabytes), use an unlimited number of processor cores, and access as much memory as permitted by the operating system.
• Standard Edition: Includes the core database engine and standalone services. SQL Server 2017 Standard can support databases as large as 524 petabytes, use up to 24 processor cores, and access up to 128 gigabytes of memory per instance for the buffer pool size. The Standard Edition is missing certain advanced features of the Enterprise Edition, such as Transparent Data Encryption and advanced high availability .
• Express Edition: Includes the core database engine online. SQL Server 2017 Express can support databases as large as 10 gigabytes, use up to 4 processor cores, and access up to 1410 megabytes of memory per instance for the buffer pool size. It is also missing features such as high availability, data integration , and business intelligence .
• Developer Edition: Includes the same features and functionality as Enterprise Edition, but limited by the software license for only development and testing purposes.
  

Each of these four editions is for a different audience. SQL Server Enterprise is for large, high-powered, data-driven organizations, while SQL Server Standard is for organizations with less intensive data needs.

Both the Express and Developer Editions are free of charge. However, they have significant limitations making them unviable as a long-term solution for most organizations.

As one of Microsoft’s flagship products, SQL Server has received constant updates and attention over the years. Recent additions to the platform include new capabilities for performance tuning, real-time operational analytics, big data analytics, data visualization, and hybrid cloud support.

What is Oracle Database?

Oracle Database is an RDBMS developed by Oracle. Like SQL Server, Oracle Database comes in four separate editions intended for different use cases :

• Enterprise Edition (EE): Oracle Database Enterprise Edition is for larger businesses that need a great deal of performance, security, availability, and scalability from their database infrastructure. EE allows businesses to develop high-powered web applications, online transaction processing (OLTP) applications, and data warehouses.
• Standard Edition 2 (SE2): According to Oracle, SE2 “includes all the features necessary to develop workgroup, department-level, and Web applications.” SE2 is largely intended for small and medium businesses, like SQL Server Standard Edition.
• Personal Edition (PE): Personal Edition is for use by a single user on a single machine, and is only available on Windows. PE includes all of the functionality of Enterprise Edition, except for the Oracle Real Application Clusters option.
• Express Edition (XE): Finally, Express Edition is a free-to-use entry-level version of Oracle Database. You can easily upgrade XE to the other versions listed above. XE can store up to 4 gigabytes of data, use 1 gigabyte of memory, and use only 1 CPU.

Most businesses who choose Oracle Database will want to use either EE or SE2. To help you make your decision, the features below are a few of those available in EE but not present in SE2:

for one-way and multi-master replication of data in a distributed system
• Advanced Compression for improving performance and reducing your storage footprint
• Oracle Data Guard for high availability, data protection, and disaster recovery
• Parallel computing for index scans, index rebuilding, and backup & recovery

Like SQL Server, Oracle Database has been innovating in recent years to keep up with customers’ demands for processing big data. Oracle Database is easy to integrate with Oracle’s other enterprise software: accounting, enterprise resource planning (ERP), customer relationship management (CRM), etc.

SQL Server vs. Oracle Database: Pros, Cons, and Differences

We’ll now discuss some of the most important points of distinction between SQL Server and Oracle. This will help you come to a final decision that’s right for your situation.

Platform Dependency

As a Microsoft product, SQL Server has traditionally only been available for the Windows operating system. However, beginning with SQL Server 2017, the platform is now available on Linux as well. Note that if you want to use an earlier version of SQL Server, you will have to use it with Windows.

Oracle, meanwhile, has a long history of supporting both Windows and Linux. Oracle Database is also available for other Unix-based operating systems such as Oracle Solaris, IBM AIX, and HP-UX. However, neither Oracle nor SQL Server supports Mac OS X.

For decades, Oracle has had better scalability and security than SQL Server, making it better suited for large enterprises. In addition, SQL Server was available only for Windows, leaving Linux users out in the cold.

This perception has evolved in recent years. Both Oracle and SQL Server have released mature enterprise and standard versions of their platform, for both Windows and Linux.

Most analysts would agree that Oracle still has a slight edge over Microsoft in terms of both core database features and cutting-edge functionality. However, these extra capabilities have a downside. Oracle is typically more complex to manage, has a higher learning curve, and costs more to maintain.

Both Oracle and SQL Server come with their own “dialect” of the SQL language that extends the basic functionality of SQL. Oracle uses PL/SQL (Procedural Language/SQL) , while SQL Server uses T-SQL (Transact-SQL) .

As such, database administrators who specialize in Oracle, or in SQL Server, will “speak” a slightly different version of SQL. PL/SQL and T-SQL each have their own distinct features, abilities, and syntax.

The main differences between PL/SQL and T-SQL are how the two languages handle variables, stored procedures , and built-in functions. PL/SQL also allows users to group procedures together into packages, which isn’t possible with T-SQL.

Syntax and Schema

Using Oracle and SQL Server “feels different” not only due to the flavor of SQL, but also due to the many variations in their syntax and schema. For example, because DATE is a reserved word in Oracle but not SQL Server, it’s perfectly legal to have a column named DATE in SQL Server (but not Oracle).

In addition, many data types that are the same under the hood have different names in SQL Server and Oracle. For example, the INTEGER type in SQL Server and the NUMBER(10) type in Oracle serve the same purposes.

These differences are mainly cosmetic, but important if you’re planning a migration from one platform to the other. To see a full list of the differences in syntax, data types, and schema, you can check this page on the Oracle website .

Transaction Control

Transaction control is another important point of departure between Oracle and SQL Server. In a relational database, a transaction is a single unit of work that may contain multiple operations or tasks. So as not to cause discrepancies in the data, the database must either apply or roll back all of the operations in the transaction. A single failed operation will cause the entire transaction to fail.

For example, when customers transfer money between their checking and savings accounts, the transfer should be a single transaction. This transaction consists of three operations:

• Removing the money from the checking account
• Adding the money to the savings account
• Recording the transfer in the bank ledger

If any one of these operations fails, the database must roll back the entire transaction so that the customer’s account balances are correct.

SQL Server executes the operations in a transaction sequentially and individually. This makes it difficult or even impossible to roll back the transaction if an error occurs partway through. The BEGIN TRANSACTION command declares the beginning of a transaction, and the COMMIT command declares the end. Roll backs are not possible beyond the most recent COMMIT statement.

In Oracle, however, each new connection to the database is a new transaction. For most use cases, the database makes changes in memory and commits them only with an explicit COMMIT statement. This is more flexible and allows for greater manual control of errors.

Price and Total Cost

Much about SQL Server vs. Oracle is a matter of opinion, but what’s not up for debate is the price comparison. SQL Server licenses are significantly cheaper than Oracle.

By one estimate, a server with 4 CPUs and 4 cores per CPU would cost $380,000 with Oracle , but just $114,000 with SQL Server. The costs rise even higher with extra features such as table partitioning, data compression, and online analytical processing (OLAP).

While the sticker price may be lower on SQL Server, you should also consider the total cost of ownership over the lifetime of the database. This includes considerations such as support, maintenance, and productivity during day-to-day use.

In this respect, Oracle seems to win out, according to one study of Oracle Database 11g and Microsoft SQL Server 2015. Skilled database administrators can perform typical functions 41 percent more quickly in Oracle than in SQL Server.

These time savings add up over time. The same study estimates that Oracle’s improvements to DBA productivity can save businesses up to $33,000 per DBA per year.

Final Thoughts

In previous years and decades, the question of Oracle vs. SQL Server was easier to answer. With more features and greater complexity, Oracle was better for large enterprises that needed high performance. SQL Server was better for organizations that didn’t want to go all-out.

However, the lines are beginning to blur with newer releases of both SQL Server and Oracle. Both Oracle and SQL Server are mature, excellent choices for relational database management.

In the end, you should choose the right tool for the job in terms of your existing tech setup, in-house skill set, budget, vendors, and customers. Need advice on the Oracle vs. SQL Server question? Contact an experienced database partner who can help give the right advice.

MS SQL Server vs Oracle

The most important thing about today’s businesses is its customers, sales, stock, etc. data. There is no secret that businesses cannot function without data nowadays. There are many different database management systems available out there. Some DBMS examples include Microsoft Access, MySQL, PostgreSQL, Mongo DB, Oracle, and MSSQL. MS SQL Server and Oracle are two of the most and widely used databases. There are many similarities and differences between these two database management systems. This article mainly focuses on comparing the key features and functions of MS SQL and Oracle databases.

Used Language in MS SQL and Oracle

Both MS SQL and Oracle use a version of Structured Query Language (SQL). Transact SQL or T-SQL use in MS SQL. This is an extension of originally developed SQL by Sybase. Oracle uses Procedural Language/SQL (PL/SQL). Both are different variations of SQL and these two have different capabilities and syntax. How these languages handle variables, functions and stored procedures are the main differences between these languages. MS SQL provides options to group procedures into packages, but PL/SQL in Oracle provides this option.

Handling Transaction Control

Another major difference between MS SQL and Oracle is the Transaction Control. MS SQL will by default execute and commit each task or command individually. Hence, it will be not easy or impossible to roll back transactions if any error occurred in the process. “Begin Transaction” command is used at the beginning of a transaction for properly group statements. Meanwhile, the “Commit” statement is used at the end of the group statement. The changed data writes to the disk and ends the transaction in Commit statement. In the transaction, any changes made within the transaction block will be discarded in the Rollback. But, with proper error handling, the rollback command can allow some protection against data corruption.

In Oracle, each new database connection is treated as a new transaction. Until the transaction committed, the transaction can be rolled back, and all the changes are made on the system memory. Because of that, in the rollback, all the changes in the statement can be undone. After the commit is done, essentially the next command initiates a new transaction. This helps to control errors easily and provide flexibility.

Organization of Database Objects

MS SQL organizes all the objects like tables, procedures, and views by database names. And, MS SQL databases have unshared and private disk files on a computer. Users are assigned to login and grant access to the selected database and its objects. But in Oracle, the database objects are grouped by using schemas. Schemas are a subset collection of database objects. All the database objects can be shared with all users and schemas. Schemas and tables access can be limited via roles and permissions.

Platform Support

MS SQL Server and Oracle have different opinions on platform support. Microsoft ensures MS SQL server only runs on Windows platforms until the latest versions. In 2016, Microsoft has announced that MS SQL server runs on Linux platforms. Further, they released MS SQL Server 2017 version for Linux platforms or Docker containers. But, Oracle has a huge platform support advantage when it compares to MS SQL Server. Because Oracle supports more than 50 platforms, it specifically separates the operating system created to run the Oracle system as efficient and reliable as much as possible, including Oracle Linux. Additionally, Oracle runs on Microsoft Windows as well.

Concurrency

Concurrency is one of the main advantages compared to a spreadsheet in the database. The servers sort out the changes to maintain integrity when users are reading and wring data to a database. MS SQL Server and Oracle handle these concurrent processes in many different ways. Oracle allows reading during the writer process, while the SQL Server holds new reads until the writer completes it. Oracle writers do not block the readers and readers do not block the writers. That’s the reason that Oracle runs much quicker than the SQL Server.

Triggers

Microsoft SQL Server and Oracle have implemented triggers in different ways. Oracle has implemented before and after triggers. But in MS SQL Server, it only allows after triggers. Before triggers helps to check availability, but in SQL server it takes unnecessary work to check availability. Therefore, it greatly reduces the usefulness of triggers in MS SQL Server.

The standard edition of both database prices is more or less similar for keeping up with the competition. But, there is a big difference between the enterprise editions. The Oracle Enterprise Edition is the highest licensing priced database for its massive scalability and efficiency. However, some versions of Oracle are free for development purposes and in certain cases, Oracle embraces the open-source community. Further, Oracle Express Edition can be used for low demand database applications. Microsoft also provides a free SQL Server Express version to gain a competitive advantage in the market.

Other differences between the two databases are as follows;

In a nutshell, MS SQL Server is ideal for database beginners and small or medium scale data management companies, while Oracle is suitable for those managing larger amounts of data. But, if half of the big companies use Oracle systems, then the rest of the companies use MS SQL. On a high-level note, there is not much difference between these two database systems. But there is a difference between the underlying architecture and the syntax.