In this modern age, we use technology for everyday purposes such as making payments and in ATMs. Companies too take the assistance of analytical systems to power business analytics or financial analysis.
We are highly dependent on systems that are powered by OLTP to make our daily lives easier while organizations depend on OLAP to gather business intelligence and insights, create reports and conduct analysis of its finances, sales, the management, or other departments such as marketing.
OLAP and OLTP are fundamentally very different as OLAP is built for the purpose of handling analytical queries and OLTP exists to power operational requests. OLAP can be reliant on OLTP while OLTP does not depend on OLAP.
When it comes to OLAP vs. OLTP, the functions of these processing systems vary across different requirements and the benefits they can offer depend on the fundamental utility they can provide for different problems.
What are DBMS and RDBMS?
DBMS or database management systems are administration systems that manage databases holding data by taking requests from users using languages such as standard query language or SQL. Users must use SQL to submit requests for managing data and DBMS then allows the data to be accessed or modified.
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RDBMS stands for relational database management systems. And, these are database management systems that store data following relational structures. The data is allocated in tables or logical units which are connected to each other through keys.
What is OLTP?
OLTP stands for online transactional processing and it can be defined as a type of data processing that focuses on tasks such as insertion of data, updating data or deletion of minor amounts of data inside a database.
Fundamentally, OLTP is geared towards transaction-oriented tasks and designed to handle an immense number of transactions initiated by a massive pool of users in multiple access environments. OLTP uses DBMS to function and a great example of OLTP systems is checkout kiosks or ATM networks.
OLTP is completely transaction-centric and will always revolve around the specific goal of assisting the transaction processing while retaining data integrity.
What is OLAP?
OLAP stands for online analytical processing and is known for performing multidimensional analysis of business data from different perspectives, allowing the implementation of complex calculations, advanced data modelling and trend analysis.
OLAP is used in applications such as business, finance and management reporting, forecasting, and business process management. Also, it makes way for various other business intelligence functionalities. OLAP uses data warehouses to function and has a wider range of use as compared to OLTP even though it relies heavily on OLTP to function.
Differences Between OLTP and OLAP
The basic difference between OLTP and OLAP is that the former works with the processing of transactions, while the latter is more focused on analytical processing. Here are the various differences that can be observed when we talk about OLTP vs OLAP:
- OLTP vs OLAP Uses: OLTP systems power fundamental tasks that are required for systems to function while OLAP provides complex problem-solving abilities and offers valuable insights to make better business decisions. OLTP is more focused on real-time operations rather than the analytics and planning utility that OLAP provides.
- OLTP vs OLAP Methodology: OLTP uses the traditional database management systems to function while OLAP uses data warehouses to power its processes. OLTP is an online transactional system while OLAP is focused on analysis and data retrieval. OLTP conducts both read and write operations while OLAP mostly focuses on reading operations only.
- OLTP vs OLAP Design: OLTP boasts of application-oriented designs while OLAP follows a subject-oriented design. OLTP contains normalised tables while OLAP does not host normalised tables. Also, OLTP contains organised and detailed data, while OLAP might contain disorganised data.
- OLTP vs OLAP Recovery and Back up: OLTP goes through a complete regular backup while doing occasional backup for extra security. OLAP does not conduct regular backup and depends on being reloaded as a recovery option.
- OLTP vs OLAP Queries: OLTP queries are very simple and standard such as insertion, deletion, and simple modifications. However, OLAP queries are operational in nature and far more complex.
- OLTP vs OLAP Users: OLTP is a market-oriented process and can support thousands of users while OLAP is a user-oriented process supporting much lesser users as compared to OLTP which is specifically built to support a huge amount of transactions. OLTP is used from the user-end by shoppers, clerks, transactors and from the backend, by DBAs and database managers while OLAP is used by analysts, managers and CEOs.
- OLTP vs OLAP Data Integrity: Due to OLTP powering functions that need to be secured, OLTP systems must always maintain data integrity and protect the data while in the case of OLAP, databases are modified rarely; hence decreasing integrity issues.
- OLTP vs OLAP Speed: OLTP is very fast and can process transactions in milliseconds while OLAP takes more time to process its queries; complex queries taking minutes at a time. Updates are fast as well for OLTP systems while OLAP requires data to be refreshed regularly and takes a long time on each occasion.
- OLTP vs OLAP Data Sources: OLTP systems use operational data which comes directly from the source. Meanwhile, OLAP systems use multiple OLTP databases to function.
Benefits of OLTP and OLAP
OLTP and OLAP both have many benefits and provide incredible value to companies. Here are some benefits that OLTP and OLAP provide:
- OLAP provides a one-stop platform to power business analysis, intelligence and insights tools to assist businesses in budgeting, planning and forecasting.
- It is secure and confidential data is protected through restrictions and regulatory functions.
- It offers consistent information and makes accurate calculations.
- OLTP supports daily real-time business activities and transactions.
- It allows many users to use services and promotes simplifying multiple individual processes occurring at the same time.
Drawbacks of OLTP and OLAP
Like all systems, OLTP and OLAP have some disadvantages as well. Here are the disadvantages of OLTP and OLAP:
- OLAP can only be effectively used by IT professionals as most tools require complex modelling.
- It needs employees from multiple departments to cooperate to effectively use its set of tools.
- OLAP systems are costly to build as compared to OLTP systems.
- Many sensitive services depend on OLTP and hardware failure can severely affect hundreds of transactions and users.
- OLTP systems turn more complex as massive amounts of users can gain access and modify data parallelly.
Frequently Asked Questions
OLTP is highly necessary and powers real-time business systems. Also, it helps businesses assess their financial, sales and other information to help get valuable insights to make better decisions. Moreover, OLAP uses OLTP to power many of its services.
Data warehouses are used by OLAP systems. And, the data housed in data warehouses can be analysed by OLAP systems to offer insights or make predictions. Data warehouses can be described as being OLAP processes.
No, SQL server is neither OLTP nor OLAP. However, both OLTP and OLAP use SQL server to power many of their functions.
Microsoft Analysis Services is an example of great data mining and OLAP tool that is built upon Microsoft SQL Server. Apache Kylin is another great example of OLAP.
Data warehouses are data management systems that help companies conduct analysis, helping support business decisions. They contain massive collections of business data that can be used to power analytics and business intelligence.
RDBMS are database management systems that follow relational structures to administrate databases.
Transaction processing is a type of information processing that divides computing operations into independent invisible operations referred to as transactions. Notably, the transactions must be completed or must fail as a singular unit and not be completed partially.
Relational model is a method of data management that uses relational structures to group and represent data.
ATMs, ticket booking, order management systems and payment kiosks are examples of OLTP.
Yes, OLTP is specifically built to be normalised and respond rapidly while minimalising data redundancy. Also, the tables are organised in OLTP and queries are fast.
When talking about OLTP vs OLAP and wondering which is more effective between the two, one must consider the requirement and type of operation to utilize these processing systems as they are meant for different purposes.
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OLTP serves to be used for empowering businesses and users to conduct online transactions and data modifications while OLAP is built to provide insights to corporations by offering analytical tools. OLTP caters to all kinds of users across all levels of authorization while OLAP serves the interests of organizations and companies.
OLTP and OLAP both serve businesses very well and are highly valuable assets that allow many services to function.