Difference Between OLTP And OLAP Databases

What Is OLTP (Online Transaction Processing)?

Online transaction processing system (OLTP) is designed to support transaction-oriented applications related to 3-tier architecture. OLTP stores day-to-day business transactions and is well-suited for querying specific records for example email address of a customer.  OLTP is carried in a client server system and many organizations use database management system to support OLTP.

OLTP systems are used for order entry, financial transactions, customer relationship management. Such systems have large number of users who conduct short transactions. Two important characteristics of OLTP system are concurrence control and atomicity.  Concurrency control guarantees that two users accessing the same data in the database system will not be able to change that data or the user has to wait until the other user has finished processing, before changing that piece of data. Atomicity on the other hand, guarantees that if one step is incomplete or fails during the transaction, the entirety will not continue.

What You Need To Know About OLTP

• Online transaction processing system is designed to support transaction-oriented applications related to 3-tier architecture. OLTP stores day-to-day business transactions and is well-suited for querying specific records for example email address of a customer.
• OLTP is characterized by a large number of short online transactions.
• OLTP reveals a snapshot of ongoing business process.
• It consists only of current operational data. It is used to run and control important business tasks such as Enterprise Resource Planning, and customer relation management.
• The response time of OLTP systems is in milliseconds because queries operate on 5% of the data.
• The data sources in OLTP systems consist of OLTP and their transactions.
• OLTP is designed to manage real time business operations.
• The space requirements in OLTP are relatively smaller if the historical data is archived.
• OLTP database is highly normalized with many tables and relationships.
• OLTP’s main operations are INSERT, UPDATE and DELETE.
• OLTP databases have to maintain the data integrity constraints.
• Data refresh in OLTP are performed fast and produce immediate results.
• OLTP are generally used by front-end employees or staff.
• OLTP allows read and write operations.
• In OLTP, complete backup of the database combined with incremental backups is necessary.
• Transaction throughput is the performance metric.
• OLTP database allows thousands of users.
• OLTP uses traditional DBMS.
• OLTP database is market oriented.
• OLTP helps to increase user’s self-service and productivity.

What Is OLAP (Online Analytical Processing)?

OLAP (online analytical processing) is a computing method that enables users to easily and selectively extract and query data in order to analyze it from different points of view. OLAP business intelligence queries often aid in trends analysis, financial reporting, sales forecasting, budgeting and other planning purposes.

OLAP is often used in data mining. The chief component of OLAP is the OLAP server, which sits between a client and database management systems (DBMS). The OLAP server understands how data is organized in the database and has special functions for analyzing the data. There are OLAP servers available for nearly all the major database systems.

Types of OLAP Servers

• Relational OLAP (ROLAP)- ROLAP  servers are placed between relational back-end server and client front-end tools.
• Multidimensional OLAP (MOLAP)-MOLAP uses array-based multidimensional storage engines for multidimensional views of data.
• Hybrid OLAP (HOLAP)-HOLAP is a combination of both ROLAP and MOLAP. It offers higher scalability of ROLAP and faster computation of MOLAP.
• Specialized SQL Servers- Specialized SQL servers provide advanced query language and query processing support for SQL queries over star and snowflake schemas in a read-only environment.

What You Need To Know About OLAP

• Online Analytical processing, is a class of software tools which provide analysis of data for business decisions. OLAP systems allow users to analyze database information from multiple database systems at one time.
• OLAP is characterized by low volume of transactions.
• OLAP provides a multi-dimensional view of various kinds of business activities.
• Consists of historical data from various databases. In this regard, OLAP is used in planning, problem-solving, managing information and decision support.
• The response time of OLAP system is large and often varies from seconds to minutes or even hours. This because the amount of data involved is large.
• The sources of data in OLAP systems comprise of different OLTP databases.
• OLAP systems are designed for the analysis of business measures in terms of category and attributes.
• OLAP requires more space requirements due to the existence of aggregation structures and history data, requiring more indexes.
• The design of OLAP is typically de-normalized with fewer tables and uses star, snowflake or constellation.
• OLAP’s main operation is to extract multidimensional data for analysis. Therefore, SELECT command is often used.
• In OLAP systems, data integrity does not serve to be an issue because the database is not modified frequently.
• In OLAP refreshing of data with huge data sets take time and is sporadic.
• OLAP are generally used by the managers, executives, data scientist, marketers or business owners.
• Allows only read and rarely write.
• OLAP only requires backup from time to time. Backup is not important compared to OLTP.
• Query throughput is the performance metric.
• OLAP allows only hundreds of users.
• OLAP uses the data warehouse.
• OLAP database is customer oriented.
• OLAP helps to increase productivity of the business analysts.

Also Read: Difference Between Decision Tree And Decision Table

Difference Between OLTP  And OLAP Databases In Tabular Form

Advantages of OLTP

• It provides fast query processing, maintaining data integrity in multi-access environments.
• It provides a flexible platform for many applications like from ATM networks to computerize shop floor automation.
• It handles large data, user volumes, more complex calculations and higher peak loads.
• It simplifies processes in an organization.
• Processes information according to defined business rules.
• Helps to reduce paper work in an organization.
• Provides accurate forecasts for revenues and expenses in an organization.

Disadvantages Of  OLTP

• It makes it convenient to produce analytical measures including financial models, financial forecasts, regressions, allocations and time-series calculations.
• It helps managers to make informed decisions.
• It has the ability to create very fast aggregations and calculations of data sets.
• It has ability to achieve fast access to shared multidimensional information.
• Large data warehouse are not necessary for OLAP.
• OLAP is the best platform for all manner of business including designing, budgeting, reporting and analysis.
• It enables the organization to respond more quickly to market demands.
• It controls the access to strategic information for more effective decision making.
• It provides quicker response time.
• There is consistency of information and calculations.
• It increases the productivity of business managers, developers and the entire organization.

Advantages Of OLAP

• OLAP requires organizing information into star or snowflake schema. These schemas are sophisticated to implement and administer.
• OLAP toots have a complicated modeling procedure.

Disadvantages Of OLTP

• Unprecedented situation can arise because OLTP systems allow multiple users to have access and change the same data at the same time.
• Like many modern online information technology solutions, some systems require offline maintenance which further affects the cost-benefit analysis.
• In the event of hardware failures of the online transaction processing systems, users of the website get affected and their transactions too get affected.
• At times, there occur millions and millions of requests at a time which gets difficult to handle.