The world is filled with data, of all kinds and businesses are totally dependent on the multitude of data for their prospects. Processing and analysis of data is a huge task that can be undertaken effectively through online data processing systems like Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP).
OLTP and OLAP are two business information processing systems, which sound similar but come with different purposes and ways of data processing. OLTP focuses on online database modifying systems while OLAP focuses on online database query answering systems. The database structure is totally different and the kind of optimization they call for needs different architectural setup and processing strategies.
Both are trivial to database management and both have their own set of characteristics, making them important for businesses. Before we compare the two, let us understand the basic terminologies.
What Is OLTP?
“The management of transactional data using computer systems is referred to as online transaction processing (OLTP). OLTP systems record business interactions as they occur in the day-to-day operation of the organization, and support querying of this data to make inferences.”
An OLTP system emphasizes on faster processing of transaction data from different databases. It is mainly concerned with capturing and maintaining data that consists of individual database records with multiple fields/columns. Based on a three-tier architecture, OLTP databases are read, written, and updated on a regular, day-to-day basis.
It consists of many online transactions that are short, needs fast processing with proper data integrity and transactional superiority. Its efficacy is measured by the number of transactions processed per second.
OLTP System Examples
- ATM centers
- Online banking
- Sending text message
- Online air-ticket booking
- Addition of book to the shopping cart
Key Features Of OLTP
- Administration of daily transactional data of an organization
- Simplification of independent processes
- Expands client base of an organization
- Faster processing of data with thorough data integrity
- Ability to handle multiple databases effectively
Known OLTP Systems
- Oracle database
- Microsoft SQL
- IBM DB2
What Is OLAP?
“Online analytical processing (OLAP) is a technology that organizes large business databases and supports complex analysis. It can be used to perform complex analytical queries without negatively affecting transactional systems.”
An OLAP system focuses on the application of complex queries to a huge amount of data collected from OLTP databases and other sources, for the application of data mining, analytics, and business intelligence. What is important here is the response time to these queries. These databases offer analysts and decision-making stakeholders, an in-depth view of the wide range of data through different data reporting tools.
OLAP can turn simple data into effective, valuable information. In case of a query failure, there is no delay in processing transactions, but it does impact the availability of insightful information. It facilitates the analysis of database information from multiple systems, simultaneously. Data here is stored as multi-dimensional schemas.
Its basic architecture consists of an OLAP server and OLAP client – both of which perform their individual functions to offer effective results. The different types of OLAP servers are Relational OLAP (ROLAP), Multidimensional OLAP (MOLAP), Hybrid OLAP (HOLAP), and specialized SQL servers.
OLAP System Examples
- Data warehouse system
- Personalized customer preferences
- Sales comparison – month-wise, location wise
- User wise analysis of different parameters based on data inputs
- Recommendation to users based on history and likings
Key Features Of OLAP
- Creation of a single platform for all types of analytical needs
- Planning, forecasting, and analysis of varied information, at one go
- Consistent and calculated information availability
- Security, privacy, and protection of sensitive information
Known OLAP Systems
- Pentaho BI
- Amazon Redshift
- IBM Cognos
- Apache Kylin
OLTP vs OLAP Comparison:
Here is a vivid comparison between OLAP and OLTP, based on certain prime characteristics:
|Primary Objective||Data processing, executing fundamental business operations in real-time||Data Analysis, planning and solving problems, discovering insights|
|Transactions||Short and frequent transaction processing||Long and less frequent transaction processing|
|Functionality||Day to day operations, repetitive usage, fast response time, low data redundancy||Decision support, ad-hoc usage, a data warehouse for database integration|
|Main Operations||Read and Write based on Insert, Update, Delete commands||Mostly Reads with Select command to extract multidimensional data for analysis|
|Size of Database||Gigabytes, lesser space requirements if data is archived||Terabytes, larger space need owing to aggregating datasets|
|Response Time||The response time is in milliseconds||The response time is in seconds to minutes|
|Data Access||Access to an immediate record of business data – current, flat relational, isolated, detailed||Compiled over time with insightful information – Historical, aggregated, multi-dimensional|
|Database Design||Application driven, traditional, normalized DBMS||Subject driven, Data warehouse with integrated, denormalized data sources|
|Unit of Transaction||A large number of Simple, short transactions||Complicated queries and large data volume|
|System Design||Market-oriented, industry-based like retail, finance, etc.||Client-oriented, subject-based like sales, inventory, etc.|
|Backup System||Needs regular backup mechanism for an undisturbed business flow||Needs backup but lost data can be recovered from the OLTP database|
|Queries||Standard and simple queries||Complicated and aggregated queries|
|Type of Users||Users like DBA, clerks, Database people who need critical information||Users like data scientists, managers, CEO, top management who need detailed insight into data|
|Number of Users||Facilitates thousands of users||Facilitates hundreds of users|
How Are OLTP And OLAP Related/Integrated?
Garnering insightful information directly from data accumulated in OLTP databases can be cumbersome and complex. For getting a variety of BI-related information like forecasts and trends, data must be available in certain standardized, usable forms so that OLAP systems can make the most of it.
The key that connects and integrates the two processes is the ETL process. ETL stands for Extract, Transform and Load. Raw data, collected from OLTP systems, is extracted from various sources, cleansed, and converted into a common format. This data is then used by analytical tools to garner intelligent information through OLAP systems.
Using OLTP and OLAP systems on the same server is also possible but there are certain challenges that could pose an issue. Direct access to the OLTP database by the OLAP database could get the system to perform slowly since OLAP queries are quite complex. OLTP does not have data in a denormalized form. Hence, direct dealing with OLAP may consume a great deal of time.
Frequently Asked Questions (FAQ)
What does OLTP mean?
OLTP stands for Online Transaction Processing. It is a set of information systems that are competent to support and manage transaction-based applications.
What is an Online Analytical Processing Program?
An Online Analytical Processing program (OLAP) facilitates users to analyze huge bulk of information, from various databases, and get in-depth information out of them.
How do Online analytical processing systems improve performance?
Online analytical processing systems undergo pre-aggregation of data so that only the required data sets are available for the queries to be solved. This helps in faster retrieval of data and enhanced performance.
Is SQL Server OLAP or OLTP?
Since the SQL Server database is created in a normal SQL Server instance, it is an OLTP database.
What is OLAP Cube?
OLAP cube is a multi-dimensional array of data that helps in the easy creation and viewing of reports. It also facilitates fast data analysis based on multiple dimensions.
Where is OLTP used?
OLTP systems are most often used for businesses that have online transactional requirements like financial transactional systems, CRM systems, retail sales systems, order-based entry systems, etc.
What Is Hybrid Online Analytical Processing (HOLAP)
Hybrid OLAP (HOLAP) is a grouping of Relational OLAP (ROLAP) and Multidimensional OLAP (MOLAP). It permits partial storage of data in the MOLAP store and the other part in the ROLAP store.
On A Parting Note:
OLTP and OLAP are both different ways of processing information. Users can choose which one to use, based on the organizational requirements. There are feasible chances of using both, linking each other by ETL process, for implementing ideal business intelligence services and solutions.
Modern-day data warehousing tools are competent to garner the best analytical information out of the heap of data structures. Data processing competencies like OLTP and OLAP are here to help organizations create a successful future, based on the in-depth information that they carve out, from the transactional help of data, that they gather.