OLTP Vs OLAP: Full Comparison
OLTP vs OLAP is among the various endless comparisons drawn in the tech (IT) space every now and then. Although both are online processing systems, each of them caters to a different set of requirements. Let’s kick in the basics.
In a batch processing system, transaction details are stacked in a set of documents that are registered in groups (called batches and hence, the name).
An online processing system is different (and efficient) from a batch processing system. Here, instead of piling up the transaction details, the same are registered in real-time. Thus, it provides an edge over the traditional batch processing systems.
Both OLTP and OLAP systems are online transaction systems. The single biggest difference, however, between OLAP and OLTP lies in their very nature of processing.
While OLTP is a transaction processing system, OLAP is an analytical processing system. For example, a data warehouse gets data via OLTP systems but to process (specifically, analyze) that data it leverages an OLAP system.
A transaction processing system manages transaction-based applications over the web. An analytical processing system, on the other hand, responds to (multidimensional) analytical queries (with respect to order entry, financial reporting, etc.) over the internet.
Another important distinction that separates OLTP and OLAP is that while the first one is an online database query answering system, the other one is an online database modifying system.
Before we head on to compare the two popular online processing systems i.e. OLAP and OLTP in detail, let’s get our head wrapped around the definitions, features, and more regarding the two online processing systems.
What is OLTP?
OLTP corresponds to OnLine Transaction Processing. OLTP systems serve as the data source for OLAP systems. These online processing systems provide support for transaction-based applications in a 3-tier architecture.
Data processing is the main aim of an OLTP system. To measure the effectiveness of an OLTP system, we consider the total transactions that it can perform in a second. It acknowledges Update, Deletion, and Insertion requests to modify a certain database.
As OLTP systems allow multiple users to access and modify the same data, transaction failures are common. Failed transactions, however, can result in causing severe data integrity issues to OLTP systems. Therefore, these online processing systems need to prioritize and maintain data integrity.
Features of OLTP
Data Integrity and Multi-access
OLTP systems ensure high data integrity in multi-access environments. As online transaction processing systems allow multiple users to access and modify the same data, issues caused by the same are frequent.
Normalization
OLTP databases store detailed and current data using the entity-relationship (ER) model. Also, normalization is performed on these using 3NF normalization.
Processing Time and Storage Space
Usually, OLTP queries are simple and small. As such, they demand less processing time and storage space.
Examples
An ATM and online banking are the two best examples of online transaction processing (OLTP) systems.
Use-cases
OLTP systems are ideal for administering day-to-day transactions. As these simplify individual processes, OLTP systems let organizations increase and accommodate their consumer bases.
What is OLAP?
OLAP expands to OnLine Analytical Processing. An OLAP system lets users extract information from a database as well as analyze it for making well-informed decisions. It also provides support for simple and complex queries.
The main objective of an online analytical processing system is data analysis. To measure the effectiveness of an OLAP system, we gauge its response time.
Unlike OLTP systems, data integrity isn’t a major concern for OLAP systems. Hence, transaction failure is not that much troublesome here. In such a scenario, the user simply reruns (refreshes) the transaction to get the required details.
All the data that has been entered using an OLTP system is stored in an OLAP database. An OLAP system lets users view various summaries of the stored multidimensional data in an OLAP database.
Features of OLAP
Transaction Complexity and Frequency
OLAP transactions are long and complex. As such, these demand more processing time and storage space. Nonetheless, these transactions, compared to OLTP transactions, are few and far between.
Normalization
Unlike OLTP databases, OLAP databases are not usually normalized and feature aggregated and historical data stored in multidimensional schemas that is usually a star and/or snowflake schema.
Examples
A personalized homepage on an online marketplace, like Amazon and eBay, and data warehouse management system are the two perfect examples of online analytical processing transactions. These are used, for example, for fetching budgeting information and viewing sales reports.
Dependence
The proper operation of an online analytical processing system depends greatly on the IT professional or team in charge of the implementation and maintenance of the same.
Moreover, the effectiveness of OLAP systems relies heavily on the cooperation of personnel of different departments.
Consistency and Security
OLAP systems feature a high level of consistency of calculations and information. In order to protect sensitive data and information, and also to let users comply with regulations, online analytical processing systems allow imposing security restrictions easily.
All-in-one Business Analytics
An OLAP system offers a unified platform to meet most types of business analytical requirements.
Which is Better?
The question of which is better among OLAP and OLTP systems is a bit tricky. That’s because each of these online processing systems serves different causes. While OLTP systems leverage traditional DBMSs, OLAP systems use data warehouses.
While the OLTP system lets users store data in databases, the OLAP system is one that helps to process the same data and answer back user queries and make informed business decisions. Therefore, we can say that both complement one another.
OLTP vs OLAP
| Parameter | OLTP | OLAP |
|---|---|---|
| Query Complexity | Simple queries. Returns only a few records. | Supports simple as well as complex queries that involve aggregations. Returns a great number of records. |
| Main Objective | Data processing | Data analysis |
| Effectiveness is Measured Using | The number of transactions carried out in a second. | Response time |
| Major Concern | Data integrity | Response time |
| Impact of Hardware Failures | High | Medium |
| Database Normalization | 3NF normalization | Usually not required |
| Backup and Recovery | A strict backup plan is required with additional backup options to safeguard business-critical data. | Infrequent. Might choose reloading data as the primary recovery method over a strict backup regime. |
| Form of Data Displayed (Fed) | Screenshot | Multidimensional views |
| Data Stored | Operational data | Consolidation data |
| Database Tables | More | Fewer |
| Response Time is Measured in | Milliseconds | Seconds or minutes |
| System Type | Online transaction system | Online data-retrieval |
Conclusion
Choosing one between OLAP and OLTP systems depends on the user requirements. This is because each of these popular online processing systems fulfills a different set of needs.
For daily task management, online transaction processing systems are the go-to option but for storing historical data that can be processed later for facilitating decision-making and problem-solving, online analytical processing systems are the best bet.
