Cloud

OLTP vs OLAP

Redpanda SQL uses an OLAP (online analytical processing) model, optimized for analytical queries over large datasets, rather than the OLTP (online transaction processing) model used by traditional relational databases. This makes OLAP suitable for querying Redpanda topics at scale.

After reading this page, you will be able to:

  • Distinguish OLTP from OLAP processing patterns

  • Explain why Redpanda SQL uses an OLAP model

Online transaction processing (OLTP)

OLTP supports transaction-oriented applications under a three-tier architecture (such as a 3NF approach). OLTP administers day-to-day transactions through a relational database.

Some daily use cases for transactional processing include:

  • Payment: Using a debit or credit card, online or offline payment

  • Online transaction: Any reservation, ticketing, and booking system that requires transactional processing

  • ATM and online banking: Cash withdrawals or online banking operations

  • Record entry: Storing data like student score records, warehouse inventory, or customer service ticketing systems

Online analytical processing (OLAP)

OLAP provides data analysis for business decisions. With OLAP, you can query information across multiple databases and data types simultaneously, including complex queries.

Some examples of OLAP in business analytics include:

  • Personalization: personalized homepages, e-commerce recommendations, and content platforms

  • Sales analytics: comparing sales across different time periods stored in separate databases

  • Customer behavior: determining customer behavior across industries

  • Trend analysis: statistical analysis across sectors to assist in decision-making

OLTP and OLAP comparison

The following table outlines the main differences between OLTP and OLAP:

Parameter OLTP OLAP

Process

A transactional mechanism for controlling database modifications

Online analysis and data retrieving process

Characteristic

Large numbers of online transactions

Large volume of data

Method

Traditional DBMS

Data warehouse

Database normalization

Normalized

Unnormalized or denormalized

Operation

INSERT, DELETE, and UPDATE commands

Mostly SELECT operations

Response time

Milliseconds

Seconds to minutes, depending on the data amount processed

Storage size

Small database

Large database

Response

Quick results for frequently accessed data

Consistently fast response to requests

Audience

Application end users

Business analysts and decision-makers

Key differences

  • OLAP analyzes data stored in a database, while OLTP supports transaction-oriented operations.

  • OLAP handles all business and data analysis, while OLTP is typically used for daily transactions.

  • OLAP can integrate different data sources, while OLTP uses traditional DBMS.