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Advanced Topic 47 of 51 Databases

OLTP vs OLAP

Transaction-heavy versus analysis-heavy workloads.

How it works

OLTP, online transaction processing, handles many short transactions that read and write a few rows, such as placing an order, with high concurrency, normalized schemas, row-oriented storage and strict ACID guarantees. OLAP, online analytical processing, runs complex queries that scan and aggregate large volumes of historical data, often over denormalized or star schemas with column-oriented storage and relaxed update patterns. The two have opposite workloads and optimizations.

Step-by-step walkthrough

  1. OLTP handles many small transactions, such as orders.
  2. It favors row storage and indexes.
  3. OLAP handles few large analytical queries.
  4. It favors column storage and compression.
  5. Warehouses are tuned for OLAP, production databases for OLTP.

Where it is used

Operational applications run on OLTP databases such as PostgreSQL and MySQL, while analytics runs on OLAP systems such as warehouses, ClickHouse and Druid, fed by data pipelines.

Common pitfall

Running heavy analytics on the OLTP database slows the application and risks locking. Duplicating data adds lag, so analytics may be slightly stale. Hybrid HTAP systems try to serve both, with trade-offs. Separate workloads, use replicas or change data capture, and choose storage layout to match the access pattern.

Where it fits in the course

OLTP vs OLAP is topic 47 of 51 in Databases, rated Advanced. It follows Data Warehousing. The next topic is LSM Trees.

Practice and explore

How to study this topic

  1. Read the explanation above and restate the definition in your own words.
  2. Open the interactive lesson and answer its mini quiz.
  3. Read the common pitfall, then write a short example that avoids it.
  4. Check your understanding in the Databases quiz, and revisit the topic if you miss a question.

Frequently asked questions

What is OLTP vs OLAP?
Transaction-heavy versus analysis-heavy workloads. It belongs to Databases and is an advanced-level topic.
Where do people use OLTP vs OLAP?
Operational applications run on OLTP databases such as PostgreSQL and MySQL, while analytics runs on OLAP systems such as warehouses, ClickHouse and Druid, fed by data pipelines.
What is the most common mistake with OLTP vs OLAP?
Running heavy analytics on the OLTP database slows the application and risks locking.
What should I learn before this topic?
Start with Data Warehousing, the topic just before it in Databases.
How can I practice it?
Answer the mini quiz in the interactive lesson, then take the Databases quiz.
Is OLTP vs OLAP hard to learn?
It is an Advanced topic. Expect to read the explanation more than once and to connect it with earlier topics. Working through a small example by hand helps most.
How long does it take to learn OLTP vs OLAP?
Most learners can read the explanation and finish the interactive lesson in under an hour. Fluency comes from applying the idea, so plan a few short practice sessions with the quiz.
Which topics are related to OLTP vs OLAP?
Data Warehousing, LSM Trees, Eventual Consistency are closely connected. The full list is in the related topics section of this page.
What should I study after OLTP vs OLAP?
Continue with LSM Trees, the next topic in Databases.

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