OLTP & OLAP
Two major words in the field of data management and processing are online transaction processing (OLTP) and online analytical processing (OLAP), each of which has a particular function. OLAP systems are focused towards complicated data analysis and reporting on vast volumes of historical data, whereas OLTP systems are often designed for processing daily transactions with a focus on data integrity and concurrency. These are some of the key variations between them
- Purpose
For the analysis and reporting of complex data, OLAP systems are created. They are used to glean insights from enormous amounts of aggregated and historical data. For business intelligence and decision-making, OLAP systems support operations including data slicing, dicing, drilling down, and rolling up.
Customer data, order processing, and inventory management are examples of common business tasks that are handled by OLTP, which is designed for daily operational transactional processes. The main objective is to guarantee data accuracy, consistency, and concurrency.
- Query Type
OLAP queries read a lot of data and concentrate on producing reports and insights. These queries run intricate analytical queries on massive datasets that include grouping, filtering, and calculation.
Low latency data access is given priority by OLTP queries. They typically handle straightforward single-transaction read/write operations on a single record or a small number of records.
- Data Structure
Denormalized or star/snowflake schemas are frequently used in OLAP databases to arrange data for quick querying and reporting. This layout makes complex aggregations and searches simpler.
The normalized data structure used in OLTP databases means that data is arranged to reduce duplication and guarantee data integrity. This layout works well for regular data additions and updates.
- Data Volume
Big data is typically involved in OLAP. Usually, the more sources there are, the more complicated the dataset is.
On the other hand, OLTP works with a smaller volume of data than OLAP.
- Concurrency
OLAP systems are less concerned with high concurrency because they are frequently used for batch processing or reporting. Queries can use a lot of resources and are typically run at off-peak times.
Concurrent data access is prioritized in OLTP systems. Data can be read and written simultaneously by multiple users without causing issues.
- Performance
OLAP systems place a high priority on report production and query performance. The query response time serves as a gauge of performance.
Low-latency transaction processing is the focus of OLTP systems. The number of transactions executed per second is a key performance indicator.
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