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Databases Intermediate

What is ETL (Extract, Transform, Load)?

A data pipeline process that extracts data from sources, transforms it into a suitable format, and loads it into a destination system.

ETL processes move data between systems. Extract pulls data from databases, APIs, files, or streams. Transform cleans, validates, enriches, and restructures the data. Load writes the processed data to a data warehouse or target system.

Modern variations include ELT (load raw data first, transform in the warehouse) and real-time streaming. Tools include Apache Airflow, dbt (transform layer), Apache Spark, and cloud services like AWS Glue. ETL is fundamental to data warehousing and analytics.

Related Terms

Database Proxy
A middleware server that sits between applications and databases, providing connection pooling, load balancing, and query routing.
Partitioning
A technique of dividing large database tables into smaller, more manageable segments while maintaining a single logical table.
SQL
Structured Query Language โ€” the standard language for managing and querying data in relational databases.
Redis
An open-source, in-memory data store used as a database, cache, message broker, and queue with sub-millisecond response times.
JSONB
PostgreSQL's binary JSON data type that stores JSON documents with indexing, querying, and manipulation capabilities.
Cursor
A database object that enables row-by-row processing of query results, useful for operations that cannot be done in bulk.
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