Data Replication: Examples, Techniques & How to Solve Challenges

Data replication is the process of copying data from one storage source to another for various purposes such as operations, analytics, or data science. It can be done in batches or real-time and involves processes like data synchronization, ingestion, and integration. Common examples include database to database, database to data warehouse, and application to data warehouse replication. Data replication techniques include full replication, incremental replication, and log-based incremental replication. Challenges faced by data engineers in implementing data replication solutions can be addressed using a data replication tool like Airbyte, which provides connectors, supports low latency, is scalable, handles schema changes, normalizes and transforms data, and offers monitoring and observability features.