Data warehouse databases are more suitable for Online Analytical Processing (OLAP) applications. Data warehouses provide fast aggregation capabilities over vast volumes of structured data. While these technologies, such as Amazon Redshift, Netezza, and Teradata, are designed to execute complex aggregate queries quickly, they are not optimized for high volumes of concurrent writes. So, data needs to be loaded in batches, preventing warehouses from being able to serve real-time insights over hot data.
Modern data warehouses use a columnar base to enhance query performance. Examples of this include Amazon Redshift, Snowflake, and Google Big Query. These data warehouses provide very fast query performance due to columnar storage and improve I/O efficiency. In addition to that, data warehouse systems such as Amazon Redshift increase query performance by parallelizing queries across multiple nodes and take advantage of massive parallel processing (MPP).
Data warehouses are...
