Best Columnar Databases for Azure Data Factory

BigQuery is a columnar database that stores data in columns rather than rows, a structure that significantly speeds up analytic queries. This optimized format helps reduce the amount of data scanned, which enhances query performance, especially for large datasets. Columnar storage is particularly useful when running complex analytical queries, as it allows for more efficient processing of specific data columns. New customers can explore BigQuery’s columnar database capabilities with $300 in free credits, testing how the structure can improve their data processing and analytics performance. The columnar format also provides better data compression, further improving storage efficiency and query speed.

More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.