While developing an open-source analytics framework Cube.js, we've encountered various data warehouses with different requirements and needs. When choosing a modern data warehouse, it's essential to consider factors such as the volume of data, dedicated human resources for support and maintenance, scalability, pricing models, and on-premises vs cloud infrastructure. The ideal solution depends on the dataset size, available resources, and specific requirements, with non-relational databases suitable for large datasets, relational databases offering great query optimizers for smaller datasets, and self-hosted options like Hadoop requiring significant setup and maintenance expertise. Pricing models vary across solutions, with Redshift, BigQuery, and Snowflake offering on-demand pricing, while Amazon S3-based solutions provide scalable and flexible pricing options. Ultimately, the choice of data warehouse depends on balancing data volume, scalability, and cost considerations to meet specific business needs.