Snowflake’s columnar storage architecture delivers faster analytics and lower costs by scanning only relevant data, compressing storage intelligently, and optimising queries automatically. This design enables significant performance gains and cost reductions across ETL, storage, and compute—transforming how businesses scale data operations and consume insights.
This blog explores how data teams can strategically reduce costs without compromising performance, drawing insights from a recent LinkedIn Live featuring experts from Select.dev, Cube, and Matatika. It outlines five key strategies, from optimising human productivity to safely switching platforms, backed by real-world examples and practical implementation steps.
SaaS ETL Tools pricing is broken. Too many businesses are stuck with platforms that charge by rows, gigabytes, or arbitrary metrics, pushing costs higher without delivering real value. It’s a model that inflates SaaS data costs, forcing companies to pay more for data that doesn’t always lead to better insights.
Managing large amounts of data can quickly become expensive, especially for companies using platforms like Google Analytics 4 (GA4) in Snowflake. Many ETL platforms charge based on the volume of data processed, leading to high costs without added business value. At Matatika, we offer a solution that helps you save up to 99.4% on GA4 costs while maintaining high performance. Here’s how our cost-based pricing model works, and why it's more effective than traditional ETL platforms.