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    • Snowflake vs Databricks Pricing: Who’s Really Playing Fair?

      Snowflake and Databricks take fundamentally different pricing approaches—Snowflake offers managed optimisation with less control, while Databricks provides flexibility with greater complexity. The real shift in value lies in adopting warehouse-agnostic, performance-based ETL pricing that aligns cost with actual infrastructure use, offering transparency and freedom from vendor lock-in.

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    • Understanding Today’s ETL Pricing Landscape: Column vs Row Approaches

      Most ETL pricing models haven’t kept pace with the evolving data landscape, leaving many teams overpaying for row-based processing that penalises growth and efficiency. This blog advocates for a shift toward performance-based pricing aligned with column-oriented processing, offering scalable, transparent cost control that reflects actual infrastructure usage rather than arbitrary metrics.

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    • Snowflake Columnar Storage: Why This Architecture Could Cut Your Analytics Costs by 70%

      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.

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    • How Smart Data Teams Cut Costs Without Sacrificing Performance

      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.

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    • From Tool Mastery to Systems Design: How Data Engineers Actually Grow

      Many data engineers plateau after mastering tools but struggle to scale because they haven't learned to think in systems. This blog explores how transitioning from query writing to system design is the key to sustainable growth, effective mentorship, and resilient analytics platforms.

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