What features could ClickHouse add to its SQL dialect to make complex analytical queries easier to write?

Introduction

To improve ClickHouse's SQL dialect for complex analytical queries, we need to focus on enhancing its functionality while maintaining its renowned performance. I'll analyze the current state, identify key user segments and pain points, propose solutions, and outline a strategy for implementation and measurement.

Step 1

Clarifying Questions (5 mins)

• Looking at ClickHouse's position as a high-performance analytical database, I'm thinking about the primary use cases. Could you elaborate on the most common types of complex analytical queries our users are running?

Why it matters: Determines the specific areas of the SQL dialect we should focus on improving. Expected answer: Time-series analysis, multi-dimensional aggregations, and complex joins. Impact on approach: Would prioritize features that streamline these specific query types.

• Considering ClickHouse's rapid growth, I'm curious about our user base evolution. How has our user demographic shifted in the past year, particularly in terms of technical expertise?

Why it matters: Helps tailor improvements to match user skill levels and expectations. Expected answer: Increasing adoption by data analysts with SQL but limited database expertise. Impact on approach: Would focus on simplifying complex operations without sacrificing power.

• Given the competitive landscape in the analytical database market, I'm interested in our differentiation strategy. What are the key features that currently set ClickHouse apart from competitors like BigQuery or Snowflake?

Why it matters: Ensures new features align with and enhance our unique value proposition. Expected answer: Superior performance for large-scale data processing and real-time analytics. Impact on approach: Would prioritize features that maintain or improve query performance.

• Considering the broader company objectives, I'm wondering about the strategic goals for ClickHouse. Are we aiming to expand our user base, increase engagement from existing users, or both?

Why it matters: Aligns product improvements with overall business strategy. Expected answer: Focus on increasing engagement and expanding use cases for existing users. Impact on approach: Would emphasize features that enable more complex analyses and increase stickiness.