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每年都有新的框架、新的“无代码”工具或新的数据平台，声称要取代SQL。然而，SQL仍然是处理数据时最通用、最可靠和被广泛采用的接口。它依然占据主导地位的几个原因：它是声明式的。你只需描述你想要的结果，而不是如何计算它。它是稳定的。经过数十年的优化，经过各行业的考验。它是可移植的。从Postgres到BigQuery，再到Snowflake和DuckDB，SQL无处不在。它是经过优化的。现代引擎能够在最小调优的情况下处理巨大的工作负载。它是每个分析师、工程师和机器学习人员都能达成共识的语言。即使是现代的“数据工程”工具——如dbt、Spark SQL、Trino和BigQuery ML——也只是将SQL带入新的环境，而不是取代它。生态系统不断变化，但SQL的简单性和持久性使其成为我们所拥有的最接近通用数据语言的东西。我很好奇其他人的看法：SQL的主导地位是成熟的标志，还是有更好的东西即将出现？

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Every year there’s a new framework, a new “no-code” tool, or a new data platform that promises to replace SQL. And yet—SQL remains the most universal, reliable, and widely adopted interface for working with data.A few reasons it still wins:It’s declarative. You describe what you want, not how to compute it.It’s stable. Decades of optimizations, battle-tested across industries.It’s portable. From Postgres to BigQuery to Snowflake to DuckDB, SQL is everywhere.It’s optimized. Modern engines can handle insane workloads with minimal tuning.It’s the one language every analyst, engineer, and ML person can agree on.Even modern “data engineering” tools—dbt, Spark SQL, Trino, BigQuery ML—are simply bringing SQL to new environments, not replacing it.The ecosystem keeps changing, but SQL’s simplicity and longevity make it the closest thing we have to a universal data language.Curious to hear how others feel: Is SQL’s dominance a sign of maturity, or is something genuinely better on the horizon?

SQL 依然占据主导地位：为什么它不会消失