SQL is making a comeback after years of being left for dead due to the rise of NoSQL databases. The major cloud providers now offer popular managed relational database services, and SQL interfaces on top of Hadoop, Spark, and Kafka continue to thrive. This resurgence can be attributed to the limitations of NoSQL languages, which led to issues such as increased complexity, denormalization, and lack of JOINs. In response, new scalable databases that fully embrace SQL have emerged, such as Google's Spanner database. The adoption of SQL is not limited to these systems but has also become a common interface across multiple systems within Google. As data continues to grow exponentially, the need for a universal interface that can connect various layers of the data stack is becoming increasingly important. SQL has become this universal interface, allowing pieces of the stack to communicate with one another and enabling users to transfer their understanding of the language between different systems. This shift towards SQL is seen as a positive development, restoring balance to the force and providing a standardized interface for data analysis.