and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

apache.org/docs/current/hadoop-yarn/hadoop-yarn- site/FairScheduler.html#Queue_Access_Control_Lists], from cluster managers, e.g. Apache Hadoop YARN [https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN [https://kubernetes.io/] to create the Spark application; 2) a user account can only access data and metadata from a storage system, e.g. Apache Hadoop HDFS [https://hadoop.apache.org/docs/current/hadoop-project Kyuubi on any cluster manager, including YARN, Kubernetes, Mesos, e.t.c… Or, you can manipulate data from different data sources with the Spark Datasource/Flink Table API, e.g. Delta Lake, Apache Hudi, Apache

apache.org/docs/current/hadoop-yarn/hadoop-yarn- site/FairScheduler.html#Queue_Access_Control_Lists], from cluster managers, e.g. Apache Hadoop YARN [https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN [https://kubernetes.io/] to create the Spark application; 2) a user account can only access data and metadata from a storage system, e.g. Apache Hadoop HDFS [https://hadoop.apache.org/docs/current/hadoop-project Kyuubi on any cluster manager, including YARN, Kubernetes, Mesos, e.t.c… Or, you can manipulate data from different data sources with the Spark Datasource/Flink Table API, e.g. Delta Lake, Apache Hudi, Apache

StarRocks [https://www.starrocks.io/], etc., to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using

and Trino [https://trino.io/], etc, to query massive datasets distributed over fleets of machines from heterogeneous data sources. The Kyuubi Server lane of the below swimlane divides our prospective of computing and storage from the end users. Thus, they can focus on their business and data with familiar tools. On the other hand, it hides the complexity of business logic from the administrators. Therefore Serverless SQL and More Serverless SQL on Lakehouses makes it easier for end users to gain insight from the data universe and optimize data pipelines. It enables: The same user experience as an RDBMS using