Usage scenarios Port workloads from HiveServer2 to Spark SQL End-users: Focus on business data of their own, not where it stores, how it computes.Īdditionally, the Kyuubi community will continuously optimize the whole system with various features, such as History-Based Optimizer, Auto-tuning, Materialized View, SQL Dialects, Functions, e.t.c.System administrators: A small group consists of Spark experts responsible for Kyuubi deployment, configuration, and tuning.In typical big data production environments with Kyuubi, there should be system administrators and end-users. Sometimes, SQL skills are unnecessary when integrating Kyuubi with Apache Superset, which supports rich visualizations and dashboards. Here, anyone means that users do not need to have a Spark technical background but a human language, SQL only. Kyuubi's goal is to make it easy and efficient for anyone to use Spark(maybe other engines soon) and facilitate users to handle big data like ordinary data. At the server-side, Kyuubi server and engines' multi-tenant architecture provides the administrators a way to achieve computing resource isolation, data security, high availability, high client concurrency, etc. This 'out-of-the-box' model minimizes the barriers and costs for end-users to use Spark at the client side. Kyuubi provides a pure SQL gateway through Thrift JDBC/ODBC interface for end-users to manipulate large-scale data with pre-programmed and extensible Spark SQL engines. We are aiming to make Kyuubi an 'out-of-the-box' tool for data warehouses and data lakes. It has been open-sourced by NetEase since 2018.

Kyuubi is a distributed multi-tenant Thrift JDBC/ODBC server for large-scale data management, processing, and analytics, built on top of Apache Spark and designed to support more engines (i.e., Flink).

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