Best Query Engines for StarRocks

Apache Hive™, a data warehouse software, facilitates the reading, writing and management of large datasets that are stored in distributed storage using SQL. Structure can be projected onto existing data. Hive provides a command line tool and a JDBC driver to allow users to connect to it. Apache Hive is an Apache Software Foundation open-source project. It was previously a subproject to Apache® Hadoop®, but it has now become a top-level project. We encourage you to read about the project and share your knowledge. To execute traditional SQL queries, you must use the MapReduce Java API. Hive provides the SQL abstraction needed to integrate SQL-like query (HiveQL), into the underlying Java. This is in addition to the Java API that implements queries.

Trino is an engine that runs at incredible speeds. Fast-distributed SQL engine for big data analytics. Helps you explore the data universe. Trino is an extremely parallel and distributed query-engine, which is built from scratch for efficient, low latency analytics. Trino is used by the largest organizations to query data lakes with exabytes of data and massive data warehouses. Supports a wide range of use cases including interactive ad-hoc analysis, large batch queries that take hours to complete, and high volume apps that execute sub-second queries. Trino is a ANSI SQL query engine that works with BI Tools such as R Tableau Power BI Superset and many others. You can natively search data in Hadoop S3, Cassandra MySQL and many other systems without having to use complex, slow and error-prone copying processes. Access data from multiple systems in a single query.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.