Hue is an open-source, Apache-2.0 licensed SQL Assistant service for databases and data warehouses, built for data analysts, data engineers, and platform teams that need a shared, browser-based way to query and explore data instead of installing a separate client for every engine.

What it is

Hue is a mature SQL Assistant for querying databases and data warehouses. It is written in JavaScript, published under the Apache-2.0 licence from the cloudera GitHub organization, and carries the tagline "Query. Explore. Share." Beyond a query editor, it ships a set of browsers: a File Browser, a Job Browser, a Table Browser, and a Table Importer. It lives firmly in the Hadoop and data-warehouse ecosystem, with documented connectors for Apache Hive, Impala, Trino/Presto, Phoenix SQL/HBase, Spark SQL, MySQL, and PostgreSQL, and it integrates with YARN and Livy Spark for job execution.

The concrete problem it solves is fragmented, per-engine query access. Without a shared front end, each analyst needs a separate client for Hive, another for Impala, another for Trino, and separately managed access to HDFS, S3, ABFS, Ozone, or Google Storage files. Hue replaces that collection of disconnected tools with one web service where users write SQL with syntax highlighting and autocomplete, browse the underlying files and tables, and monitor the queries and jobs they submitted. Organizations use it to answer questions through self-service querying and report executing hundreds of thousands of queries daily.

Key capabilities

• Interactive SQL editing with syntax highlighting and autocomplete.
• File Browser for navigating and operating on HDFS, S3, ABFS, Ozone, and Google Storage (GS) files.
• Job Browser for monitoring and managing Hive queries, Impala queries, YARN applications, and Livy Spark jobs.
• Table Browser for exploring and managing database tables, schemas, and metadata.
• Table Importer that creates Hive and Impala tables from CSV or Excel files, uploaded from the local system or imported from remote filesystems including HDFS, S3, ABFS, Ozone, and GS.
• Multiple database connectors, including Hive, Impala, MySQL, and PostgreSQL, plus documented integrations for Trino/Presto, Phoenix SQL/HBase, and Spark SQL.
• SQL Scratchpad for building a custom editor, and a Query Service deployable on Kubernetes with a documented API.

Who uses it and how

• Enterprises running self-service analytics: the README reports 1000+ customers worldwide, including top Fortune 500 organizations, executing hundreds of thousands of queries daily.
• Evaluation and small deployments via a single Docker container, started with docker run -it -p 8888:8888 gethue/hue:latest and reachable at http://localhost:8888.
• Production query service on Kubernetes, installed from the Helm chart with helm repo add gethue https://helm.gethue.com followed by helm install hue gethue/hue.
• Data platform teams that configure the connectors for whichever warehouses and databases their analysts need to reach.
• Developers embedding a query experience into their own product using the SQL Scratchpad component.

Getting started

Start the server with Docker using the published image, docker run -it -p 8888:8888 gethue/hue:latest, then configure the databases to query. Kubernetes deployments use the Helm chart, or the live demo at demo.gethue.com can be tried first.

How it compares

The facts provide no list of paid products that Hue replaces, and the README excerpt names no competing tools. Hue therefore stands alone in this registry.

When to use it — and when not to

A self-hoster must run the Hue server and configure each connector for the databases and warehouses they want to query; the provided README excerpt does not spell out the supporting dependencies, so those must be checked against the installation documentation before committing. Teams that do not run Hive, Impala, Trino/Presto, Spark SQL, or a comparable warehouse will get little from the browsers, which are tied to that ecosystem. The licence is clear and recent commits exist, but the brief README excerpt is thin on operational detail, which is the main caution here.

docker run -it -p 8888:8888 gethue/hue:latest

helm repo add gethue https://helm.gethue.com
helm repo update
helm install hue gethue/hue

git clone https://github.com/cloudera/hue.git
cd hue
make apps
build/env/bin/hue runserver