Open-Source Databases · cloudera

hue

Hue is an open-source SQL query editor and data exploration platform maintained by Cloudera. It provides a web-based interface for writing, executing, and sharing SQL queries against multiple databases and data warehouses, along with file browsing, job monitoring, and metadata exploration.

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Source: GitHub — github.com/cloudera/hue

1.4k

GitHub stars

410

Forks

JavaScript

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	cloudera/hue
Owner	cloudera
Primary language	JavaScript
License	Apache-2.0 — OSI-approved
Stars	1.4k
Forks	410
Open issues	27
Latest release	release-4.11.0 (2023-01-19)
Last updated	2026-07-04
Source	https://github.com/cloudera/hue

What hue is

Hue is a JavaScript/Python-based web application that acts as a SQL IDE with support for Hive, Impala, MySQL, PostgreSQL, Trino/Presto, Spark SQL, and other connectors. It includes syntax highlighting, autocomplete, file browser (HDFS/S3/ABFS/Ozone/GCS), job browser (YARN/Livy), table importer, and REST/Python/CLI APIs for programmatic access.

Quickstart

Get the hue source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/cloudera/hue.git2cd hue3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Self-Service Analytics & BI Querying

Organizations needing a centralized, user-friendly interface for end users to write and execute SQL queries against data warehouses without direct database access. Hue's autocomplete, syntax highlighting, and query history reduce friction for non-expert SQL users.

Multi-Warehouse Data Exploration

Teams operating multiple data sources (Hive, Impala, PostgreSQL, Presto, Spark SQL) who need a unified editor rather than separate tools. Hue's connector framework simplifies switching between systems and browsing metadata across platforms.

Data Pipeline Monitoring & Job Management

Environments running Hadoop/YARN jobs, Hive queries, or Livy Spark jobs where operators need real-time visibility into execution status, logs, and history. The Job Browser and query editor are integrated for quick diagnosis and resubmission.

Implementation considerations

Deployment: Choose Docker (quick start), Kubernetes + Helm (cloud-native), or manual setup; all are documented but Kubernetes requires familiarity with orchestration.
Database connectors must be configured post-deployment; review the Configuration Guide and ensure network access and credentials are prepared for each target database.
SQL parser support varies by dialect; test syntax highlighting and autocomplete against your specific SQL variants (Hive vs. Presto vs. PostgreSQL) before rollout.
Multi-user environments require a backend database (typically SQLite or PostgreSQL) to store queries, job history, and user metadata; plan for persistent storage.
Performance tuning may be needed for large query results or high user concurrency; monitor server logs and consider horizontal scaling if serving many concurrent users.

When to avoid it — and what to weigh

Lightweight, Embedded Use Cases — If you need a minimal SQL IDE for a single-server deployment without Docker/Kubernetes, Hue's architectural overhead (web server, backend services, dependencies) may be excessive compared to lighter alternatives.
Real-Time OLTP or Sub-Millisecond Latency Required — Hue is designed for analytical queries on data warehouses, not transactional workloads. Performance expectations must align with typical ETL/BI query timelines; it is not a real-time query engine.
Proprietary or Exotic Database-Only Support — If your primary database is not in Hue's supported connector list (Hive, Impala, MySQL, PostgreSQL, Trino, Spark SQL, etc.), custom connector development is required. Check the Configuration Guide to confirm your database is supported.
Minimal Maintenance & Long-Term Stability Unknown — Latest release (4.11.0) was in January 2023, with last push in July 2026. If you require frequent security patches or rapid bug fixes, verify Cloudera's support roadmap and SLA before committing to production.

License & commercial use

Licensed under Apache License 2.0, a permissive OSI-approved license that permits commercial use, modification, and distribution with standard attribution and liability disclaimers.

Apache 2.0 permits commercial use and derivative works. However, this is open-source software; Cloudera provides commercial support and hosted offerings (gethue.com) separately. For production use, review Cloudera's support terms and any enterprise SLA agreements independently.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

Authentication model (LDAP, OAuth, basic auth) and database credential management are not detailed in the provided data. Network segmentation should isolate Hue from untrusted users. Query logging and audit trails should be reviewed to comply with data governance policies. Sensitive credentials (database passwords, cloud access keys) must be stored securely using environment variables or a secrets manager. Review Cloudera's security advisories and perform penetration testing in sensitive environments before production deployment.

Alternatives to consider

Apache Superset

Modern, lighter-weight BI and analytics tool with SQL IDE, visualization, and dashboarding. Better for organizations focused on BI/visualization; less feature-rich for pure SQL editing and job monitoring.

DBeaver (open-source or commercial)

Mature desktop/web SQL IDE with broad database support and strong SQL authoring features. Lighter footprint; lacks Hue's Hadoop ecosystem integration (YARN, Livy, HDFS browser) and multi-warehouse management.

Databricks SQL Editor (Databricks proprietary) or Snowflake Web UI

Cloud-native SQL editors with deep integration to their respective platforms and built-in optimization. Not open-source; best for organizations already committed to those cloud data warehouses.

Software development agency

Build on hue with DEV.co software developers

Hue is a mature, Apache 2.0-licensed SQL IDE trusted by 1000+ organizations. Suitable for multi-warehouse analytics and self-service querying. Get started with Docker in seconds; plan 2–4 weeks for production hardening and integration testing.

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hue FAQ

Can Hue run on a single server or does it require Hadoop/YARN?

Hue can run standalone with just a database backend (SQLite or PostgreSQL). YARN and Livy integration are optional for job monitoring; core SQL editing works independently.

Does Hue include data visualization or dashboarding?

Not clearly stated in the data provided. Hue is primarily a query editor and metadata browser; visualization capabilities, if any, are not described. For dashboarding, consider pairing Hue with a BI tool like Superset.

How are database credentials managed securely in Hue?

Credentials storage and rotation mechanisms are not detailed in the provided data. Requires review of the Configuration Guide and security best practices documentation before production deployment.

What is the typical query execution latency and concurrent user capacity?

Unknown. Benchmarks and performance characteristics are not provided. Performance depends on underlying databases, query complexity, and server resources. Test in your environment before production rollout.

Software development & web development with DEV.co

DEV.co helps companies turn open-source tools like hue into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source databases stack.

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