We Put SQL Back in NoSQL
Query HBase with standard SQL and JDBC. Low latency OLTP and operational analytics for Hadoop.
Query HBase with standard SQL and JDBC. Low latency OLTP and operational analytics for Hadoop.
The trusted data platform for OLTP and operational analytics on Hadoop.
Use familiar SQL queries and JDBC APIs with full ACID transaction capabilities.
Low latency performance for small queries or seconds for tens of millions of rows.
Schema-on-read flexibility from the NoSQL world leveraging HBase as backing store.
Fully integrated with Spark, Hive, Pig, Flume, and Map Reduce.
Proven patterns where Phoenix delivers value.
Real-time SQL queries on operational data with ACID guarantees for business insights.
Transactional workloads with millisecond response times and full ACID support.
Build SaaS applications with tenant isolation using views and dynamic columns.
Fast lookups on non-primary key columns with automatic index maintenance.
SQL queries over time-series data with efficient storage and retrieval patterns.
ETL pipelines with Spark, Hive, and Map Reduce for comprehensive data workflows.
Recent capabilities now available in the 5.3.0 release.
Point your DynamoDB SDK clients at Phoenix using the phoenix-adapters REST service — no application rewrite required.
Native binary JSON column type with server-side projection, filtering, and atomic per-field updates.
Stream row-level changes as ordered, partitioned events — read with standard SQL, with full split/merge lineage.
Phoenix takes your SQL query, compiles it into HBase scans, and orchestrates execution to produce JDBC result sets.
SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY, and more. Full DML and DDL support.
Queries compiled into HBase scans with coprocessors and custom filters for millisecond performance.
Connect using standard JDBC URL: jdbc:phoenix:server1,server2:port
Apache Phoenix is a top-level Apache project with an active community of users and contributors. Join discussions, explore the language reference, and help shape the future of SQL on HBase.
From download to production in a few simple steps.