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Apache Hive vs Apache Impala

Apache Hive: The original SQL-on-Hadoop warehouse, now mostly valued for its Metastore and Iceberg support. Apache Impala: Low-latency MPP SQL engine for Hadoop, Kudu and Iceberg tables, developed largely by Cloudera.

key differences

  • Apache Hive is built for larger datasets (Multi-PB) than Apache Impala (≤ 1 PB).
  • Only Apache Hive has materialized views.

choose apache-hive for

  • +Existing Hadoop data warehouses
  • +Shared Metastore catalog for lakehouse engines
  • +Large overnight batch SQL

best at · Warehouse, OLAP, Lakehouse

choose apache-impala for

  • +Interactive BI on Hadoop and Cloudera clusters
  • +Analytics over Kudu tables
  • +Iceberg queries in Cloudera Data Warehouse

best at · OLAP, Warehouse, Lakehouse

Apache HiveThe original SQL-on-Hadoop warehouse, now mostly valued for its Metastore and Iceberg support.
Apache ImpalaLow-latency MPP SQL engine for Hadoop, Kudu and Iceberg tables, developed largely by Cloudera.
overview
Primary model
Relational
Relational
Also supports
Columnar / OLAP
Columnar / OLAP
Type
Database engine
Database engine
Status
Active
Active
Developer
Apache Software Foundation
Apache Software Foundation
First release
2010
2013
Latest version
4.2.1 (Aug 24, 2026)
4.5.3 (Oct 6, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
30.1
29.0
Rank
#87
#91
GitHub stars
6K
1.3K
Stack Overflow questions
21.7K
2.1K
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Limited
Limited
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Distributed, Client server
Distributed, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
—
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
AWS, Google Cloud, Azure
–
capabilities
Transactions
✓
✓
Joins
✓
✓
Secondary indexes
—
—
Full-text search
—
—
Vector search
—
—
Geospatial
—
—
JSON
✓
✓
Change data capture
—
—
Triggers
—
—
Stored procedures
—
—
Materialized views
✓
—
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
✓
✓
In-memory
—
—
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
—
—
Role-based access
✓
✓
Time travel
✓
✓
Branching
—
—
Online schema changes
—
—
Streaming ingest
—
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
HiveQL
SQL (Impala dialect, HiveQL-compatible)
Client languages
Java, Python, Go, JavaScript
Python, Java, C++, Go
Best for
Warehouse, OLAP, Lakehouse, Metadata
OLAP, Warehouse, Lakehouse
Add more to this comparisonNot sure either fits? Try smart match

Apache Hive vs Apache Impala: FAQ

What is the difference between Apache Hive and Apache Impala?

Apache Hive: The original SQL-on-Hadoop warehouse, now mostly valued for its Metastore and Iceberg support. Apache Impala: Low-latency MPP SQL engine for Hadoop, Kudu and Iceberg tables, developed largely by Cloudera. Apache Hive is built for larger datasets (Multi-PB) than Apache Impala (≤ 1 PB). Only Apache Hive has materialized views.

When should I choose Apache Hive over Apache Impala?

Choose Apache Hive for existing Hadoop data warehouses, shared Metastore catalog for lakehouse engines and large overnight batch SQL. Choose Apache Impala for interactive BI on Hadoop and Cloudera clusters; analytics over Kudu tables; and iceberg queries in Cloudera Data Warehouse.

Is Apache Hive or Apache Impala more popular?

Apache Hive ranks #87 on the WhichDB Score (30.1/100) and Apache Impala ranks #91 (29.0/100). Popularity is not fit: check the requirements that matter for your project.

Are Apache Hive and Apache Impala open source?

Yes. Apache Hive is open source. License: Apache License 2.0. Yes. Apache Impala is open source. License: Apache License 2.0.