apache/impala

Health v2 · maintenance only

Adoption not part of the score

1285 stars · 558 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Apache Impala is a massively parallel, distributed SQL query engine written in C++ for analyzing petabyte-scale data stored in open data and table formats like Iceberg, Parquet, ORC, Kudu, HDFS, and cloud object stores. It provides low-latency, high-concurrency analytic (BI-style) SQL queries with LLVM-based per-query code generation and enterprise security via Kerberos, LDAP, TLS, and Ranger.

Use cases

• run low-latency SQL analytics on petabyte-scale data lakes
• query Apache Iceberg and Parquet tables with BI tools
• unify Hadoop and cloud storage analytics under one SQL engine
• serve high-concurrency dashboards over a data lakehouse
• migrate Hive workloads to a faster SQL engine
• analyze data in S3 or Azure Data Lake with standard SQL

When to choose

• you need fast, concurrent BI-style SQL over open table formats like Iceberg or Parquet
• you want to reuse existing Hive metadata, ODBC drivers, and Hadoop security frameworks
• you need linear scalability in multitenant environments on Linux clusters

When to avoid

• you need a lightweight single-node embedded database
• your workloads run on Windows or macOS
• you need transactional OLTP workloads rather than analytics
• you want a fully managed cloud warehouse without cluster operations

Facets

application · maturity stable

database search-engine security cryptography databases big-data analytics microservices cloud self-hosted sql-query-engine mpp olap apache-iceberg parquet orc kudu hadoop data-lake llvm-codegen bi-analytics data-engineering linux docker

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markdown · JSON · MCP: product_card(name="apache/impala")