Apache Hudi
Big data processing and distribution systems
Database software
Big data software
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- Ease of use
- Ease of management
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What is Apache Hudi
Apache Hudi is an open-source data lake storage framework that manages large analytical datasets on object storage and distributed file systems while enabling incremental processing and upserts/deletes. It targets data engineering teams building lakehouse-style pipelines with engines such as Apache Spark, Apache Flink, and query engines that read Hudi tables. Hudi provides table services (e.g., compaction, clustering, cleaning) and supports copy-on-write and merge-on-read storage modes to balance query performance and ingestion latency.
Incremental ingestion and querying
Hudi tracks commits and file-level changes to support incremental reads for downstream pipelines. This reduces the need to reprocess full datasets when only new or changed records arrive. It is well-suited for CDC-style ingestion and near-real-time data lake updates using supported compute engines.
Upserts and deletes on lakes
Hudi provides record-level upserts and deletes on top of columnar files in object storage, addressing a common limitation of append-only data lakes. It maintains indexes and metadata to locate records efficiently during writes. This enables maintaining slowly changing dimensions and mutable fact tables without moving data into a separate database system.
Built-in table management services
Hudi includes operational services such as compaction (for merge-on-read), clustering, cleaning, and retention management. These services help control small files, optimize layout, and manage storage growth over time. Compared with platforms that bundle these capabilities as managed services, Hudi exposes them as configurable table operations that can be scheduled in existing orchestration tools.
Operational complexity and tuning
Running Hudi effectively requires configuring write modes, indexing, compaction/clustering schedules, and file sizing to match workload patterns. Misconfiguration can lead to small-file proliferation, high write amplification, or degraded query performance. Teams often need strong data engineering and distributed systems expertise to operate it reliably at scale.
Engine and feature compatibility gaps
Capabilities and performance can vary depending on the processing/query engine and the table type (copy-on-write vs merge-on-read). Some advanced behaviors (e.g., certain incremental patterns, concurrency controls, or metadata features) may not be uniformly supported across all readers/writers. This can introduce integration testing overhead when multiple engines access the same tables.
Not a full DBMS experience
Hudi is a storage framework rather than a complete database service, so it does not provide a single integrated SQL endpoint, workload management, or fully managed operations by default. Governance, security, and catalog integration depend on the surrounding lakehouse stack. Organizations seeking turnkey administration and elastic scaling may need additional managed infrastructure or a commercial distribution.
Plan & Pricing
Apache Hudi is an open-source project distributed under the Apache License, Version 2.0. The official project website does not list any paid plans, tiers, or pricing — the software is available for free download and use. Key notes: - Licensed under Apache License 2.0 (per official site footer). - No subscription plans, commercial tiers, or pricing information on the official site. - Integrations and cloud vendor support are listed, but those are integrations; any paid commercial services (cloud providers or third-party vendors) are not detailed as Hudi vendor pricing on the official project site.
Seller details
Apache Software Foundation
Wakefield, Massachusetts, USA
1999
Non-profit
https://www.apache.org/
https://x.com/TheASF
https://www.linkedin.com/company/the-apache-software-foundation/
