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Text of the page (random words):
apache hudi an open source data lake platform apache hudi skip to main content ️ if you like apache hudi give it a star on github docs learn tutorial series blogs talks video guides faq tech specs tech specs pre 1 0 contribute developer sync call how to contribute developer setup rfc process security community get involved community syncs office hours team github slack linkedin youtube x ecosystem adopters roadmap integrations vendors download docs learn contribute community ecosystem download back to main menu apache hudi tm brings to data lakes get started community what is hudi apache hudi is an open data lakehouse platform built on a high performance open table format to bring database functionality to your data lakes hudi reimagines slow old school batch data processing with a powerful new incremental processing framework for low latency minute level analytics integrations data streaming apache kafka apache pulsar databases postgresql mysql cdc debezium apache flink cdc file formats apache parquet apache orc apache avro csv json lake storage apache hadoop amazon s3 google cloud storage azure blob storage alibaba cloud ibm cloud oracle cloud tencent cloud minio data catalogs aws glue data catalog google bigquery apache hive metastore datahub apache xtable incubating for sync data warehouses amazon redshift clickhouse interactive analytics presto trino apache hive aws athena google bigquery apache doris starrocks apache impala data processing apache spark apache flink databricks aws emr azure hdinsight onehouse ray daft orchestration dbt apache airflow hudi features mutability support for all workload shapes sizes quickly update delete data with fast pluggable indexing this includes database cdc and high scale streaming data with best in class support for out of order records bursty traffic data deduplication unlock 10x efficiency by incrementally processing new data replace old school batch pipelines with incremental streaming on your data lake experience faster ingestion and lower processing times for your data pipelines acid transactional guarantees for your data lake atomic writes with relational streaming data consistency models snapshot isolation and non blocking concurrency controls tailored for longer running lake transactions analyze historical data with time travel query historical data with the ability to roll back to a table version debug data versions to understand what changed over time audit data changes by viewing the commit history interoperable multi cloud ecosystem support built on open data formats with extensive ecosystem support across cloud vendor ecosystem with plug and play options for popular data sources query engines automatic table services for a high performance lakehouse fully automated table services that continuously schedule orchestrate clustering compaction cleaning file sizing indexing to ensure tables are always optimized open data lakehouse platform to get you going faster effortlessly build your lakehouse with built in tools for auto ingestion from services like debezium and kafka and auto catalog sync to major cloud engines more query acceleration through multimodal indexes experience faster write transactions on huge wide tables faster query performance with first of its kind multimodal indexing subsystem resilient pipelines with schema evolution enforcement easily change the current schema of a hudi table to adapt to the data that is changing over time and ensure pipeline resilience by failing fast and avoiding data corruption why hudi the most innovative and completely open data lakehouse platform in the industry trusted platform battle tested and proven in production in some of the largest data lakes on the planet open source hudi is a thriving growing community that is built with contributions from people around the globe high performance hudi s storage format is purpose built to continuously deliver performance as data scales data streams take advantage of built in cdc sources and tools for streaming ingestion hudi blogs srikanth mamidala august 26 2026 beyond offset lag computing time in queue for apache hudi data lake pipelines at petabyte scale sivabalan narayanan august 14 2026 point lookups on the lakehouse how hudi indexes accelerate read heavy workloads sivabalan narayanan august 13 2026 apache hudi vs apache iceberg performance what benchmarks show and what we measured sivabalan narayanan august 12 2026 apache hudi vs delta lake for write heavy workloads sivabalan narayanan august 11 2026 apache hudi vs apache iceberg for streaming ingestion sivabalan narayanan august 6 2026 apache hudi vs apache iceberg for cdc workloads sivabalan narayanan august 5 2026 migrating from apache iceberg to apache hudi sivabalan narayanan august 4 2026 migrating from delta lake to apache hudi sivabalan narayanan july 30 2026 migrating from apache hive tables to apache hudi sivabalan narayanan july 29 2026 migrating from parquet to apache hudi a practical guide view all join our community get technical help influence the product roadmap see what s new with hudi youtube linkedin github slack mailing x about our vision concepts team releases download adopters learn quick start tutorial series blog talks video guides faq hudi on cloud aws google cloud alibaba cloud microsoft azure tencent cloud ibm cloud oracle cloud community get involved vendors slack github x youtube linkedin mailing list apache events thanks license security privacy telemetry sponsorship foundation copyright 2021 the apache software foundation licensed under the apache license version 2 0 hudi apache and the apache feather logo are trademarks of the apache software foundation