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https://wiki.apache.org/confluence/spaces/INCUBATOR/pages/195727327/May2022
The donated 5 repositories have been migrated from hugegraph org to apache org, 7 committers have completed the github account association, they are granted codebase write permissions, 5 of them have been initialized as PPMC members
https://wiki.apache.org/confluence/spaces/INCUBATOR/pages/140774569/February2020
org/confluence/display/INCUBATOR/February2020 There are presently 46 podlings incubating
https://wiki.apache.org/confluence/spaces/INCUBATOR/pages/173083657/February2021
Do not include long URLs and use the apache URL shortener https://s
https://cwiki.apache.org/confluence/spaces/INCUBATOR/pages/110694277/October2018
It may be difficult to do so as the project
never really got started at Apache and most of the initial committers
haven't signed ICLAs
https://wiki.apache.org/confluence/exportword?pageId=110694277
It may be difficult to do so as the project
never really got started at Apache and most of the initial committers
haven't signed ICLAs
https://wiki.apache.org/confluence/spaces/INCUBATOR/pages/110694384/September2018
org/project/apache-airflow/ #history
How would you assess the podling's maturity
https://apache.org/foundation/records/minutes/2018/board_minutes_2018_09_19.txt
Special thanks to: * Rich Bowen for coordinating * Ruth Suehle, for "everything" (Ruth is bridging the gap between producers) * Kevin McGrail, for fundraising * Sally Khudairi, for marketing assistance * Sharan Foga, for organizing the ASF booth presence * Trevor Grant, for being our on-site person for the booth *
https://seatunnel.apache.org/blog
In enterprise-level data integration, data consistency is one of the core concerns for technical decision-makers. However, behind this seemingly simple requirement lies complex technical challenges and architectural designs.
When using
https://doris.apache.org/blog/apache-doris-4-1-iceberg-v3/
1 on Iceberg V3: Running the Full Lakehouse Lifecycle from One SQL Engine - Apache Doris
velodb
https://doris.apache.org/blog/apache-doris-variant-open-lakehouse/
Apache Doris · Mingyu ChenSeptember 15, 2026
Preview: Apache Doris 5
https://doris.apache.org/blog/apache-doris-lance-physical-ai-analytics/
Apache Doris · Wenqiang LiSeptember 8, 2026
Abstract:
Apache Doris 5
https://doris.apache.org/blog/apache-doris-paimon-agentic-ai-data-loop/
Apache Doris · Wenqiang LiSeptember 9, 2026
Abstract
Apache Doris 5
https://doris.apache.org/blog/kwai-paimon-vector-search-apache-doris/
Apache Doris · Wenqiang Li; Kwai · Junrui Li, Shiyao Yu, Fangyuan DengSeptember 10, 2026
Introduction:
Kwai uses Apache Doris in production to query vector indexes directly on Apache Paimon tables
https://doris.apache.org/blog/olake-iceberg-and-doris/
Set Up a Lakehouse with PostgreSQL, Apache Iceberg, and Apache Doris in 15 Minutes - Apache Doris
Olake · Rohan KhameshraApril 23, 2026
import { BlogLink } from
https://fluss.apache.org
Query engines along the bottom include Apache Flink, Apache Spark, Trino, StarRocks, Apache Doris, DuckDB and Ray
https://inlong.apache.org/blog/2023/03/23/release-1.6.0
Apache InLong recently released version 1
https://seatunnel.apache.org/blog/2.1.0-Released-Apache-SeaTunnel-Incubating-First-Apache-Release-Refactors-Kernel-and-Supports-Flink-Overall
Apache SeaTunnel(Incubating) First Apache Release Refactors Kernel and Supports Flink Overall | Apache SeaTunnel
March 18, 2022 · 6 min read
On December 9, 2021, Apache SeaTunnel(Incubating) entered the Apache Incubator, and after nearly four months of endeavor by the community contributors, we passed the first
https://doris.apache.org/blog/xanhsm-with-apache-doris/
How Xanh SM, Leading EV ride hailer in Vietnam, Built Real-Time Recommendations with Apache Doris - Apache Doris
velodb
https://doris.apache.org/blog/from-hive-hbase-and-trino-to-apache-doris-tuhu-cars-unified-olap-architecture/
From Hive, HBase, MySQL, and Trino to Apache Doris: Tuhu Car's Unified OLAP Architecture - Apache Doris
Tuhu Car · Wenbo WangJuly 3, 2026
import { BlogLink } from
https://doris.apache.org/blog/json-in-agent-observability-variant-and-inverted-indexes-in-apache-doris/
Hybrid Modeling for JSON in Agent Observability: VARIANT and Inverted Indexes in Apache Doris - Apache Doris
velodb
https://doris.apache.org/blog/why-ai-agents-need-real-time-analytics-and-hybrid-search/
Why AI Agents Need Real-Time Analytics and Hybrid Search: The Data Infra for Production Agents - Apache Doris
velodb
https://doris.apache.org/blog/apache-doris-and-polaris-per-user-identity-mode/
/src/components/blogs/components/see-more';
Apache Doris 4
https://doris.apache.org/blog/databricks-rt-and-ltap-oltp-olap-real-time-olap-and-htap/
How does it fit into OLTP, OLAP, real-time OLAP, and HTAP - Apache Doris
Databricks RT and LTAP are here
https://doris.apache.org/blog/apache-doris-4-1-spill-to-disk/
/src/components/blogs/components/see-more';
Apache Doris 4
https://doris.apache.org/blog/autonomous-driving-multimodal-search/
/src/components/blogs/components/see-more';
An autonomous driving company consolidated fragmented data platforms by adopting Apache Doris as a unified analytics engine, enabling seamless search across text, vectors, labels, and metadata while reducing query times from minutes to seconds
https://doris.apache.org/blog/from-data-silos-to-context-silos/
From Data Silos to Context Silos: What Database History Teaches Us About the AI Infrastructure Problem - Apache Doris
velodb
https://doris.apache.org/blog/mexican-mining-giant-azure-to-apache-doris/
/src/components/blogs/components/see-more';
One of largest mining companies in Mexico migrated from Azure Synapse to Apache Doris to solve unpredictable cloud costs and slow query performance across its 20,000-employee operation
https://doris.apache.org/blog/how-we-built-production-vector-search-in-apache-doris/
/src/components/blogs/components/see-more';
Apache Doris 4
https://doris.apache.org/blog/how-stepfun-built-agent-observability-platform-with-apache-doris/
/src/components/blogs/components/see-more';
StepFun built StepTrace, a PB-scale agent observability platform on Apache Doris, to analyze agent traces, costs, search, evaluation loops, and infrastructure behavior in real time
https://doris.apache.org/blog/netease-games-unified-doris-lakehouse/
/src/components/blogs/components/see-more';
NetEase Games consolidated six specialized data systems into Apache Doris across two phases, first unifying real-time analytics, then adding batch processing capabilities to create a lakehouse architecture serving 15 million daily queries