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As enterprises push forward with building a lakehouse architecture, they often face complex challenges. Apache Doris aims to facilitate this process. It offers easy data access (from Hive, Iceberg, Hudi, Paimon), an extensible connector framework (with Kudu, BigQuery, Delta Lake, Kafka, and Redis) and convenient cross-source data processing with high analytics performance. It also allows easy deployment, a rich set of data storage and management capabilities, and strong support for open table formats and file formats.
Rayner Chen, Apache Doris PMC Chair · 2025/06/30
EMQX now supports real-time data ingestion into Apache Doris for efficient IoT analytics
Top commercial bank migrated from Elasticsearch to Apache Doris for PB-scale log storage and analytics
Apache Doris 3.0.6 Released
Elasticsearch vs ClickHouse vs Apache Doris — which powers observability better?
How Tencent Music saved 80% in costs by migrating from Elasticsearch to Apache Doris
Apache Doris 2.1.9 Released
Slash your cost by 90% with Apache Doris Compute-Storage Decoupled Mode
Why Apache Doris is a Better Alternative to Elasticsearch for Real-Time Analytics
Apache Doris 3.0.4 Released
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