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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
Top commercial bank migrated from Elasticsearch to Apache Doris for PB-scale log storage and analytics
Elasticsearch vs ClickHouse vs Apache Doris — which powers observability better?
How Tencent Music saved 80% in costs by migrating from Elasticsearch to Apache Doris
Why Apache Doris is a Better Alternative to Elasticsearch for Real-Time Analytics
Replacing Apache Hive, Elasticsearch and PostgreSQL with Apache Doris
Creator of Talkie migrated from Loki and built a PB-scale logging system with Apache Doris
Apache Doris for log and time series data analysis in NetEase, why not Elasticsearch and InfluxDB?
Log analysis: Elasticsearch VS Apache Doris
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