Skip to main content
Skip to main content
12K+
Github stars
4000+
Enterprises using it
600+
Total contributors
120+
Monthly active contributors
Apache Doris version 2.1.5 has been released
Release Note

Apache Doris version 2.1.5 has been released

In this update, we have optimized various functional experiences for data lakehouse and high concurrency scenarios, functionalities of asynchronous materialized views. Additionaly, we have implemented several improvemnents and bug fixes to enhance the stability.

Read more
Migrate data lakehouse from BigQuery to Apache Doris, saving $4,500 per month
Best Practice

Migrate data lakehouse from BigQuery to Apache Doris, saving $4,500 per month

Dien Tran Thanh shares his firsthand experience, proven best practices, and insightful suggestions for migrating from BigQuery to Apache Doris to build a more cost-efficient data warehouse.

Read more
Why Apache Doris is the Best Open Source Alternative to Rockset
Top News

Why Apache Doris is the Best Open Source Alternative to Rockset

Among of all the claim-to-be alternatives to Rockset, Apache Doris is one of the few that cover all the key features of Rockset.

Read more
Steps to industry-leading query speed: evolution of the Apache Doris execution engine
Tech Sharing

Steps to industry-leading query speed: evolution of the Apache Doris execution engine

From the Volcano Model to the Pipeline Execution Engine, and now PipelineX, Apache Doris brings its computation efficiency to a higher level with each iteration.

Read more

What is Apache Doris

Learn more

Core capabilities

Real-time ingestion and storage
Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation.
Lightning-fast query
Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine.
Federated querying
Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL.
Semi-structured data
Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches.
Elastic architecture
Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.
Open ecosystem
Compatible with MySQL protocol and ANSI SQL, easily integrated with BI tools. Provide open data API to be accessible for external compute engines like Spark, Flink and ML/AI.

Unified data warehouse

for various analytics use cases

From traditional batch reporting to real-time reporting and dashboards. From internal-facing analytics like traditional BI to customer-facing analytics. From decision support analytics to algorithm-driven real-time decision-making.
Read JD.com story

Connect with community

Developer mailing list
GitHub discussions
Slack workspace
Twitter
LinkedIn
All video resources

Start a real-time analytical journey with Apache Doris

DownloadRun anywhere
ASF
Resources
Community
Join the community
Copyright © 2024 The Apache Software Foundation,Licensed under the Apache License, Version 2.0. Apache, Doris, Apache Doris, the Apache feather logo and the Apache Doris logo are trademarks of The Apache Software Foundation.