Apache Doris
Apache Doris is an open-source, real-time analytical MPP (massively parallel processing) database designed to deliver fast SQL queries over large volumes of both batch-loaded and streaming data.
Definition
Apache Doris is an open-source, real-time analytical MPP (massively parallel processing) database designed to deliver fast SQL queries over large volumes of both batch-loaded and streaming data.
Overview
Doris positions itself as a unified engine for both real-time analytics and interactive ad hoc queries, aiming to reduce the need for separate systems for reporting, dashboards, and exploratory SQL analysis. It uses a massively parallel processing (MPP) architecture, splitting queries across many nodes that process data in parallel, which is the same general approach used by other analytical engines such as Presto and Trino. Doris supports high-concurrency, low-latency queries typical of OLAP workloads, along with materialized views and various storage models to optimize different query patterns. It can ingest data through both bulk loading and near-real-time streaming pipelines, which lets it serve dashboards that need to reflect recent data changes without a separate real-time layer bolted on afterward. Doris originated at Baidu and was later contributed to the Apache Software Foundation, and it has seen particular adoption in markets and companies looking for an open-source alternative to proprietary MPP data warehouses. It competes in a crowded field of modern analytical databases that includes ClickHouse, StarRocks, and cloud data warehouses like Snowflake.
Key Features
- Massively parallel processing (MPP) query execution
- Unified support for real-time and batch analytical queries
- High-concurrency SQL interface for dashboards and reporting
- Materialized views to accelerate common query patterns
- Near-real-time data ingestion pipelines
- Horizontal scalability across commodity hardware
- Open-source alternative to proprietary MPP data warehouses