Apache Doris

Apache Doris is a modern, real-time data warehouse built on a massively parallel processing (MPP) architecture. It is designed to deliver ultra-fast analytics on large-scale, high-concurrency workloads, supporting both real-time and batch data ingestion. Originally developed by Baidu and now a top-level Apache project, Doris is widely adopted across industries for its simplicity, performance, and flexibility in handling complex analytical scenarios.

Features

• Real-time data ingestion via push-based micro-batch and pull-based streaming
• Columnar storage engine with vectorized execution and cost-based optimizer
• High-throughput and low-latency query performance
• Federated querying across Hive, Iceberg, Hudi, MySQL, PostgreSQL, and more
• Materialized views and advanced indexing for query acceleration
• SQL-based observability for log and event analysis
• Native support for complex data types and multidimensional analysis
• Seamless integration with BI tools and data platforms
• Built-in support for upsert, append, and pre-aggregation operations
• Scalable architecture with elastic deployment options

Capabilities

• Supports real-time reporting, ad-hoc analysis, and unified data warehousing
• Enables user behavior analysis, A/B testing, and e-commerce analytics
• Accelerates lakehouse queries with federated access and caching
• Handles high-concurrency workloads with sub-second response times
• Combines batch and stream processing for hybrid data pipelines
• Provides SQL-based access to structured, semi-structured, and nested data
• Offers decentralized metadata management for flexible data integration
• Powers IoT analytics with real-time ingestion and device-level granularity
• Facilitates log and event analysis in distributed systems
• Supports dynamic schema discovery and schema evolution

Benefits

• Delivers lightning-fast analytics for real-time decision-making
• Reduces infrastructure complexity and operational costs
• Enhances developer productivity with simplified architecture
• Improves data accessibility across silos and formats
• Enables agile business intelligence with flexible query capabilities
• Scales efficiently from small teams to enterprise-grade deployments
• Supports diverse use cases from finance to manufacturing and healthcare
• Backed by a vibrant open-source community and proven enterprise adoption
• Offers high availability and fault tolerance for mission-critical workloads
• Simplifies data lakehouse integration and accelerates time-to-insight