Amazon Redshift
Fully managed, petabyte-scale cloud data warehouse for analytics and reporting
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
High-performance real-time analytical database with MPP architecture
Apache Doris is an MPP-based analytical database delivering sub-second query responses on massive datasets, supporting high-concurrency queries and complex analysis for real-time data warehousing.
Apache Doris is a high-performance, real-time analytical database built on MPP (Massively Parallel Processing) architecture. It delivers sub-second query responses on massive datasets while supporting both high-concurrency point queries and high-throughput complex analysis scenarios.
Doris uses a storage-compute integrated architecture with two core components: Frontend (FE) nodes handle query parsing, metadata management, and request routing, while Backend (BE) nodes manage data storage and query execution. Both components scale horizontally to support hundreds of machines and tens of petabytes of storage.
The database is highly compatible with MySQL protocol and supports standard SQL syntax, including most MySQL and Hive functions. Its vectorized columnar storage engine optimizes query performance and compression ratios, while the Pipeline execution model ensures efficient resource utilization.
Apache Doris excels in real-time reporting, ad-hoc analysis, user behavior analytics, and lakehouse query acceleration. Organizations use it to build unified data warehouses, accelerate data lake queries through federated analytics, and perform log analysis for observability. The platform supports various applications including AB testing platforms, user profiling, order analysis, and real-time dashboards with second-level data ingestion from upstream transactional databases.
When teams consider Apache Doris, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Real-Time Business Dashboards
Deliver sub-second reporting and decision-making dashboards with real-time data ingestion from transactional databases, enabling automated business processes and instant insights.
User Behavior Analytics Platform
Analyze user participation, retention, and conversion patterns with multidimensional ad-hoc queries, supporting population insights and targeted audience selection for marketing campaigns.
Lakehouse Query Acceleration
Accelerate queries across data lakes (Hive, Iceberg, Hudi) using federated analytics, eliminating data silos and simplifying architecture while maintaining data lake management capabilities.
Log Analysis for Observability
Perform real-time or batch analysis of distributed system logs and events to identify performance bottlenecks, troubleshoot issues, and optimize system reliability.
Frontend (FE) nodes handle query parsing, metadata management, and request routing, while Backend (BE) nodes manage data storage and query execution. Both scale horizontally and work together in the storage-compute integrated architecture.
Doris stores metadata and data with multiple replicas, using quorum protocol for synchronization. It supports Master, Follower, and Observer FE roles for disaster recovery, and automatically isolates faulty nodes to maintain cluster availability.
Yes, Apache Doris is highly compatible with MySQL protocol and supports standard SQL syntax, including most MySQL and Hive functions. You can connect using MySQL client tools and integrate with BI reporting and data transmission tools.
Doris offers flexible modeling including wide table models, pre-aggregation models, and star/snowflake schemas. You can flatten data during import or perform modeling through views, materialized views, and real-time multi-table joins.
Apache Doris provides second-level data ingestion capabilities, capturing incremental changes from upstream transactional databases within seconds to support real-time data warehouse scenarios.
Project at a glance
ActiveLast synced 4 days ago
