Real-Time Analytics
Sub-second dashboards and data products on petabytes of data at any concurrency
Data Warehousing
Sub-second analytics on open lakehouse formats with no vendor lock-in
Observability in the AI Era
The most cost-effective alternative to Elasticsearch observability
Context Engineering
Hybrid search and fresh context for RAG, agents, and LLMs
The unified SQL database for engineers and Al agents.
10,000+ Enterprises Trust Apache Doris and VeloDB
REAL-TIME
Supports high-frequency, second-level streaming ingestion from both Kafka and Database CDC.
Replaces batch processing with incremental materialized views that refresh complex transformations in minutes.
10x on complex analytics . Under concurrency, it maintains a consistent 10ms response time across PB-scale datasets.
AI-READY
Empowers autonomous AI agents to interact directly with your data through seamless MCP Server integration for real-time decision-making.
Provides the ultimate retrieval foundation for RAG by unifying Full-text search and Vector search within a single high-performance engine.
Embeds LLM capabilities directly within the database to enable SQL-driven large-scale text analysis, and semantic exploration.
Leverages columnar JSON and multi-modal capabilities to master unstructured data at scale. It accelerates analytics, feature engineering, and data wrangling with seamless AI engine interoperability.
Seamlessly manage AI logs and traces with native integrations for Langfuse and the broader AI ecosystem. Gain full visibility into your AI stack with an ultra-low-cost observability solution.
UNIFIED
VeloDB/Doris outperforms ClickHouse through its advanced MPP architecture with a Cost-Based Optimizer (CBO) for efficient distributed joins and a strongly consistent primary key model for high-frequency real-time updates.
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VeloDB/Doris outperforms Trino in Lakehouse analytics by delivering 3x faster query speeds through its C++ vectorized engine and native local caching.
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VeloDB/Doris delivers 10x higher cost-efficiency and 5x faster write throughput than Elasticsearch by leveraging columnar storage with ZSTD compression, inverted indexes for flexible text search, and a native MPP engine for complex SQL-based analytics.
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USE CASES
Purpose-built and architected for data applications to handle high-concurrency and low-latency analytics.
Explore Customer-Facing AnalyticsSub-second analytics on petabyte-scale lakehouse data. Open formats, unified workloads, no vendor lock-in.
Explore Data WarehouseStreamline logs, metrics, and traces with a SQL-based observability stack, delivering lightning-fast insights at a fraction of the cost.
Explore ObservabilityStore vectors, full-text, structured data, and JSON in one database. Serve fresh context to LLMs and agents in milliseconds.
Explore Context EngineeringINTEGRATION


