VeloDB Cloud (Committed Contract)

Founded by the original creators of Apache Doris, VeloDB is the leading commercial distribution and managed service for the Apache Doris ecosystem. Apache Doris is a top-level Apache Software Foundation project with 14,000+ GitHub stars, 700+ contributors, and a vibrant open-source community. VeloDB contributes 1 PMC Chair, 9 PMC members, and 26 committers to the Apache Doris project, ensuring deep alignment between the commercial service and the open-source engine. VeloDB Cloud is fully compatible with Apache Doris, ensuring seamless migration and zero vendor lock-in between VeloDB Cloud and self-managed Apache Doris deployments.

Real-Time OLAP Analytics at Any Scale VeloDB Cloud leverages Apache Doris's columnar storage, MPP (Massively Parallel Processing) distributed architecture, and advanced vectorized execution engine to deliver industry-leading query performance.

• Sub-second query performance on petabyte-scale datasets using Apache Doris's vectorized execution engine and cost-based optimizer
• Real-time data ingestion with second-level freshness via high-throughput streaming ingestion, CDC (Change Data Capture), and micro-batch loading
• High concurrency supporting thousands of simultaneous queries for customer-facing analytics, embedded BI, and operational dashboards
• Materialized views for intelligent query acceleration - up to 42x faster queries with 98% reduction in scan size

Unified Engine - Replace Multiple Databases with One VeloDB Cloud consolidates the capabilities of multiple specialized systems into a single analytical database:

• OLAP data warehouse - replace ClickHouse, Druid, or Kylin for real-time reporting and interactive analytics
• Search and log analytics - replace Elasticsearch for observability (logs, traces, metrics) with 10x cost efficiency, 5x ingestion throughput, and 80% storage reduction with inverted index and 10:1 compression
• Lakehouse analytics - query Apache Iceberg, Apache Hudi, Delta Lake, and Apache Paimon directly with 3x faster performance than Trino/Presto, or accelerate with VeloDB internal tables for 10x improvement
• Federated queries - connect to MySQL, PostgreSQL, Oracle, SQL Server, and object storage (S3, GCS) via multi-catalog support

AI-Ready: Hybrid Search, Vector Search, and MCP Support Apache Doris natively integrates vector search, full-text search, and structured SQL analytics within a single columnar storage layer - enabling Hybrid Search and Analytics Processing (HSAP) for Generative AI, RAG (Retrieval-Augmented Generation), and agentic AI applications.

• Hybrid Search - combine vector similarity search, BM25 full-text search, and structured SQL filters in a single query for superior retrieval accuracy in RAG pipelines
• Vector search indexes - native approximate nearest neighbor (ANN) indexing for embedding-based semantic search at petabyte scale
• AI SQL functions - built-in LLM operators (summarize, classify, extract, translate, sentiment analysis) directly in SQL for AI-augmented analytics
• MCP (Model Context Protocol) support - connect AI agents directly to VeloDB via the Doris MCP Server for real-time data discovery, schema understanding, and query execution, enabling agentic AI applications with live analytical context
• AI observability - purpose-built for monitoring LLM systems with support for OpenTelemetry, Langfuse, and OpenLLMetry integration

Cloud-Native Architecture with Flexible Deployment

• Fully Managed SaaS: Zero-ops, fully managed experience with auto-scaling compute and storage
• BYOC (Bring Your Own Cloud): Data stays in your own AWS VPC for full data sovereignty and security compliance / Leverage your existing AWS Reserved Instances and Savings Plans
• Enterprise Software (Self-Managed): Deploy Apache Doris on EC2, EKS, or bare metal with VeloDB enterprise features, commercial support, and SLA guarantees

Cost-Effective at Scale

• Tiered storage - automatically tier data across NVMe cache, EBS, and S3 to optimize cost-per-query
• 10:1 compression ratio - columnar storage with advanced encoding reduces storage costs by up to 80%
• ARM processor support - run on AWS Graviton instances for up to 40% better price-performance
• Auto-scaling - elastically scale compute up and down based on workload demand

Production-Proven Across Industries

• Financial Services - real-time risk analytics, fraud detection, regulatory reporting
• E-Commerce & Retail - user behavior analytics, real-time recommendations, inventory dashboards
• Web3 & Fintech - on-chain analytics, trading dashboards, token analytics for millions of users
• Observability & DevOps - log analytics, distributed tracing, metrics monitoring at 10x lower cost than Elasticsearch
• IoT & Manufacturing - sensor data analytics, predictive maintenance, operational intelligence
• Generative AI - RAG pipelines, hybrid search, AI agent data backends, LLM observability