Sold by: VeloDB Inc
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VeloDB Cloud: The Real-Time Analytical Database Built for Analytics and AI.
VeloDB Cloud is the fully managed, cloud-native real-time analytical database powered by Apache Doris - the fastest open-source OLAP engine trusted by 5,000+ enterprises worldwide. Deliver sub-second analytics, hybrid search, and AI-ready data infrastructure from a single unified platform.
Overview
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 and 700+ contributors. VeloDB Cloud is 100% compatible with Apache Doris, so migration is seamless with zero vendor lock-in. Pay only for what you use, billed hourly across SaaS, BYOC, and Enterprise plans. Free trial available. See full pricing and the cost estimator at https://www.velodb.io/pricing .
One engine for real-time analytics at any scale VeloDB Cloud combines columnar storage, MPP (Massively Parallel Processing) architecture, and a vectorized execution engine to deliver:
- Sub-second queries on petabyte-scale data, with a cost-based optimizer and materialized views (up to 42x faster queries, 98% less data scanned)
- Real-time ingestion with second-level freshness via streaming, CDC (Change Data Capture), and micro-batch loading
- High concurrency for thousands of simultaneous queries powering customer-facing analytics and embedded BI
Replace multiple systems with one
- OLAP analytics: a faster, simpler alternative to ClickHouse, Druid, and Kylin
- Log and search analytics: replace Elasticsearch for observability at up to 10x lower cost, 5x ingestion throughput, and 80% storage savings
- Lakehouse: query Apache Iceberg, Hudi, Delta Lake, and Paimon directly (3x faster than Trino/Presto), or accelerate with internal tables
- Federated queries across MySQL, PostgreSQL, Oracle, SQL Server, and object storage (S3, GCS)
AI-ready: hybrid search, vector search, and MCP Apache Doris natively unifies vector search, full-text search, and SQL analytics in a single storage layer for Generative AI and RAG workloads:
- Hybrid Search: combine vector similarity, BM25 full-text, and SQL filters in one query for higher retrieval accuracy
- Native vector indexes for embedding-based semantic search at scale
- AI SQL functions (summarize, classify, extract, translate, sentiment) built directly into SQL
- MCP (Model Context Protocol) support to connect AI agents to live analytical data
- AI observability via OpenTelemetry, Langfuse, and OpenLLMetry
Flexible deployment
- Fully Managed SaaS: zero-ops with auto-scaling compute and storage
- BYOC (Bring Your Own Cloud): data stays in your own AWS VPC for full sovereignty; reuse your Reserved Instances and Savings Plans
- Enterprise (Self-Managed): run on EC2, EKS, or bare metal with commercial support and SLAs
Tiered storage (NVMe, EBS, S3), 10:1 compression, and AWS Graviton/ARM support deliver up to 40% better price-performance. Production-proven across financial services, e-commerce, Web3/fintech, observability, IoT, and Generative AI.
Highlights
- 1) Real-time analytical database powered by Apache Doris with sub-second query latency on petabyte-scale data; 2)AI-ready with native hybrid search (vector + full-text + SQL), MCP protocol support, and built-in AI SQL functions for RAG and agentic AI.
- 1) Unified OLAP engine replacing ClickHouse, Elasticsearch, and Trino-10x cost reduction for log analytics, 3x faster lakehouse queries; 2)Cloud-native with storage-compute separation, tiered storage, auto-scaling, and AWS Graviton support.
- 1) Fully compatible with Apache Doris - zero vendor lock-in with bidirectional migration between managed and self-managed deployments; 2) Flexible deployment: Fully Managed SaaS, BYOC (data in your VPC), or Enterprise Self-Managed on AWS.
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Dimension | Cost/unit |
|---|---|
VeloDB Cloud Usage | $0.002 |
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Customer support services e-mail : support@velodb.io
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By VeloDB Inc
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Real-Time Query Performance
Sub-second query latency on petabyte-scale data with cost-based optimizer and materialized views enabling up to 42x faster queries and 98% less data scanned
Hybrid Search Capabilities
Native unified vector search, BM25 full-text search, and SQL analytics in a single storage layer with support for combining vector similarity, full-text, and SQL filters in one query
Data Ingestion and Freshness
Real-time ingestion with second-level freshness via streaming, CDC (Change Data Capture), and micro-batch loading supporting high concurrency for thousands of simultaneous queries
Multi-Source Query Support
Federated query capability across MySQL, PostgreSQL, Oracle, SQL Server, and object storage (S3, GCS), plus direct querying of Apache Iceberg, Hudi, Delta Lake, and Paimon
Storage Architecture and Optimization
Columnar storage with MPP architecture, vectorized execution engine, tiered storage (NVMe, EBS, S3), 10:1 compression, and AWS Graviton/ARM support
Distributed SQL Database Architecture
Fully managed, distributed SQL database with lock-free cloud-native architecture designed for transactional (OLTP) and analytical (OLAP) workloads
High-Throughput Data Ingestion
Parallel, distributed lock-free ingestion capable of processing millions of events per second using Pipelines
Vector Search Capabilities
Indexed vector search with full-text search capabilities for generative AI applications with elastic scale-out architecture
Real-Time Query Processing
Low-latency SQL query execution on billions of rows of data with support for tens or hundreds of thousands of concurrent users
Unified Workload Engine
Single engine supporting transactional (OLTP), analytical (OLAP), and vector (GenAI) workloads without requiring data movement between systems
Native Object Store Capabilities
Native Object Store (NOS) Read/Write functionality enabling direct interaction with object store data
Multi-Cloud Analytics Platform
Connected multi-cloud data platform supporting full integration with SQL, Python, R languages and data sources including object stores and HDFS
Advanced Analytics Functions
4D analytics, nPath, sessionization, attribution, and scoring capabilities for descriptive, diagnostic, predictive, and prescriptive analytics
Amazon S3 Integration
Direct integration with Amazon S3 for backup, restore, and optional direct querying of object store data
Included Management Tools
Rights to use Teradata Data Stream Controller, Ecosystem Manager, Query Service, Server Management, and Viewpoint tools with Premier Cloud Support
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