VeloDB Cloud
VeloDB Cloud is a fully managed, real-time analytics and search database built on Apache Doris, the open-source OLAP engine used by over 5,000 enterprises.
Publisher review
VeloDB Cloud is a fully managed, real-time analytics and search database built on Apache Doris, the open-source OLAP engine used by over 5,000 enterprises. It targets teams needing sub-second analytics, hybrid search, and AI-ready data infrastructure from a single platform, particularly for observability (log analytics), real-time dashboards, and high-concurrency query workloads. Founded in 2025 by the original creators of Apache Doris, VeloDB Inc. offers both SaaS and Bring Your Own Cloud (BYOC) deployment on AWS, Azure, and Google Cloud, with a self-managed Enterprise edition for on-premises or Kubernetes environments.
VeloDB Cloud uses a multi-compute, shared-data architecture that separates storage and compute, allowing independent scaling of clusters without downtime. It supports high-throughput real-time data updates and high concurrency, claiming 7x faster query performance and 8x higher concurrency than competitors. The database includes rich indexing options: Skip Index (Minmax Index, BloomFilter Index) and Point Query Index (Prefix Index, Inverted Index). It ingests data from OpenTelemetry, Logstash, Filebeat, and other ELK ecosystem tools, and integrates with Grafana and Kibana for visualization. The platform handles complex JOINs and full-text search via JSON and inverted indexes.
In log analytics benchmarks, VeloDB Cloud outperforms Elasticsearch using only 1/6 the resources, with faster data ingestion and query response times. It competes directly with Redshift, Snowflake, ClickHouse, and Elasticsearch, positioning itself as a unified replacement for separate analytics and search databases. Its multi-cloud support and BYOC option appeal to organizations that want cloud flexibility without vendor lock-in, while the Enterprise edition offers 36 months of extended support for on-premises deployments.
The main trade-offs are pricing and deployment flexibility. SaaS plans are Pay-As-You-Go only unless a private contract is negotiated, and BYOC billing covers only compute ($0.11/vCPU/h), but storage and cache costs apply separately. Some advanced features (e.g., dedicated metadata service, TDE/CMEK) require the Premium plan. The product is new (2025), so the ecosystem and community are smaller than those of established competitors. Also, the Enterprise edition's pricing is undisclosed, requiring a sales inquiry.
How it works
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Multi-compute shared-data architecture
Separates storage and compute, allowing independent scaling of compute clusters without affecting ongoing operations or data access.
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Rich indexing support
Includes Skip Index (Minmax, BloomFilter) and Point Query Index (Prefix, Inverted) to accelerate diverse query patterns.
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Real-time data ingestion
Supports high-throughput updates from OpenTelemetry, Logstash, and Filebeat, achieving seconds-vs-minutes latency over competitors.
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High concurrency and JOINs
Handles complex JOINs and high concurrency for analytical workloads, claiming 8x higher concurrency than Redshift or Snowflake.
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Multi-cloud and BYOC deployment
Available on AWS, Azure, and Google Cloud via SaaS or BYOC, letting customers run in their own VPC for data residency.
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Grafana and Kibana integration
Works with Grafana and Kibana for visualization, enabling teams to reuse existing dashboards and monitoring stacks.
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High availability with zero-downtime scaling
Cluster scaling does not impact ongoing business operations, with Premium plan offering dedicated metadata service and virtual clusters.
Strengths and trade-offs
Strengths
- Delivers 7x faster query performance than Elasticsearch in log analytics benchmarks, using only 1/6 the resources.
- Supports 8x higher concurrency than Redshift and Snowflake for analytical workloads, per vendor claims.
- Achieves real-time data latency of seconds versus minutes compared to Elasticsearch for ingestion and queries.
- Provides a single unified platform for sub-second analytics, hybrid search, and AI-ready data infrastructure.
Trade-offs
- SaaS plans are limited to Pay-As-You-Go subscriptions unless a private contract is negotiated, reducing cost predictability.
- Some advanced features like dedicated metadata service and TDE/CMEK require the Premium plan at $0.174/vCPU/h.
- The product launched in 2025, so its ecosystem, community, and third-party integrations are less mature than those of Redshift or Elasticsearch.
- Enterprise on-premises pricing is undisclosed, requiring direct sales contact for cost estimation.
Pricing context
SaaS Standard: $0.134/vCPU/h compute, $0.00005/GB/h storage, $0.000332/GB/h cache. SaaS Premium: $0.174/vCPU/h compute, same storage/cache rates. BYOC: $0.11/vCPU/h compute only. Enterprise: self-managed, pricing upon request.
Getting started with VeloDB Cloud
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Sign up for VeloDB Cloud
Navigate to the VeloDB Cloud website and click the Sign Up button. Provide your email address, create a password, and verify your account via the confirmation email to activate your subscription.
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Connect your data sources
In the VeloDB Cloud console, go to the Data Sources section. Select your source type (e.g., OpenTelemetry, Logstash, Filebeat) and follow the on-screen instructions to configure the connection, including endpoint URL and authentication tokens.
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Configure your database schema
Define your table schema by specifying column names, data types, and indexing options such as Skip Index or Point Query Index. Use the web interface or SQL commands to create tables that match your data structure and query patterns.
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Load sample data and run a query
Upload a sample dataset using the built-in import tool or by sending data from your connected source. Then, execute a simple SELECT query in the query editor to verify that data is ingested and returns results within seconds.
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Set up a Grafana dashboard
In Grafana, add VeloDB Cloud as a data source using the provided connection details. Create a new dashboard, add panels with queries against your VeloDB tables, and configure refresh intervals to monitor real-time analytics.
Frequently Asked Questions
What is VeloDB Cloud?
VeloDB Cloud is a fully managed real-time analytics and search database built on Apache Doris. It provides sub-second analytics, hybrid search, and AI-ready data infrastructure from a single platform, targeting observability, real-time dashboards, and high-concurrency workloads.
How does VeloDB Cloud pricing work?
VeloDB Cloud offers SaaS Pay-As-You-Go plans starting at $0.134/vCPU/h for Standard and $0.174/vCPU/h for Premium, plus separate storage and cache costs. BYOC pricing is $0.11/vCPU/h for compute only. Enterprise on-premises pricing is available upon request.
How does VeloDB Cloud compare to Elasticsearch for log analytics?
In log analytics benchmarks, VeloDB Cloud claims 7x faster query performance than Elasticsearch using only 1/6 the resources. It also achieves real-time data latency of seconds versus minutes for ingestion and queries, making it a more efficient alternative.
What deployment options does VeloDB Cloud offer?
VeloDB Cloud provides SaaS and Bring Your Own Cloud (BYOC) deployment on AWS, Azure, and Google Cloud. It also offers a self-managed Enterprise edition for on-premises or Kubernetes environments, giving organizations flexibility in data residency and control.
What are the main features of VeloDB Cloud?
Key features include a multi-compute shared-data architecture for independent scaling, rich indexing like Skip and Point Query Indexes, real-time data ingestion from OpenTelemetry and Logstash, high concurrency with complex JOINs, and integration with Grafana and Kibana for visualization.
What are the weaknesses of VeloDB Cloud?
SaaS plans are limited to Pay-As-You-Go unless a private contract is negotiated, reducing cost predictability. Some advanced features require the Premium plan. The product launched in 2025, so its ecosystem and community are smaller than those of established competitors like Redshift or Elasticsearch.
Alternatives
How VeloDB Cloud compares
Direct head-to-head against 2 competitors. Picked by 7wData.
VeloDB Cloud
- Pricing
- SaaS Standard: $0.134/vCPU/h compute, $0.00005/GB/h storage, $0.000332/GB/h cache. SaaS Premium: $0.174/vCPU/h compute, same storage/cache rates. BYOC: $0.11/vCPU/h compute only. Enterprise: self-managed, pricing upon request.
- Target
- VeloDB Cloud is a fully managed, real-time analytics and search database built on Apache Doris, the open-source OLAP engine used by over 5,000 enterprises.
- Strength
- Delivers 7x faster query performance than Elasticsearch in log analytics benchmarks, using only 1/6 the resources.
- Watch for
- SaaS plans are limited to Pay-As-You-Go subscriptions unless a private contract is negotiated, reducing cost predictability.
Elasticsearch
- Pricing
- $0.356/vCPU/h (Elastic Cloud, 48 vCPU tier)
- Target
- Log analytics, observability, and search workloads
- Deployment
- SaaS, BYOC, self-managed
- Strength
- Mature ecosystem for log and search use cases
- Watch for
- Higher storage cost and slower write performance vs. VeloDB
ClickHouse Cloud
- Pricing
- $0.10/vCPU/h (compute) + storage and cache costs
- Target
- Real-time analytics, observability, and log storage
- Deployment
- SaaS, BYOC, self-managed
- Strength
- High compression and fast query on large datasets
- Watch for
- Complex tuning for high-concurrency workloads
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