Actian Launches VectorAI DB with 22x Faster Vector Search for Production AI Anywhere, Including the Edge
Actian VectorAI DB gives developers data ownership across edge, on-premises, and cloud environments
Gartner® predicts "33% of enterprise software applications will include agentic AI by 2028, up from less than 1% in 2024."2 At the core of these applications are vector databases, which enable AI systems to find and retrieve information based on semantic meaning and context, not just exact keywords.
Most vector databases were built for cloud-first workloads that assume always-on connectivity and distributed infrastructure. These databases do not always meet latency and data residency requirements, especially as AI use cases progress from retrieval-augmented generation (RAG) and agentic AI toward autonomous systems and robotics. As data residency and compliance requirements tighten globally, organizations need AI infrastructure that runs reliably outside the cloud and keeps sensitive data under organizational control.
Actian VectorAI DB Overview
Actian VectorAI DB handles real-world query volumes without depending on cloud resources to scale. The database delivers local, low-latency vector search across embedded systems, edge devices (including resource-constrained hardware such as NVIDIA Jetson and Raspberry Pi devices), on-premises environments, and cloud deployments. Developers build once and deploy using the same architecture and APIs, retaining data ownership with consistent, predictable performance across every environment without re-architecting as applications scale. The database embeds multimodal data including text, images, audio, video, and documents.
"Too often, vector search requires data to move outside governed systems, creating blind spots in security, compliance, and policy enforcement" said
Built for Regulated Industries
Actian VectorAI DB is purpose-built for industries where data sovereignty requirements are most stringent.
- Manufacturers operating production environments that need AI embedded directly in machines and sensors.
- Healthcare organizations managing sensitive patient data across hospitals, clinics, and research environments.
- Financial institutions running fraud detection, risk analysis, and compliance monitoring across hybrid environments.
- Government agencies where sensitive data must remain within classified environments and under full organizational control.
The database includes AES-256 encryption and support for customer-managed API keys. It supports deployment configurations aligned with HIPAA, GDPR, ISO 27001, and SOC 2 Type II for customer compliance requirements.
Availability
Actian VectorAI DB is available now. A 30-day free trial and a free Community Edition are available for developers. To learn more,
Actian VectorAI DB Quick Reference
- Category: On-premises vector database
- Performance: 745.2 queries/second on 10M vectors at 768 dimensions – more than 22X faster than leading open-source alternative1
- Compliance-ready configurations: Supports customer-built applications requiring HIPAA, GDPR, ISO 27001, SOC 2 Type II compliance
- Security: AES-256 encryption, customer-managed API keys
- Supported programming languages and SDKs: Python, JavaScript
- Supported frameworks: LangChain, LlamaIndex, Hugging Face
- Availability: Free 30-day trial; Community Edition
About Actian
Actian empowers enterprises to confidently manage and govern data at scale. Actian data management and data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data and AI division of HCLSoftware, at actian.com.
1 Initial VectorDBBench tests show Actian VectorAI DB delivering a 22x QPS advantage over open-source vector databases Milvus (2026-04-09T08:19:17.456044) and Qdrant Local at 10M vectors across 768 dimensions on identical self-hosted hardware. Actian VectorAI DB retained 72% of its throughput (QPS) when scaling from 1M to 10M vectors, while competitors' throughput decreased to ~12%. Testing conducted by Actian,
2 Gartner Press Release, "Gartner Predicts Over 40% of Agentic AI Projects Will Be Canceled by End of 2027,"
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SOURCE Actian
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