Actian VectorAI DB vs Voyage AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-09
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At a glance

DimensionActian VectorAI DBVoyage AI
PricingContact sales (no free tier)Contact sales (usage-based, no free tier)
DeploymentEdge, on-prem, hybrid, cloudCloud API only
Core CapabilityVector database (store & search)Embedding & reranker models
Best ForEdge AI, IoT, on-prem complianceEnterprise RAG, domain-specific retrieval
Key Metric13ms p99 latency, 99% recall at 10M32K token context, low-dim embeddings
ComplianceHIPAA, GDPR on-premSOC 2, HIPAA (cloud)
Try Actian VectorAI DBTry Voyage AI
Actian VectorAI DB
Actian VectorAI DB

Local-first vector database for AI agent memory, RAG, and air-gapped edge deployments.

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Voyage AI
Voyage AI

Voyage AI delivers domain-tuned embedding models and rerankers for high-precision RAG retrieval

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Pricing
Freemium
Paid
Plans
$0/mo
$417/mo
$1,250/mo
Custom
Consumption-based pricing (rates not published on page)
Popularity
1 views
7.4k views
Skill Level
Advanced
Intermediate
API Available
Platforms
DesktopAPICLI
WebAPI
Categories
🗄️ Vector Databases & Retrieval
🗄️ Vector Databases & Retrieval
Features
Local vector search with sub-15ms query latency
745 QPS on 10M vectors at 768 dimensions (vendor-reported)
13ms p99 latency at 99% recall on self-hosted hardware (vendor-reported)
Approximate nearest neighbor (ANN) indexing
Metadata filtering on vector queries
Full CRUD operations on vector embeddings
Persistent agent memory that survives sessions
Offline operation with sync-on-connect
Deploys on NVIDIA Jetson and Raspberry Pi
Air-gapped environment support for defense, aerospace, and pharma
Single Docker container running identically on laptop, edge, or Kubernetes
Python SDK (pip install actian-vectorai), JavaScript SDK, and REST API
Bring-your-own embedding model
MCP server support for agent frameworks
Native Prometheus metrics for existing Grafana dashboards
General-purpose embedding models including voyage-3.5 and voyage-3.5 lite
Domain-specific embedding models optimized for finance, legal, and code
Company-specific fine-tuned embedding models on proprietary data
Voyage 4 model series for improved retrieval quality
voyage-multimodal-3.5 embeds images and text in one retrieval pipeline
Low-dimensional embeddings (3x-8x shorter vectors) cut storage and search costs
32K-token long-context support for embedding long documents
rerank-2.5 and rerank-2.5-lite add instruction-following to ranking
voyage-context-3 keeps chunk-level detail with global document context
Batch API for large-scale embedding workloads
4x smaller model with faster inference and superior accuracy
2x cheaper inference with superior accuracy
Plug-and-play with any vectorDB and any LLM
SOC 2 and HIPAA compliance
Deploy on major clouds, in-VPC customer tenants, or on-premise with model licensing
Integrations
CrewAI
LangChain
LangGraph
LlamaIndex
Prometheus
Grafana
Actian Data Intelligence Platform
Actian Data Observability

What real users say: Actian VectorAI DB vs Voyage AI

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Actian VectorAI DB

31 mentions across 3 sources · 67% positive (averaged across 3 sources)

YouTube, Product Hunt, Bluesky

What users praise

  • • Portable design works offline on Raspberry Pi and Jetson.
  • • Sub-15ms latency with 99% recall at 10M vectors claimed.
  • • HIPAA/GDPR-compliant on-prem deployment for regulated industries.
  • • Consistent architecture from prototype to production avoids rewrites.

What frustrates them

  • • Pricing is opaque; no free tier or self-serve option exists.
  • • Very little real-world community validation or case studies.
  • • Storage footprint vs competitors at scale remains undisclosed.
  • • Write-heavy workload performance not benchmarked publicly.

Researched Jul 26, 2026

Voyage AI

64 mentions across 6 sources · 54% positive — mixed (weighted across 6 sources)

Hacker News, YouTube, App Store, Stack Overflow, GitHub, Lemmy

What users praise

  • • Domain-tuned legal and finance embedders cut irrelevant docs by 25% in the Harvey case
  • • 3x-8x shorter vectors materially cut vectorDB storage and search costs
  • • rerank-2.5 instruction following lets you steer ranking behavior in plain language
  • • voyage-multimodal-3.5 handles images and text in a single retrieval pipeline

What frustrates them

  • • Default terms train on API customer data with a perpetual, irrevocable license grant
  • • Per-million-token pricing gets expensive fast for high-frequency agent RAG pipelines
  • • A small Jina model reportedly beat Voyage on retrieval in one public benchmark
  • • Open-source ecosystem still thin — Python library has only 114 GitHub stars

Researched Oct 7, 2026

Who should pick which

  • Edge AI Engineer
    Pick: Actian VectorAI DB

    Needs local vector search on devices like Raspberry Pi or NVIDIA Jetson; Actian supports edge deployment with offline operation and sub-15ms latency.

  • Legal Document RAG Developer
    Pick: Voyage AI

    Requires domain-specific legal embedding model and long-context support (32K tokens) for accurate retrieval; Voyage offers both.

  • Healthcare On-Prem Compliance Team
    Pick: Actian VectorAI DB

    Needs HIPAA-compliant on-prem database for clinical search; Actian provides full data locality control.

  • Enterprise RAG Architect
    Pick: Voyage AI

    Wants best-in-class embedding/reranker models for general RAG with cost-efficient storage; Voyage's low-dim vectors reduce vector DB costs.

  • Manufacturing IIoT Engineer
    Pick: Actian VectorAI DB

    Needs offline vector search in disconnected factory environments for predictive maintenance; Actian's sync-on-connect fits.

Frequently Asked Questions

Can I use Actian VectorAI DB with Voyage AI models?

Yes, they are complementary. Voyage AI generates embeddings that Actian can store and search, enhancing RAG pipelines with local or edge deployment.

Which product has better latency for real-time search?

Actian VectorAI DB claims 13ms p99 latency for local vector search, making it ideal for real-time edge applications. Voyage AI's models have inference latency but that depends on API call overhead.

Do either offer a free tier or open-source version?

No, both are commercial products with contact-based pricing. Neither offers free tiers or open-source alternatives.

Which is better for cloud-native RAG?

Voyage AI (embedding API) is cloud-native; Actian is not primarily cloud-native but can be deployed in the cloud alongside Voyage.

Can I fine-tune models in Voyage AI?

Yes, Voyage AI offers company-specific fine-tuned models (custom).

Does Actian support offline operation?

Yes, Actian supports offline operation with sync-on-connect capability for edge devices.

What integrations does Voyage AI have?

Voyage AI integrates with any vector database or LLM via API; no specific pre-built integrations listed.

Which product is HIPAA compliant?

Both claim HIPAA compliance: Actian via on-prem deployment, Voyage AI via cloud SOC 2/HIPAA.

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Explore each tool further

Actian VectorAI DB
View Actian VectorAI DB reviewActian VectorAI DB alternatives
Voyage AI
View Voyage AI reviewVoyage AI alternatives

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Last reviewed: July 3, 2026