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Qdrant vs Stack AI

A direct comparison using the real catalog fields currently available for both products.

Last updated July 24, 2026

Tool A

Tool B

Qdrant

Stack AI

Overview

Rating

—

Qdrant best for

Production RAG applications

High-throughput vector search

Multi-modal search

Hybrid search pipelines

Performance-sensitive AI applications

Stack AI best for

Document intelligence pipelines

Internal AI tool creation

Data extraction automation

Enterprise AI workflow

Pricing

Starting price

FreeBest value

$199/mo

Pricing model

Open Source

Freemium

Free plan

Yes

Free trial

Pricing notes

Open source self-hosted free. Qdrant Cloud free tier (1GB cluster). Managed cloud from $0.014/hour. Enterprise cloud custom pricing.

Free plan with limited runs. Starter $199/month. Teams $799/month. Enterprise custom.

Capabilities

Best for

Production RAG applicationsHigh-throughput vector searchMulti-modal searchHybrid search pipelinesPerformance-sensitive AI applications

Document intelligence pipelinesInternal AI tool creationData extraction automationEnterprise AI workflow

Target audience

ML engineersData engineersBackend developersAI startup teamsPerformance-focused teams

Business analystsOperations teamsLegal and compliance teamsEnterprise AI buildersNon-technical teams

AI type

ML Platform

LLM Application Framework

Modalities

TextData

TextDocumentData

Technical

Model provider

Agnostic

OpenAIAnthropicAzure OpenAIAgnostic

Model names

—

API available

✓

Open source

✓

Deployment

Open SourceSaaSSelf-hosted

SaaSPrivate deployment

Platforms

WebPythonTypeScript

Web

Integrations

LangChainLlamaIndexOpenAIAnthropicHugging FaceAny embedding model

SalesforceHubSpotSharePointZapierAll major LLM providersREST API

Team collaboration

✓

Trust & security

Security

Open source self-hosted provides complete data control. Qdrant Cloud: review data handling policy. Enterprise cloud includes data handling agreements.

SOC 2 Type II. GDPR compliant. SSO and audit logs on enterprise plans. Private deployment for data sovereignty.

Privacy notes

Self-hosted Qdrant provides complete data control. Qdrant Cloud processes data on Qdrant managed infrastructure.

Review Stack AI data handling policy. Enterprise private deployment keeps data within customer infrastructure.

Verdict

Pros

Rust implementation provides strong performance for high-throughput production workloads
Sparse vector support enables native hybrid search without separate keyword infrastructure
Advanced filtering with minimal performance impact on vector search queries
Named vectors support multiple embedding types per data point for multi-modal search

No-code visual builder accessible to enterprise business teams without ML engineering
Document processing pipelines strong for legal, healthcare, and financial services
Enterprise governance features (SSO, audit logs, RBAC) meet corporate requirements
Private deployment option for data sovereignty requirements

Cons

More setup complexity than managed services like Pinecone
Smaller community and fewer learning resources than Weaviate or Pinecone
Enterprise support requires cloud or custom deployment engagement

$199/month Starter plan is expensive relative to open source alternatives like Flowise
Most value in document processing rather than general AI application building
Less flexibility than coded frameworks for highly custom AI logic