Tools
Dify vs Vectara Platform
Dify or Vectara Platform? Their plans monthly and yearly, the capabilities their makers state, security and latest updates, side by side — read from the makers' own pages.
In inglese
In short
- Both: Choice of models, Self-hosted, API, Builds agents and workflows, Search over your data, Traces and evaluates
- Only Vectara Platform states: Runs models for you
Dify
Dify lets teams build, test, deploy, and monitor AI apps, agents, workflows, and RAG pipelines in the cloud or on private infrastructure.
Plans
Sandbox
Free
- 200 message credits
- 1 Team Workspace
- 1 Team Member
- 5 Apps
- 50 Knowledge Documents
- 50MB Knowledge Data Storage
Professional
- $590 per workspace / year
- 5,000 message credits / month
- 1 Team Workspace
- 3 Team Members
- 50 Apps
- 500 Knowledge Documents
- 5GB Knowledge Data Storage
Enterprise
Price on request
- Enterprise-grade Scalable Deployment Solutions
- Commercial License Authorization
- Multiple Workspaces & Enterprise Management
- SSO
- Advanced Security & Controls
- Professional Technical Support
Prices checked 2026-09-25 by web search.
Capabilities
- Choice of models — “Credits are provided to help you easily try out different models from OpenAI, Anthropic, Gemini, xAI, Tongyi in Dify.” source
- Self-hosted — “Self-host or run in your VPC.” source
- API — “Publish Dify apps as hosted experiences, API endpoints, embeds, or MCP-compatible tools.” source
- Builds agents and workflows — “Build an agent by chatting or configuring it manually.” source
- Search over your data — “Prepare searchable knowledge bases” source
- Traces and evaluates — “Use logs, feedback, annotations, latency, and usage data to understand what happened and improve the app over time.” source
Latest updates
- v1.17.0 (v1.17.0)
Adds an E2B sandbox backend, build-time home snapshots, and skill management.
- v1.16.0 (v1.16.0)
Launches Dify Agent (Beta), with a UI builder for agents that run in a Linux sandbox.
Vectara Platform
Enterprise platform for building, deploying, and governing AI agents over business data.
Plans
30 Day Free Trial
Free
- 30 days to try Vectara
- 10,000 credits included
- All features included for 30 days
SaaS
- Starting at $100K/ year
- 1 SaaS Deployment
- 10,000,000 credits/year included with base platform package purchase
VPC
- Starting at $250K/ year
- 1 VPC Deployment (Any VPC)
- 100,000,000 credits/year included with base platform package purchase
On-prem
- Starting at $500K/ year
- 1 On-Premise Deployment
- 100,000,000 credits/year included with base platform package purchase
Prices checked 2026-09-24 by web search.
Capabilities
- Choice of models — “Vectara lets you apply the retrieval LLM that best fits your use case.” source
- Self-hosted — “Vectara is available as a service on-premises, within your VPC, or via SaaS.” source
- API — “One easy-to-use API to enable 100s of use cases” source
- Runs models for you — “Vectara's own RAG-optimized Generative LLM” source
- Builds agents and workflows — “Vectara provides the industry's highest accuracy and lowest hallucination rates.” source
- Search over your data — “Vectara employs agentic extraction from documents, neural and lexical search, knowledge re-ranking, and customized generation.” source
- Traces and evaluates — “Vectara flips the script, providing granular observability and proactive Guardian Agents.” source
Latest updates
- LLM Token Quotas and Per-Agent Quotas
Cap input and output tokens per minute, UTC day, and UTC month for an LLM or agent.
- Confluence Ingests Attachments and Embedded Images
A Confluence pipeline source ingests page attachments as records and inlines images embedded in page bodies.
- Ingest Multiple S3 Prefixes in One Pipeline
An S3 pipeline source scopes ingestion with prefixes, a list of up to 100 key prefixes.