Agentic Index
Dataiku vs Databricks Mosaic AI (2026)
Dataiku and Databricks Mosaic AI both sell enterprises a governed path to production AI agents on corporate data: Dataiku offers a free community edition with paid enterprise editions priced by users and capabilities through sales, its LLM Mesh centralizing model spend controls across providers, while Mosaic AI is the Databricks native framework with agent evaluation and governance on consumption based DBU pricing across clouds. Organizations wanting platform neutrality across data stacks and a visual multi tool environment lean Dataiku; lakehouse committed organizations that want agents inheriting Unity Catalog governance lean Mosaic.
| At a glance | Dataiku | Databricks Mosaic AI |
|---|---|---|
| Category | Multi-agent platform | Multi-agent platform |
| Entry price | Free community edition; paid enterprise editions priced by users and capabilities through sales | Free trial · usage based (DBUs) |
| Free / trial | Free community edition available; enterprise editions and trials through sales | A free trial is available to evaluate the Databricks platform and Mosaic AI before committing to consumption billing. |
| Pricing confidence | public partial | public partial |
| Feature |
D
Dataiku
|
|
|---|---|---|
| Action & orchestration | ||
|
Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
Full / Explicit | Full / Explicit |
|
Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
Full / Explicit | Full / Explicit |
|
Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
Partial | Partial |
| Knowledge & context | ||
|
Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
Full / Explicit | Full / Explicit |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Partial | Full / Explicit |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Full / Explicit | Full / Explicit |
|
Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
Full / Explicit | Full / Explicit |
|
Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
Full / Explicit | Full / Explicit |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
Full / Explicit | Full / Explicit |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
Full / Explicit | Partial |
| Platform extensibility | ||
|
Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
Full / Explicit | Full / Explicit |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
Full / Explicit | Full / Explicit |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
Full / Explicit | Full / Explicit |
| Specialist automation | ||
|
Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
No / Not documented | No / Not documented |
Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing |
D
Dataiku
|
|
|---|---|---|
|
Entry price Lowest public entry point |
Free community edition; paid enterprise editions priced by users and capabilities through sales | Free trial · usage based (DBUs) |
|
Pricing confidence How public the numbers are |
Public — partial | Public — partial |
|
Billing Primary billing axis |
users and platform capabilities | usage (DBUs) |
|
Variable cost Workload / overage exposure |
Medium variable cost | High variable cost |
|
Free tier / trial Try before you buy |
Free tierTrial
|
No free tierTrial
|
|
Buying motion Self-serve vs sales call |
Sales call | Mixed |
Choose Dataiku if
- Platform neutrality across your data estate is strategic.
- The LLM Mesh's centralized model governance appeals to your team.
- Visual tooling for mixed skill teams matters in your organization.
Choose Databricks Mosaic AI if
- Your data gravity is Databricks and agents should inherit its governance.
- DBU consumption pricing through existing commitments eases procurement.
- Built in agent evaluation on the lakehouse is the requirement.