Agentic Index
DBOS vs Kestra (2026)
DBOS and Kestra both make agent and data workflows durable, from different abstractions: DBOS is a durable execution library, open source and free, embedding checkpointed reliability directly into your application code, with Conductor free in development and paid Pro and Enterprise support quoted through sales plus a serverless DBOS Cloud, while Kestra is a workflow orchestration platform, open source edition free forever self hosted, with an Enterprise Edition license quoted by organization size and a managed Kestra Cloud rolling out. Library in your code versus platform above your code is the entire decision.
| At a glance | DBOS | Kestra |
|---|---|---|
| Category | Agent infrastructure | Agent infrastructure |
| Entry price | Free open source library; paid Pro, premium, and Enterprise support tiers are quoted through sales with no retrievable public rates | Free open source edition; Enterprise Edition license and Kestra Cloud are quoted through sales with no published rates |
| Free / trial | The DBOS Transact library is free and open source, and Conductor is free in test and development mode | The open source edition is free forever, self hosted on Docker or Kubernetes |
| Pricing confidence | contact only | contact only |
| Feature |
D
DBOS
|
K
Kestra
|
|---|---|---|
| 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. |
Partial | 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 | Full / Explicit |
| 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. |
No / Not documented | Partial |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Full / Explicit | Full / Explicit |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Partial | 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. |
Partial | Full / Explicit |
| 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. |
Partial | 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. |
Partial | Partial |
| 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
DBOS
|
K
Kestra
|
|---|---|---|
|
Entry price Lowest public entry point |
Free open source library; paid Pro, premium, and Enterprise support tiers are quoted through sales with no retrievable public rates | Free open source edition; Enterprise Edition license and Kestra Cloud are quoted through sales with no published rates |
|
Pricing confidence How public the numbers are |
Contact only | Contact only |
|
Billing Primary billing axis |
support and tooling tiers on top of a free open source core, plus usage based serverless compute on DBOS Cloud | license fees on top of a free open source core, scoped by organization size and features, plus usage based pricing on the managed Kestra Cloud |
|
Variable cost Workload / overage exposure |
Medium variable cost | Medium variable cost |
|
Free tier / trial Try before you buy |
Free tierTrial
|
Free tier
|
|
Buying motion Self-serve vs sales call |
Mixed | Mixed |
Choose DBOS if
- Durability belongs inside your application code, not an external orchestrator.
- A free open source library with optional paid support fits your model.
- Serverless cloud execution appeals for elastic workloads.
Choose Kestra if
- Declarative orchestration across teams and systems is the actual need.
- A visible platform with governance features suits your organization.
- The free self hosted edition covers you until enterprise features matter.