JamJet vs Temporal
for AI Agents
Temporal is the gold standard for durable execution. It earned that reputation with a $5B valuation, 1,000+ enterprise customers, and 9.1 trillion lifetime actions. It is excellent at what it does.
But durable execution alone doesn't make AI agents production-safe. Agents need policy enforcement, audit trails, human approval, cost governance, and memory — none of which Temporal provides natively. That's where JamJet comes in.
The quick version
Choose Temporal when
- You already use Temporal for non-AI workflows
- You need battle-tested durability at massive scale
- You want the largest ecosystem and enterprise support
- You're building general distributed workflows, not just AI agents
- You have a team comfortable with Temporal's programming model
Choose JamJet when
- Your agents need policy controls and governance
- You need audit trails for compliance (EU AI Act, financial regs)
- You need human-in-the-loop as a first-class primitive
- You want agent memory built into the runtime
- You need cost governance at the runtime level
- You want MCP/A2A protocol-native integration
Feature comparison
| Capability | Temporal | JamJet |
|---|---|---|
| Durable execution | Best-in-class. Event-sourced, battle-tested at massive scale. The industry standard. | Event-sourced with checkpoint snapshots. Proven in tests and examples, not yet at Temporal scale. |
| Policy engine | None. No way to block tool calls, enforce model restrictions, or scope agent permissions at the runtime level. | 4-level hierarchy (global → tenant → workflow → node). Glob-pattern tool blocking, model allowlists, delegation scoping. 76 tests. |
| Audit trails | Workflow history only. Not separate, not retention-aware, not designed for compliance export. | Separate append-only audit log. Per-entry retention policies. Actor enrichment. Designed for compliance. |
| Human-in-the-loop | Via signals — functional but manual. Not a first-class workflow primitive. Requires custom handling. | First-class pause/resume/approval nodes. Durable across restarts. Built into workflow IR. |
| Agent memory | None. Bring your own. | Engram: temporal knowledge graph, fact extraction, conflict detection, hybrid retrieval, consolidation. 11 MCP tools. |
| Cost governance | None. No per-agent or per-workflow cost tracking or enforcement. | Per-workflow and per-agent token/dollar budgets. Runtime-enforced. Automatic escalation. |
| MCP support | None natively. You build it. | Client + server. Full spec. 11 Engram tools. MCP Registry listed. |
| A2A protocol | None. | Client + server. Streaming, failure handling, agent discovery. |
| Multi-tenant isolation | Namespace-based (Temporal Cloud). Functional but limited scoping. | Row-level partitioning. Per-tenant policies, resource limits, cost caps. |
| Evaluation / testing | None. Separate tool needed. | Built-in eval harness. LLM judge, assertions, cost scoring. CI exit codes on regression. |
| PII redaction | None. | Built-in. Runtime-enforced. |
| OAuth delegation | None. | RFC 8693 token exchange. Scope narrowing. Per-step scoping. |
| Programming model | Workflows + Activities + Signals + Queries. Powerful but steep learning curve. | Progressive: @task (3 lines) → Agent → Workflow. Python, Java, YAML. |
| Language SDKs | Python, TypeScript, Go, Java, .NET. Best-in-class breadth. | Python, Java. Go planned. Fewer languages but deeper agent-native features per SDK. |
| Runtime language | Go core | Rust core + Java native runtime |
| Community | ~12K GitHub stars. 1,000+ customers. Large Slack community. Enterprise proven. | Early-stage. Small community. Production examples but few known production deployments. |
| Pricing | Self-hosted: free. Cloud: $100/mo minimum + $50/million actions + storage fees. Costs can scale unpredictably. | Fully open source. No commercial offering yet. Self-hosted only. |
| Maturity | Proven at scale. Netflix, Snap, DoorDash, Box. $5B valuation. 431 employees. | Pre-revenue. Solo founder. Strong engineering, unproven at scale. |
Where Temporal excels
Temporal's durability model is the best in the industry. If your primary concern is "my distributed workflows must never lose progress," Temporal is the safe, proven choice. It handles:
- Massive-scale durable execution (trillions of actions)
- Complex workflow patterns (signals, queries, child workflows, continue-as-new)
- Multi-language support (5 SDKs, all production-grade)
- Enterprise support with SLAs and managed cloud
- Active integrations with OpenAI Agents SDK, Vercel AI SDK, Pydantic AI
Temporal is also building AI agent integrations rapidly. Their activity_as_tool helper for OpenAI Agents SDK shows they're taking this space seriously.
Where JamJet goes further
JamJet's thesis is that durable execution alone isn't enough for AI agents in production. Agents create unique challenges:
- Agents call tools autonomously — you need policy enforcement to prevent unauthorized actions, not just retry logic
- Agents make decisions with real consequences — you need audit trails that are separate from execution history and designed for compliance
- Agents need human oversight — you need first-class pause/resume/approval, not manual signal handling
- Agents accumulate context — you need governed memory with conflict detection, not just a key-value store
- Agents spend money (LLM calls) — you need runtime-enforced cost budgets, not just monitoring
- Agents need to interoperate — you need MCP/A2A protocol support, not custom integration for each tool
These are not features you can easily add to Temporal. They require agent-native abstractions built into the runtime from the ground up.
Can you use both?
Technically, yes — but it would be unusual. Both are execution runtimes. Using both would mean running Temporal for durability and JamJet for governance, which adds operational complexity.
More practically: if you already use Temporal for non-AI workflows and want to add AI agent governance, JamJet's MCP Gateway (coming soon) can sit between your agent and its tools to add policy enforcement and audit trails without replacing Temporal.
If you're starting fresh with AI agents, JamJet gives you durability and governance in one runtime.
The honest tradeoff
Temporal gives you
Battle-tested durability, massive scale, enterprise support, broad language coverage, proven at thousands of companies. You sacrifice agent-native governance — you'll build policy, audit, HITL, memory, and cost controls yourself.
JamJet gives you
Agent-native governance, durability, memory, and protocol support in one open-source runtime. You sacrifice scale confidence, enterprise support, language breadth, and the comfort of a $5B-backed platform. JamJet is early-stage.
Ready to try JamJet?
Start with a 60-second quickstart. Add governance controls as you need them.