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ProductArena

Durable Execution Engines Arena

Durable Execution Engines — procurement report

ProductArena · rankings as of 2026-09-16 · evidence as of 2026-09-16 · 6 products · 53 judged requirements · 318 judged cells

Methodology: Every product is judged against a shared taxonomy of user stories using cited evidence — hands-on probes > repository code > independent community sources > vendor claims — never opinion. Full writeup: https://ultrametric.ai/productarena/methodology

Leaderboard

#ProductPA ScoreCoverage scoreApplicable cellsConfidence
1Temporal42.749.649/53B
2DBOS40.547.751/53B
3Trigger.dev39.443.853/53A
4Inngest38.550.152/53B
5Hatchet37.432.250/53B
6Restate33.443.451/53C

PA Score = agent-readiness blend (see methodology). Coverage score = weighted share of judged requirements met. Confidence = how much of the score rests on tested vs claimed evidence (A–D).

Uncertainty note

The current #1/#2 gap in this arena is not close enough to qualify for the multi-judge uncertainty pass (or the pass has not covered it yet) — no extra caveat applies beyond the per-product confidence grades above.

Buyer checklist (RFP)

The arena's 53 judged user stories as requirements, grouped by theme. Priorities mirror the story weights our scoring uses (3 = must-have, 2 = should-have, 1 = nice-to-have). Interactive version with per-requirement verdicts for the top products: /arena/durable-workflows/checklist

Agent workloads — stories about agent workloads in this arenaAgent workloads

Stories about agent workloads in this arena

  • agent builderI run LLM agent loops as durable workflows — model and tool calls as checkpointed, retried steps that survive crashes mid-runmust-have
  • agent builderFirst-party integrations wrap my AI stack — AI SDKs, agent frameworks, model providers — so agent steps get durability without glue codeshould-have
  • ai-native userI stream live progress — step updates or model tokens — from a running workflow into my frontend as it executesshould-have

Agenticness — how well agents can access and operate the productAgenticness

How well agents can access and operate the product

  • ai-native userPlug MCP servers into this product so it can use their toolsmust-have
  • ai-native userConnect an agent via an official MCP servermust-have
  • ai-native userDrive the product through a documented public APImust-have
  • ai-native userDelegate tasks to a built-in AI assistant inside the productmust-have
  • ai-native userPoint an agent at llms.txt or agent-oriented docsshould-have
  • ai-native userRun the product headlessly / in CI for automationshould-have
  • ai-native userUse an official CLIshould-have
  • ai-native userIssue scoped/least-privilege API credentials for an agentshould-have
  • ai-native userBuild against official SDKsshould-have
  • ai-native userSubscribe to events via webhooksshould-have
  • ai-native userGet AI-generated insights and suggestions from my data inside the productshould-have
  • ai-native userSet up automations that run autonomously in the backgroundshould-have
  • ai-native userOperate the product with natural-language commandsshould-have
  • ai-native userExplore an interactive API reference with runnable examplesshould-have
  • ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)should-have
  • ai-native userRely on versioned APIs with a documented deprecation policyshould-have
  • ai-native userTest against a sandbox environment without touching production datanice-to-have

Automation depth — how much of the product can run unattendedAutomation depth

How much of the product can run unattended

  • ai-native userDefine rules that trigger actions automatically on eventsmust-have
  • ai-native userPerform bulk operations across many items at onceshould-have
  • ai-native userSchedule recurring jobs or workflowsshould-have
  • ai-native userVersion, review, and roll back my automationsnice-to-have

Developer experience — stories about developer experience in this arenaDeveloper experience

Stories about developer experience in this arena

  • backend developerOne command runs the whole engine locally, and testing utilities let me unit-test workflows with time skipping and mocked stepsshould-have

Human in the loop — stories about human in the loop in this arenaHuman in the loop

Stories about human in the loop in this arena

  • backend developerA workflow pauses for human approval or input for hours or days and resumes the moment the response arrivesmust-have
  • backend developerI send signals, events, or messages into a specific running workflow from outside — an API call, webhook, or another workflowshould-have

Observability debugging — stories about observability debugging in this arenaObservability debugging

Stories about observability debugging in this arena

  • platform engineerEvery run has a step-by-step timeline — inputs, outputs, retries, and errors per step — in a dashboard my team can search and filtermust-have
  • platform engineerI replay or rerun a failed workflow from its recorded history — optionally from a specific step — to debug and recovershould-have
  • platform engineerFailure rates, latencies, and queue depths export to my observability stack, and alerts fire when workflows misbehavenice-to-have

Openness — open source, data portability, and self-hosting storiesOpenness

Open source, data portability, and self-hosting stories

  • ai-native userExport all of my data in open formats and leavemust-have
  • ai-native userSelf-host the core productmust-have
  • ai-native userDo everything through the API that I can do in the UIshould-have
  • ai-native userRead the product's source under an open licenseshould-have

Operations hosting — stories about operations hosting in this arenaOperations hosting

Stories about operations hosting in this arena

  • platform engineerI run workers in my own infrastructure while the vendor manages the orchestration control plane — code and data stay inside my networkshould-have

Performance scale — stories about performance scale in this arenaPerformance scale

Stories about performance scale in this arena

  • platform engineerI cap concurrency and set rate limits per workflow, per key, or per tenant so one hot customer can't starve the restshould-have
  • platform engineerThroughput scales by adding workers — the platform load-balances tasks across the fleet and tolerates worker lossshould-have
  • platform engineerI assign priorities to runs and get fair scheduling across tenants instead of a single FIFO queuenice-to-have

Privacy posture — data-handling and privacy storiesPrivacy posture

Data-handling and privacy stories

  • ai-native userPrevent my data from being used to train AI modelsmust-have
  • ai-native userChoose where my data is stored (region/residency)should-have
  • ai-native userControl data retention and deletionshould-have
  • ai-native userOpt out of telemetry and usage trackingshould-have

Reliability recovery — stories about reliability recovery in this arenaReliability recovery

Stories about reliability recovery in this arena

  • backend developerA workflow interrupted by a process crash, deploy, or infrastructure failure resumes from its last completed step with state intactmust-have
  • backend developerEvery step retries automatically with configurable backoff, timeouts, and failure policies — no try/catch scaffoldingmust-have
  • backend developerIdempotency keys and exactly-once step semantics stop duplicate triggers from double-charging or double-sendingshould-have
  • backend developerA workflow can sleep or wait for days to months without holding a server, connection, or billable computeshould-have

Triggers scheduling — stories about triggers scheduling in this arenaTriggers scheduling

Stories about triggers scheduling in this arena

  • backend developerEvents from my app, webhooks, or queues trigger workflows declaratively, and one event can fan out to many functionsshould-have
  • backend developerI schedule workflows on cron expressions with overlap policies, pause/resume, and visibility into upcoming runsshould-have
  • backend developerI debounce, batch, or delay triggers so noisy event streams collapse into the runs I actually wantnice-to-have

Versioning deployment — stories about versioning deployment in this arenaVersioning deployment

Stories about versioning deployment in this arena

  • platform engineerI deploy new workflow code while in-flight runs finish on the version they started with — versioning without breaking determinismmust-have

Workflow authoring — stories about workflow authoring in this arenaWorkflow authoring

Stories about workflow authoring in this arena

  • backend developerI write workflows as ordinary code in my language — steps with automatic checkpointing — not YAML or a proprietary DSLmust-have
  • backend developerI compose workflows from parallel steps, fan-out/fan-in over dynamic batches, and child workflows without hand-rolling coordinationshould-have
  • backend developerI author workflows in the language my team already uses — TypeScript, Python, Go, or more — with real feature parity across SDKsshould-have

Appendix: recorded probes

Hands-on probe recordings — transcripts/videos a human can replay, the strongest evidence tier. Watch them at https://ultrametric.ai/productarena/proofs

  • DBOSuvx --from dbos dbos --help | head -12terminal · recorded 2026-09-10 · exit 0
  • DBOScurl -s https://cloud.dbos.dev/conductor/v2/openapi.json | head -c 400terminal · recorded 2026-09-10 · exit 0
  • DBOSecho '<jsonrpc initialize>' | uvx dbos-mcpterminal · recorded 2026-09-10 · exit 0
  • DBOScurl -s https://docs.dbos.dev/llms.txt | head -6terminal · recorded 2026-09-10 · exit 0
  • DBOScurl -sL https://docs.dbos.dev/architecture.md | head -8terminal · recorded 2026-09-10 · exit 0
  • Hatchetcurl -si https://cloud.onhatchet.run/api/v1/tenants | head -10terminal · recorded 2026-09-10 · exit 0
  • Hatchetcurl -fsSL https://install.hatchet.run/install.sh | head -8terminal · recorded 2026-09-10 · exit 0
  • Hatchetcurl -s https://docs.hatchet.run/llms.txt | head -6terminal · recorded 2026-09-10 · exit 0
  • Hatchetcurl -sL https://docs.hatchet.run/cookbooks/hatchet-and-mcp.md | head -8terminal · recorded 2026-09-10 · exit 0
  • Hatchetuvx --from hatchet-sdk python -c 'import importlib.metadata; print("hatchet-sdk", importlib.metadata.version("hatchet-sdk"))'terminal · recorded 2026-09-10 · exit 0
  • Inngestcurl -si https://api.inngest.com/v1/eventsterminal · recorded 2026-09-10 · exit 0
  • Inngestnpx -y inngest-cli@latest --versionterminal · recorded 2026-09-10 · exit 0
  • Inngestcurl -si -X POST https://api.inngest.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'terminal · recorded 2026-09-10 · exit 0
  • Inngestcurl -sL https://www.inngest.com/docs-markdown/learn/how-functions-are-executed | head -8terminal · recorded 2026-09-10 · exit 0
  • Inngestcurl -s https://www.inngest.com/llms.txt | head -6terminal · recorded 2026-09-10 · exit 0
  • Restatenpx -y @restatedev/restate --versionterminal · recorded 2026-09-10 · exit 0
  • Restatecurl -s -X POST https://docs.restate.dev/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # FULL keyless handshake, no auth wallterminal · recorded 2026-09-10 · exit 0
  • Restatecurl -s https://docs.restate.dev/llms.txt | head -6terminal · recorded 2026-09-10 · exit 0
  • Restatecurl -s https://docs.restate.dev/hosting/overview.md | head -8terminal · recorded 2026-09-10 · exit 0
  • Temporaltemporal --versionterminal · recorded 2026-09-10 · exit 0
  • Temporalcurl -si -X POST https://temporal.mcp.kapa.ai -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # the docs MCP advertised in Temporal's own llms.txtterminal · recorded 2026-09-10 · exit 0
  • Temporalcurl -s https://docs.temporal.io/llms.txt | head -6terminal · recorded 2026-09-10 · exit 0
  • Temporalcurl -sL https://docs.temporal.io/workflows.md | head -8terminal · recorded 2026-09-10 · exit 0
  • Trigger.devcurl -si https://api.trigger.dev/api/v1/projectsterminal · recorded 2026-09-10 · exit 0
  • Trigger.devnpx -y trigger.dev@latest --versionterminal · recorded 2026-09-10 · exit 0
  • Trigger.devecho '<jsonrpc initialize>' | npx -y trigger.dev@latest mcpterminal · recorded 2026-09-10 · exit 0
  • Trigger.devcurl -s https://trigger.dev/docs/llms.txt | head -6terminal · recorded 2026-09-10 · exit 0
  • Trigger.devcurl -sL https://trigger.dev/docs/how-it-works.md | head -8terminal · recorded 2026-09-10 · exit 0

Cite as: ProductArena by Ultrametric Inc, Durable Execution Engines arena, rankings as of 2026-09-16 — https://ultrametric.ai/productarena/arena/durable-workflows

License: © 2026 Ultrametric Inc. Brief quotation of individual verdicts, scores, or evidence excerpts is permitted with attribution to "ProductArena by Ultrametric Inc (ultrametric.ai/productarena)", as is use of the data to evaluate, contest, or contribute corrections. Bulk copying, redistribution, or use to build competing datasets requires prior written permission (see DATA-LICENSE in the repository).

No liability: rankings, verdicts, and scores are research outputs derived from the cited evidence at a point in time, provided "as is", without warranties. Ultrametric Inc accepts no responsibility for procurement, purchasing, or other decisions made in reliance on them — verify against the cited evidence before acting (https://ultrametric.ai/productarena/terms).