For developers building GTM automations, Upstash QStash is a serverless message queue and HTTP cron service that schedules, queues, and retries HTTP requests so teams don't have to run their own queue infrastructure.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Upstash QStash is working to become the serverless delivery layer for background jobs, scheduled HTTP calls, and durable agent workflows. Its standalone GTM footprint is still early and quiet, and practitioner discussion has not yet settled into recurring themes. The clearer position comes from the product’s role inside the broader Upstash platform: developers hand off messages or API calls, and QStash manages scheduling, retries, callbacks, rate limits, and delivery. That places it behind automations that need dependable asynchronous execution without a separately operated queue or worker fleet.
Zapier, Supabase, GitBook, ClickFunnels, Branch, Dub, Navattic, Humata, OpenArt, Paul Smith
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Business Profile
QStash is a product within Upstash, an independent developer infrastructure company founded in 2020 with 23 employees and $11.9 million in funding. Upstash began with serverless Redis and expanded QStash as the third product in its platform, extending the same managed, usage-based approach into messaging and scheduling. QStash reached general availability in 2025 with production support and monitoring options. Customer references include Zapier, Supabase, GitBook, ClickFunnels, and Branch, showing adoption among software products that depend on reliable background execution.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
QStash exposes REST APIs and TypeScript and Python SDKs for publishing, scheduling, batching, and monitoring HTTP-driven work. Upstash also maintains an MCP server for compatible coding agents, while QStash’s built-in LLM integrations add retries, callbacks, batching, and long request timeouts to model calls. Together, these surfaces make QStash a programmable execution layer for agents that need durable asynchronous steps.
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