Startups overload Postgres with triggers, queues, and pub/sub patterns because adding Kafka or Temporal feels like overkill at their scale, but they hit lock contention, processing loops, and consistency bugs that cook their DB
A lightweight sidecar or hosted service that sits alongside Postgres, replaces trigger-based workflows with a transactional outbox pattern, provides exactly-once async processing guarantees, loop detection, and a visual DAG of what updates trigger what — all without requiring teams to adopt a full event streaming platform
Freemium SaaS — free tier for low-throughput workloads, paid tiers based on events processed per month ($99-$499/mo)
The Reddit thread is a textbook pain signal — 'cooked the DB for a week,' '5-10 second simple operations,' race conditions from trigger loops. This isn't a nice-to-have, it's a production-down-at-2am problem. Teams hit this wall reliably at the 'too big for triggers, too small for Kafka' inflection point. However, many teams tolerate the pain longer than they should because the failure mode is slow degradation, not catastrophic failure.
TAM is constrained by definition: early-stage startups (2-20 devs) using Postgres who've outgrown triggers but won't adopt Kafka. That's maybe 50K-100K companies globally, with realistic penetration of 1-5%. At $200/month average, that's $12M-$120M potential revenue. It's a real market but not a massive one. Upside: if the product nails it, the TAM expands as companies grow (land-and-expand) and the 'Postgres maximalist' trend accelerates.
Teams at this pain point are already paying for Postgres hosting ($200-2000/month on RDS/Supabase/Neon). $99-499/month to fix event processing is within their infrastructure budget and cheaper than hiring an SRE to manage Kafka. The blocker: the person feeling the pain (backend dev) often isn't the one approving the budget. Counter-signal: 'transactional outbox has been shot down' from the Reddit thread suggests org resistance to new infrastructure.
A solo dev can build a functional MVP in 6-8 weeks: a sidecar that polls an outbox table (or tails WAL via logical replication), processes events with retry/DLQ semantics, and exposes a basic web UI showing the event DAG. The hard parts are exactly-once processing guarantees (doable with idempotency keys), loop detection (cycle detection on the event graph), and WAL slot management (tricky but well-documented). The 'hosted service' version adds significant complexity — multi-tenant WAL consumption, isolation, auth. Start with the self-hosted sidecar.
There is a clear gap in the market. Sequin does CDC-to-HTTP but lacks the outbox pattern, processing layer, and DAG visualization. PGMQ gives you the outbox primitive but no processing framework. Inngest handles processing but can't reliably capture events from Postgres. Debezium does everything but requires Kafka. Nobody offers: transactional outbox + reliable processing + loop detection + DAG visualization + no Kafka. That's the product.
Extremely sticky once adopted. Event processing is infrastructure — teams don't rip it out casually. Usage-based pricing (events/month) scales naturally with company growth. The 'free for low throughput, paid as you grow' model aligns incentives perfectly. Event volume is a strong proxy for business growth, so revenue grows with customer success.
- +Clear, validated pain point with production-incident-level severity — this isn't theoretical
- +Strong competition gap: no product combines transactional outbox + processing + DAG viz without requiring Kafka
- +Tailwind from the 'Postgres maximalist' movement (Supabase, Neon, Tembo ecosystem)
- +Naturally sticky infrastructure with usage-based pricing that scales with customer growth
- +Small enough niche that large players (AWS, Confluent) are unlikely to target it directly
- !Postgres extensions (PGMQ, pg_partman, pg_net) may combine into a 'good enough' open-source stack before this product gains traction
- !Sequin is the closest competitor and well-funded — if they add outbox support and a processing layer, the gap closes fast
- !Selling infrastructure to early-stage startups is hard: high churn, price-sensitive, prefer open-source, small deal sizes
- !The target audience may simply grow into Kafka/Temporal before paying for this, making the addressable window narrow
- !WAL-based approaches create a tight coupling to Postgres internals — major version upgrades and managed Postgres providers (Aurora, AlloyDB) may break assumptions
Postgres CDC-to-HTTP platform that streams row-level changes from Postgres WAL directly to HTTP endpoints, message queues, or webhooks without requiring Kafka. The closest direct competitor to this idea.
Postgres extension that adds SQS-like message queue semantics
High-performance Postgres-based job queue for Node.js using LISTEN/NOTIFY and FOR UPDATE SKIP LOCKED for low-latency task processing directly from your existing Postgres.
Event-driven serverless workflow engine where you send events and define step functions that react to them, with built-in retries, concurrency control, debounce, fan-out, and durable execution.
The gold-standard CDC platform that streams row-level changes from Postgres WAL into downstream systems. Has a dedicated transactional outbox connector that routes outbox table entries to topics/endpoints.
Open-source Go or Rust sidecar binary (single binary, zero dependencies beyond Postgres). Connects to your Postgres, creates an outbox table, polls it efficiently with LISTEN/NOTIFY. You write to the outbox table in your application transactions. The sidecar picks up events, executes registered handlers (HTTP webhooks initially), handles retries with exponential backoff, dead-letter queue, and exposes a lightweight web UI showing: event flow DAG, processing latency, failed events, and detected loops. Ship as a Docker image. Target: 'docker-compose up' and you're running in 5 minutes.
Open-source sidecar (free, builds community and trust) -> Hosted cloud version with multi-tenant isolation, managed WAL connections, alerting, and team collaboration ($99-499/month) -> Enterprise tier with SLAs, SSO, audit logs, dedicated support, and custom integrations ($999+/month). The open-source version is the funnel; the cloud version is the product.
8-12 weeks to open-source MVP with early adopters. 4-6 months to first paying cloud customer. The open-source phase is critical for credibility — infrastructure buyers need to trust before they pay. Expect 6+ months of near-zero revenue while building community. First $10K MRR likely at 9-12 months if execution is strong.
- “we decided to put a flag on the main table and then use a global trigger”
- “we got into trouble when there was a processing loop between the triggers and the processing”
- “we basically cooked the DB for a week where simple operations were turning into 5-10sec ordeals”
- “I suggested transactional outbox pattern... it's been shot down”
- “no global durability strategy or 2 phase commit structure to recover/resume processing”
- “we don't need it at our scale”