Vaachas vs DIY multi-DB glue
A conservative look at what it usually costs to build and maintain multi-database workflows yourself with queues and workers, versus using a database gateway like Vaachas for a single representative workflow.
These are example scenarios based on cautious assumptions for a typical Postgres + search/analytics workflow. They are not guarantees for every team or every stack, but a way to sanity-check the economics of a gateway.
- In the example scenario below, building a DIY Postgres + search workflow with queues and workers takes about 3-4 weeks of a strong backend engineer (~$9k-12k of engineering time), plus roughly $5k-13k/year to keep it healthy.
- Using Vaachas for that same workflow is framed as a few days of integration (~$3k-4k of engineering time) with less custom infrastructure to maintain over time.
- In simple in-region tests, Vaachas calls landed around ~39-43 ms p50 and ~47-53 ms p95 — well within normal in-region API latency bands — so the gateway does not have to be a major latency tax.
- Designing the workflow across app DB and search/analytics store
- Setting up messaging (Kafka/RabbitMQ/etc.) and consumer workers
- Implementing ordering guarantees, retries, and idempotency
- Wiring logs/metrics and on-call runbooks for incidents
For a single representative workflow, it is common for a strong backend engineer to spend 3–4 weeks building this from scratch.
At a conservative fully-loaded cost of $150k–$200k/year, that is roughly $9k–$12k of engineering time just to ship the first version.
After launch, small changes, incident work, and edge cases typically consume another 8–16 days/year, or roughly $5k–$13k/year of ongoing maintenance for this one path.
- Register existing databases once in Vaachas
- Define ordered steps for the Postgres + search/analytics write path
- Call one HTTP endpoint from the application
- Use Vaachas's per-DB outcomes and retries for observability and recovery
For the same workflow, teams typically spend a few days integrating with a gateway instead of multiple weeks rebuilding plumbing.
With cautious assumptions (3–5 days of a similar engineer), that is roughly $3k–$4k to integrate, with less custom code to own long term.
Ongoing adjustments are usually configuration and request changes in Vaachas, plus smaller application updates, rather than repeatedly revisiting queue and worker internals.
Latency and performance
A common concern with any gateway is latency. We measured Vaachas against direct REST access to Elasticsearch and Postgres in a simple in-region setup.
p50: ~39–43 ms
p95: ~47–53 ms
N = 100 requests, warm connections
p50: ~79–81 ms
p95: ~83–93 ms
p50: ~167 ms
p95: ~189 ms
Method. Same-region VM; warmup 10, 100 runs; results vary by region and setup. "Gateway" = call to Vaachas (in-region) using X-API-KEY. "Direct" = client calls database REST directly from its region.
Why direct can be slower. With naive direct calls, the client pays for more network hops and per-request connection setup. In our setup, the gateway reuses pooled connections in-region.
Interpretation. These numbers sit comfortably within typical in-region API latency bands, and show that a gateway does not have to introduce a large latency tax for typical operations.
Pricing bands and fit
For teams that fit Vaachas well (multi-DB features already in production, and appetite to simplify coordination), we are targeting annual contract values in these ranges:
Target band: $8k–$20k ACV/year
Roughly in line with the engineering time many teams already spend building and maintaining a single significant workflow themselves.
Target band: $20k–$60k ACV/year
Higher scope and risk mean more value from centralizing coordination, retries, and visibility in a gateway instead of more bespoke glue.
These ranges are planning bands, not public list prices, and actual contracts depend on workload scope, traffic, and support expectations. They are intended to show that using a gateway is usually in the same order of magnitude as what teams already spend on custom coordination for a handful of important workflows.
If you'd like, we can map one of your workflows end-to-end (current queues/workers included) and see where a gateway would or would not make sense.