The questions prospects ask, answered directly.

dbt tests and Great Expectations are excellent tools for the rules a team writes by hand: not-null, unique on a known key, expected-range on a column the team already knows is sensitive. They are not data quality in the sense of coverage, drift detection, or freshness.

If your team is not constantly authoring new YAML tests as the warehouse grows, the coverage gap is the problem Siftra solves. Siftra auto-inferring rules from column profiling and tracking distribution shift over time complements what dbt and Great Expectations already do — it does not replace them, and it does not require you to migrate your existing tests. Many teams run Siftra alongside dbt or Great Expectations to get the breadth that handbook-authored suites cannot keep up with.

Setup is a read-only database credential and one click. Siftra profiles all tables on connection, generates rules in the same scan, and assigns health scores within minutes. No agent. No sidecar. No pipeline YAML. No warehouse-side deployment.

Competitors typically require a deployment call with their solutions engineering team, a sidecar on your cluster, YAML pipeline definitions per dataset, and a CI integration before the first rule ever fires. The demo runs against a sandbox database so you can see the setup path end-to-end before involving your real data.

Run them on the same database with the same failure seeds. Our 6-tool benchmark article does exactly that on a 14GB Postgres dataset, with no sponsorship involvement.

The honest four-axis comparison most teams end up using:

• Time-to-first-rule from a fresh connection
• Coverage breadth out of the box (rules auto-generated vs required hand-authored)
• Pricing transparency and predictability (see /pricing)
• Agent footprint and infrastructure changes

Siftra scores well on all four; competitors vary widely. The one-click demo plus transparent /pricing removes the sales-call gating from the comparison in under five minutes.

If your data engineer is happy with the current coverage and is not asking for headcount to write more tests, you probably do not need this. If, like most teams, the data engineer is the single point of failure for every new dataset, every schema change, and every distribution shift that lands in the warehouse — they are the bottleneck.

Siftra is not a replacement for the data engineer's judgment; it is a force-multiplier that takes the "did anyone write a not-null test for this new column yet" question off their plate. Auto-generated rules from column profiling cover the long tail that a single engineer cannot keep up with by hand. The data engineer reviews the auto-generated rules, tunes thresholds, and focuses on the high-value anomalies — instead of writing the 200th not-null test of the quarter.

One person, one database connection, and about ten minutes. Siftra does not require a procurement-led rollout, an executive sponsor, or a quarter-long evaluation. A senior engineer or analytics lead can connect a warehouse, watch the first scan generate health scores across every table, and decide whether the auto-generated rules are useful within the same session.

The /pricing page documents the only modal decision: whether the team is willing to spend one engineering hour upfront to get continuous monitoring across the whole warehouse. There is no required executive training session, no required one-week onboarding, and no required call with our team before you can use it.

Yes, on a $0 trial basis. The one-click demo at /app?demo=true costs nothing, requires no credit card, and runs against a sandbox database so you can validate the product without involving procurement at all.

If you decide Siftra is worth rolling out to a real warehouse, the price is $99/mo flat — most teams find it pays for itself in the first avoided incident. Compared to the six-figure annual contracts across the six-tool benchmark on /pricing, Siftra is the only line item in the data observability category that fits inside an engineer's discretionary spend. Look now, allocate later, and keep the demo bookmarked for when the conversation turns into a real evaluation.

The free tier lets you connect a sandbox database and see the full product end-to-end, with no time limit. There is no hidden pressuring-on tier, no trial-ending cut-off, and no automatic credit-card prompt.

Paid is $99/mo flat and adds three things: connection to your own real warehouse, scheduled automatic scans, and persistent rule history. The pricing model on /pricing shows what you get at every tier — there are no surprise upsells once you connect production. You can stay on the free sandbox tier indefinitely if continuous scanning on a real warehouse is not yet a priority.

A column is a column in your database schema — one cell in a row, not every value. If your orders table has 12 columns, that is 12 columns regardless of whether the table has 100 rows or 100 million rows.

We do not price per cell, per row, per value, per event, per scan, or per query. A PostgreSQL table with 40 columns and 10 million rows is the same price as a 40-column table with 100 rows. Derived columns and views are tracked the same way. The goal is a pricing model where the engineering team never has to weigh monitoring decisions against the monthly bill, and where adding a new table or column does not require a procurement conversation.

Cancel from your billing dashboard in two clicks. No annual contract. No minimum term. No retention call. No exit-fee. The moment you cancel, scans stop running and the connection is closed.

Your rule definitions are stored as plain SQL in our metadata store and remain exportable for 30 days, so you can pull them into your warehouse, hand them to a successor tool, or hand them back to your data team. There is no vendor lock-in by design: rules expressed in plain SQL are portable to other systems, and the auto-generation model means there are no proprietary rule definitions that walk out the door with us.

We publish our rolling 30-day uptime on /pricing. The Siftra control plane runs on Render's standard infrastructure tier, and we commit to the Render SLA as our operating floor rather than layering a custom-contract SLA on top.

If your team's SLA requirement is stricter than what we publish, the right conversation is an enterprise contract — reach out via the early-access list on /pricing and we will scope a committed SLA and a dedicated support channel. The auto-rules and health-score history are tied to your scan schedule, so a brief control-plane outage does not affect the integrity of your historical scores.

Yes to the trial, no to the credit card. The /app?demo=true one-click demo spins up a sandbox database with intentional data quality issues, profiles it, generates rules, and shows health scores in under a minute. There is no signup wall, no card prompt, no auto-renewal after a 14-day countdown.

You can keep the sandbox connected for as long as you want. When you decide to connect your own real warehouse, that is when the $99/mo paid tier kicks in — and you control when that happens. The full pricing comparison on /pricing walks through exactly what you get at the free sandbox tier versus the paid tier, so there are no surprises at the upgrade moment.