For enterprise data teams

The modern
data comparison
platform.

Validate any source against any target. Catch data issues before they hit production. Cloud or self-hosted — your choice, same price.

Book a live demo See the platform

Source · core_banking.txns Target · snowflake.fct_txns Result

TXN_88412

1,204.00

MATCH

TXN_88413

87.55

MATCH

TXN_88414

9,610.02 expected 9,610.20 · Δ 0.18

FLAG

TXN_88415

442.00

MATCH

TXN_88416

15.99

MATCH

521,748 matched 12 mismatched cell-level · 8.4s

60+Enterprise featuresshipped to production

<15 minTime to first comparisonno services engagement

10M+Rows in under 10 minauto-spill via DuckDB

EitherCloud or on-premsame price, your choice

The problem

Data validation is stuck in 2010.

Three patterns most enterprise data teams know all too well.

Months to deploy

Legacy tools demand weeks of professional services, classroom training, and consultant time before you generate a single comparison.

Brittle, hand-rolled scripts

When tools fall short, teams write custom Python or SQL to compare data. It drifts, breaks silently, and nobody owns it once the author leaves.

No path off legacy ETL

Hundreds of Alteryx, Informatica, or SSIS workflows mean years of manual rebuilding to switch tools. Migration cost kills the business case.

How it works

From data source to verified output
in four steps.

Built in the UI for hands-on review. Run from your pipelines when it's time to automate.

STEP 01

Connect

Databases, files, cloud storage, REST APIs, or COBOL copybooks. Test the connection, browse the schema, save it. Isolated per workspace.

STEP 02

Compare

Build in the SQL editor, the no-code wizard, or plain language. Five strategies. Run on demand, on a schedule, or from a webhook.

STEP 03

Validate

Wire comparisons into pipelines on a 30+ node canvas. Watch runs stream live. Anomaly detection flags drift on its own.

STEP 04

Integrate

Plug into your CI/CD, orchestrator, or BI stack. MCP server, email, Slack, Teams, webhooks — with a full audit trail behind it.

Platform capabilities

Built for the realities
of enterprise data.

A handful of the 60+ features already in production.

Workflow

30+ node workflow canvas

Fuzzy join plus a full Alteryx-parity prep, parse, and transform toolkit. Live execution, wire-data preview, multi-tab workspace.

Engine

Five comparison strategies

Cell-level, row-count, aggregate, schema, and custom SQL. Auto-spills to DuckDB past 500K rows. Snapshot mode for current, as-of, or range.

Connect

19 connectors today

PostgreSQL, MySQL, SQL Server, Oracle, Snowflake, Databricks, BigQuery, Redshift, Synapse, SAP HANA, REST API, COBOL, files, S3, Azure.

Test generation and NL → SQL

Four LLM providers. Turn a mapping document into a test suite, ask for a comparison in plain language, get root-cause analysis on failures.

Detect

Anomaly detection

Distribution-shift, null-rate spike, and volume-change detectors with rolling baselines. Catches drift before anyone opens a dashboard.

Profile

Data profiling

Per-column cardinality, null percentage, distinct count, min, max, mean, median, standard deviation, and 10-bucket histograms on any source.

Govern

Immutable audit trail

Append-only, enforced at the database level — updates and deletes are denied outright. Every login, edit, run, and export is captured.

Govern

5-role RBAC and workspaces

Viewer, Tester, Author, Admin, Super Admin, with custom permissions per membership. SAML 2.0 and OIDC single sign-on.

Migrate

Alteryx and dbt import

Upload a .yxmd or manifest.json and get back working connections, comparisons, and a test suite. Over 80% of common tools map one to one.

Where TRACe fits

Enterprise capability.
Modern experience.

The category leaders, side by side, on the things buyers actually ask about.

Capability	TRACe	QuerySurge	Datafold	Alteryx	iceDQ
Visual workflow canvas	30+ nodes	None	None	Full	None
AI test generation	Full	Full	Full	Partial	Anomaly only
Natural language → SQL	Full	Full	None	Partial	None
COBOL / mainframe support	Full	Full	None	Via ODBC	Via conversion
Workflow import (Alteryx, dbt)	Full	Manual	Manual	n/a	None
On-prem deployment	No upcharge	Available	Cloud only	Available	Available
Immutable audit trail	Full	Full	Partial	Basic	Partial
Connector breadth	19	40+	15	50+	150+
Time to first comparison	<15 min	Weeks	Hours	Hours	Days

Comparison based on public documentation and product availability as of June 2026.

Built for

Teams where data correctness
can't be optional.

Financial services & banking

Reconciling mainframe core banking against cloud warehouses. Trade-by-trade validation, regulatory reporting integrity, and drift flagged between reconciliation cycles.

Daily reconciliation · 1M–100M rows per cycle

Insurance & claims

Policy migration off legacy admin systems. Claims validation across the new and old system overlap, plus premium calculation engine checks.

Migration cycle · 10M–500M rows total

Healthcare & pharma

Clinical trial data integrity and EHR migration validation, with PHI-aware mismatch display and an immutable audit trail. On-prem at no extra cost.

Multi-source integrity · HIPAA + GxP

Modern data platform teams

Validating dbt models against source systems, detecting drift between staging and production, and gating deploys on data quality.

Continuous · Plugs into dbt, Airflow, Dagster

API-first architecture

Build it in the UI.
Automate it through the API.

Every action in the interface is an API call. The comparison you review by hand is the same one your pipeline runs at 3am.

REST API

44+ endpoints with an auto-generated OpenAPI spec.

CI/CD blocking run

Returns pass or fail with an exit code, so you can gate a deploy on data quality today.

POST /ci/comparisons/{id}/run-blocking

MCP server — 6 tools

list_connections, run_comparison, nl_to_sql, and more. Connect TRACe to any MCP-compatible AI agent.

Webhooks and live events

Run complete, comparison failed, threshold breached. Real-time run progress over SSE. HMAC signing ships Q3.

Gate a deploy on data quality

# Fails the build if the warehouse doesn't match source
POST /ci/comparisons/{id}/run-blocking
Authorization: Bearer trace_sk_live_xxx

→ {
    "status": "passed",
    "exit_code": 0,
    "summary": {
      "matched": 521748,
      "mismatched": 12
    }
  }

# 0 = pass, 1 = fail. Blocks until the run finishes.

The commercial story

Enterprise capability
without enterprise gatekeeping.

Priced for predictability and adoption. Here's the shape of it — we'll walk through specifics on the call.

Per user, per workspace

Pricing scales with people, not data volume. Your finance team can forecast it.

No per-run metering

Run a million comparisons or run one — the price is the same. Nobody has to ration coverage.

No professional-services tax

Self-serve onboarding by design, first comparison in under 15 minutes. No mandatory implementation package.

On-prem at no upcharge

Same product, same price, running inside your environment. There's no premium tier to climb to keep data where it is.

Ready to see TRACe?

Run your first comparison
in under 15 minutes.

A live demo against your own data. No professional-services upsell, no six-week onboarding.

Book a live demo Talk to engineering