Platform Overview

The Operational Data Platform for live enterprise data.

Tapstate is an operational data platform that captures, transforms, and serves live operational state to the applications, APIs, automation, and AI agents that depend on it.

Start with reliable log-based CDC. Expand into transformation and state serving on the same platform.

Production systems

Committed source changes

Tapstate Operational Data Platform

ConnectorsOrderingCheckpointsRecovery
Capture
Transform
Serve

Operational State Layer

current · queryable · reusable

ApplicationsAPIsAutomationAI agents

Capture → Transform → Serve

One platform. Three continuous responsibilities.

Tapstate keeps capture, ordered transformation, and state delivery on the same operational data path.

Tapstate Platform

Capture

Load existing data and, where supported, continue from source changes.

SnapshotFull load + CDCSource positions + checkpointsConnector-specific recovery

Transform

Apply ordered, reviewable transforms to records in flight.

Filter recordsJavaScript enrichmentRename + normalizeArray unwind + fan-out

Serve

Materialize and deliver current state through supported targets.

Structured syncUpsert or appendDeletes by stable keySchema-change policy

Shared across the path

One deployableDeclarative resourcesWorkspace validationDurable recovery state

Progressive adoption

Start with Capture. Expand on the same platform.

Teams can begin with capture and delivery. As requirements grow, the same platform can add ordered transformation and materialize current state through supported targets.

Capture

Load existing data or continue from supported source changes.

Capture + Transform

Add ordered transforms to filter, normalize, enrich, and reshape records.

Capture + Transform + Serve

Materialize consumer-ready current state through supported targets.

Start with the responsibilities the use case needs today.

Expand on the same platform as requirements grow.

The output

Maintain current state once. Deliver it to many consumers.

Tapstate materializes source changes into consumer-ready current state through supported targets. Applications, APIs, automation, and AI agents can reuse the same maintained result without rebuilding the full data path.

Source-oriented changes

  • order row updated
  • payment inserted
  • shipment status changed
  • customer tier updated
  • support case opened

Tapstate Platform

Capture → Transform → Serve

Current order state

  • order status
  • payment state
  • shipment position
  • customer tier
  • active support context

Downstream consumers

Applications

Use current entities.

APIs

Expose maintained state.

Automation

Act on current conditions.

AI agents

Use coherent context.

The Operational State Layer

A shared layer for what is true now.

The Tapstate platform establishes the Operational State Layer between systems of record and operational consumers — a shared architectural capability, not a separate product, that keeps current state maintained once instead of rebuilt by every consumer.

Systems of record

Databases where operational facts are created and committed.

Tapstate Platform

Capture, transform, and serve changes as they happen.

Operational State Layer

Current, queryable, reusable state — maintained once.

Operational consumers

Applications, APIs, automation, and AI agents.

Use cases

Where teams put operational state to work.

A representative, not exhaustive, set of ways teams use the operational state layer.

  1. Unified customer context

    Combine order, account, and support activity into one current customer view.

  2. Real-time inventory and order state

    Keep stock levels and order status current across channels and locations.

  3. Operational APIs for internal tools

    Expose maintained state to internal apps without querying source systems directly.

  4. Event-driven automation

    Trigger workflows and alerts from changes in current operational state.

  5. Context for AI agents

    Give agents coherent, current state instead of stale or fragmented lookups.

Platform operating model

The full operating path, not just one component.

Tapstate maintains the definitions, progress, policies, and diagnostic context required to operate a data path across capture, transformation, and delivery.

  1. 01

    Declarative resources

    Keep source, pipeline, transform, and delivery definitions explicit and reviewable.

  2. 02

    Positions and checkpoints

    Retain capture progress, checkpoints, and retry context across interruptions.

  3. 03

    Transform and schema state

    Apply ordered rules while keeping mappings and output shape inspectable.

  4. 04

    Delivery policies

    Control target writes, stable keys, deletes, and schema-change behavior.

  5. 05

    Validation and diagnostics

    Validate resources and retain status, retry, and failure context for troubleshooting.

Platform boundaries

A clear operating boundary, not a replacement for everything else.

The platform operates the data path from source capture through transformation and delivery. It works alongside the systems that remain authoritative, analytical, or responsible for business behavior.

Systems of record

Remain authoritative for operational facts and source-side behavior.

Event backbones

Continue to support custom event distribution and specialized stream topologies.

Warehouses and lakehouses

Retain historical data for analysis, aggregation, and model training.

Applications and agent frameworks

Own business logic, user experience, decisions, and execution.

Explore the Architecture

Building on the platform

Define, validate, and run one declarative data path.

Tapstate uses .tapstate.yml resources to define connections, apply supported transforms, and declare delivery targets. Teams can review the configuration in Git, validate it before a run, and test connectivity and data behavior in their own environment.

Step 1

Define connections

Choose connector roles, capture modes, endpoints, and credentials.

Step 2

Define a pipeline

Reference a source, apply supported transforms, and declare sync or push targets.

Step 3

Review and validate

Check resource structure, fields, IDs, references, and secret placeholders.

Step 4

Run in your environment

Test connectivity and representative data behavior before production.

Quickstart

Build your first operational data path.

The Tapstate quickstart defines a MySQL source, a MongoDB target connection, and a pipeline that links them. Validate the workspace before testing connectivity and data behavior in a non-production environment.

Source · MySQL · Snapshot

orders_source.tapstate.yml

Defines the MySQL source connection and snapshot read mode.

Pipeline

orders_to_customer_view.tapstate.yml

References the source and declares the MongoDB delivery target.

Target · MongoDB

customer_view.tapstate.yml

Defines the MongoDB target connection.

Validate the workspace

$tapstate validate --workdir tapstate-work
Open the Quickstart

Next steps

See how Tapstate fits your operational data path.

Review the architecture, read the docs, or walk through your use case with us.