Low-Code CDC

Real-time change capture.
Without writing code.

Low-Code CDC lets teams set up real-time change data capture through a visual interface — streaming row-level inserts, updates, and deletes from source databases into governed pipelines, no code required.

Real-time CDCNo codeRow-level changesGoverned streamingAuto-lineage
Change Capture — Live
Core Banking · accounts
CDC active · 142 changes/min
green
LOS · applications
Insert + Update captured
green
CRM · contacts
Schema change detected · handled
amber
PII Masking
PAN + mobile masked in-stream
green
Lineage
Source → target · row-level
green

Why this matters.
Right now.

Batch loads leave AI agents working on yesterday's data, while hand-built change capture is fragile, code-heavy, and breaks the moment a source schema changes.

Batch data is stale data.

Nightly loads mean AI agents and dashboards decide on yesterday's state. In fraud, credit, and operations, stale data produces decisions that are already wrong.

Hand-built CDC is fragile.

Custom change-capture code is complex to build and breaks the moment a source schema changes — leaving teams firefighting pipelines instead of delivering data.

Streaming PII is a blind spot.

Change streams move sensitive data at high velocity. Without governance in the stream, PII flows downstream unmasked, faster than any manual check can catch.

From source to
governed pipeline.

1

Select

Pick a source database and the tables to capture — through a visual interface.

2

Configure

Choose inserts, updates, deletes, and masking rules with guided controls — no code.

3

Govern

PII is masked in-stream, schema changes are handled, and lineage is captured per row.

4

Stream

Governed change data flows in real time to lakehouse, agents, and analytics.

What Low-Code CDC
delivers.

Real-time change capture.

Stream row-level inserts, updates, and deletes from source databases the moment they happen — so AI agents and dashboards always reflect current state.

🎛️

No-code setup.

Configure change data capture through a visual interface — select tables, set rules, and start streaming without writing or maintaining fragile custom code.

🔐

Governed in the stream.

PII is detected and masked in-stream, so sensitive change data is protected at velocity — not after it has already flowed downstream.

🛡️

Schema-change resilient.

Low-code CDC adapts to source schema changes automatically, so column renames and type changes no longer break your real-time pipelines.

Row-level lineage.

Every captured change carries lineage from source row to target, so real-time change data capture stays fully auditable for regulated industries.

🔌

Major database support.

Capture changes from core banking, loan origination, CRM, and other relational sources — governed identically through the low-code CDC builder.

Frequently asked
questions.

What is low-code CDC?

Low-code CDC is a visual way to set up change data capture — streaming row-level inserts, updates, and deletes from source databases — without writing code. Tantor's low-code CDC governs the stream automatically, masking PII and capturing lineage per row.

How is CDC different from batch loading?

Batch loading copies data on a schedule, leaving AI agents working on stale data. Change data capture (CDC) streams only what changed, the moment it changes — so low-code CDC keeps dashboards and agents current in real time.

Is low-code CDC governed?

Yes. Tantor's low-code CDC governs the change stream — PII is masked in-stream, schema changes are handled automatically, and row-level lineage is captured — so real-time change data capture stays auditable in regulated industries.

Do I need to write code for change data capture?

No. Low-code CDC replaces fragile, hand-built change-capture code with a visual interface — you select source tables, configure rules, and start streaming governed change data, with schema changes handled automatically.

Real-time change data.
Governed, no code.

See how Tantor Low-Code CDC streams governed, row-level change data in real time — PII masked in-stream, schema changes handled, lineage tracked per row.