Sumeta
Use case

Real-time database replication

Move every committed change from your operational databases into analytics and applications in seconds — captured directly from database logs.

The context

Why this belongs on your own infrastructure

Operational databases were built for transactions, not analytics. Yet every dashboard, cache, and search index depends on changes getting out of them quickly and completely. Bridge captures changes at the database log level — Oracle Redo, MySQL binlog, PostgreSQL WAL, SQL Server transaction log. Every row is checkpointed and replayable.

Common challenges

  • Change-control on production cores

    Database teams restrict third-party software on OLTP systems. Log-based CDC reads the transaction log directly.

  • Latency vs. completeness

    Nightly batches leave hours of blind spot; streaming must not drop a single committed transaction under load.

  • Schema drift

    Source tables evolve constantly. A silent column change should not break the downstream warehouse or lake.

  • Spiky transaction volume

    Month-end, promotions, or batch windows swing volume by orders of magnitude — and a per-row SaaS bill spikes with it.

How Bridge helps

Built for exactly these constraints

Capabilities drawn from production deployments — log-based capture, in-perimeter operation, and a spend you can predict.

Log-based CDC

Parse redo, binlog, and WAL directly from the source transaction logs.

Lineage & replay

Checkpoint-resume and automatic rollback mean every row is accounted for and re-runnable on demand.

Schema drift handling

Source schema changes are detected and propagated without breaking downstream models.

Data masking

Tokenize or mask sensitive fields before they reach the analytics tier.

In-perimeter operation

Run entirely inside your VPC or data center. Residency is structural, not a setting.

Predictable cost

Bill by rows with a 3× monthly cap — no surprise from a spike in transactions.

A typical flow

What the pipeline looks like

Operational DB (Oracle / MySQL / Postgres / SQL Server)→
Log-based CDC→
Transform / mask→
Warehouse · Cache · Search

All stages run inside your network. No data egresses unless you choose to.

Oracle · MySQL · PG · MSSQL
Log-based capture sources
<60s
CDC end-to-end lag at P95
100+
Supported source & target types

Ready to put real-time database replication into production?

Book a 30-minute demo scoped to your stack, or start a free evaluation license today.