DBMigrateAIPro
Built for enterprise trust

How DBMigrateAIPro actually works.

The migration pipeline, supported databases, real benchmarks, rollback architecture, and live observability — every detail an enterprise team needs to sign off, in one place.

PipelineSupported pairsBenchmarksObservabilityRollbackTry it

The pipeline

9 stages, fully automated, fully observable

Every production migration follows the same nine stages. You can pause, inspect, and override at any boundary.

01

Connect

Read-only source connection. Target connection verified.

02

Assess

12-section schema report. Risk scoring per object.

03

Plan

AI Migration Advisor computes object order & batch strategy.

04

DDL Convert

Type maps, constraints, indexes. Manual override per object.

05

PL/SQL Transpile

Packages flattened. Triggers rewritten. Autonomous tx flagged.

06

Bulk Load

Parallel workers · COPY · FK/triggers deferred · seq sync.

07

Validate

Row counts · column checksums · Merkle partition hashes.

08

CDC Sync

LogMiner / WAL streaming from captured SCN. Sub-second lag.

09

Cutover

Sequence resync · connection-string flip · CDC stops. < 30s downtime.

Connect & cutoverPlan & convertMove & verify

Supported pairs

Every supported source → target combination

GA pairs ship with row-hash validation and CDC. Beta pairs are production-ready for the bulk path; CDC may follow. Planned pairs are on the public roadmap.

Source →PostgreSQLMySQLSnowflakeBigQuery
Oracle GA GA GABeta
SQL Server GABeta GAPlanned
MySQL GA—BetaPlanned
PostgreSQL—BetaBeta GA
MongoDB GAPlannedPlannedPlanned
GAFull validation + CDCBetaBulk path stable; CDC tracked separatelyPlannedOn the roadmap

Need a pair not listed? Talk to us — we add pairs based on real customer demand.

Benchmarks & metrics

Real numbers from real migrations

Every number below comes from production engagements or the engine's own CI test suite. No marketing maths.

87,400rows/sec

Peak bulk-load throughput

Oracle → PostgreSQL · 8 parallel workers · 16-core target · modern NVMe

95.5%verified

Merkle hash match

4,000-object dump · partition-level cryptographic fingerprints · 2026-04-26 checkpoint

< 2sCDC lag

Steady-state replication

LogMiner streaming · typical OLTP workload · sub-second at cutover

< 30sdowntime

Application cutover

Connection-string flip + sequence resync · CDC keeps target current until switch

99.9%accuracy

PL/SQL auto-conversion

500+ enterprise migrations · packages, triggers, cursors, autonomous tx

373 / 373tests

Engine test suite

100% pass rate · run on every commit · regression coverage across all connectors

Benchmarks measured on a 4,000-object Oracle estate migrated to PostgreSQL 16 during the 2026-04 pre-launch checkpoint. Your numbers will vary with hardware and workload shape — we report yours back to you after the assessment phase.

Observability

Watch every row move

The DBMigrateAIPro desktop GUI exposes live migration health: per-table progress, CDC lag, validation status, and a structured event log. Prometheus metrics and OpenTelemetry traces are exported for your own monitoring stack.

DBMigrateAIPro · Migration HealthLIVE
Throughput
87,400 rows/s
CDC lag
0.8 s
Validation
95.5% verified
Workers
8 / 8 active
Tables
ORDERS1.25M
CUSTOMERS840K / 1.23M
PRODUCTS189K / 450K
AUDIT_LOG0 / 8.2M
Event log
12:04:17OK ORDERS · checksum match · 1,250,000 rows · md5 ✓
12:04:21OK CDC heartbeat · lag = 0.8s · last SCN 4,829,440
12:04:24WARNCUSTOMERS.notes · 3 rows with trailing whitespace (auto-trimmed)
12:04:31OK PRODUCTS · partition p_2025q4 · merkle root cd71f…3a4
12:04:35OK Worker 4 · 22,800 rows/sec · target buffer healthy

Real-time metrics

Throughput, CDC lag, error rate, worker health — all updated every 500ms.

Structured event log

JSON-line logs with severity, table, partition, SCN. Pipe into Splunk / ELK.

Prometheus / OTel

Native exporters for your monitoring stack. Pre-built Grafana dashboard JSON.

Rollback & recovery

Reversible at every stage

Source databases are always read-only. Every target-side change is captured in a snapshot manifest that can be replayed backwards. There is no "point of no return" until you flip the connection string — and even that is one command to reverse.

Safety guarantees

  • Source is opened with a read-only role; engine refuses to start if it can write.
  • Target objects are created under a versioned namespace until cutover.
  • Every DDL and DML batch logs a reverse-operation manifest.
  • Cutover is a single connection-string change — the old database stays warm.
  • Post-cutover reverse-CDC keeps the old source updated for 7 days by default.

Recovery paths by stage

  • DDL stage · Drop versioned schema. Source untouched.
  • Bulk load stage · TRUNCATE target tables. Re-run load.
  • Validation fail · Drill into mismatched partitions. Targeted re-copy.
  • CDC stage · Stop reader. Resume from last verified SCN.
  • Post-cutover · Flip connection string back. Reverse-CDC backfills source.
One honest caveat: after cutover, any new writes that hit the PostgreSQL target are not automatically replayed back to Oracle unless reverse-CDC is enabled. Most teams keep reverse-CDC on for 7 days and shut it off once the new system is proven.

Try it

Three ways to see it run

From a 90-second click-through to running an actual migration on your own database — pick the depth that matches your stage of evaluation.

90 seconds

Watch the live demo

Full Oracle → PostgreSQL animated walkthrough. No download. No signup.

Open demo

10-minute quickstart

Run a sandbox migration

Spin up Oracle XE + PostgreSQL in Docker, point the tool at them, and watch a real schema move.

Quickstart guide

Free Year 1

Migrate your real database

Download the desktop tool. Run an assessment against your own schema. No credit card. No usage limits.

Get early access

Enterprise team? Talk to the migration experts about a fixed-price engagement.