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Data Migration Factory

$79

Industrialized migration framework with extractors for 8 source types (SQL Server, PostgreSQL, Oracle, MySQL, files, APIs), validation, and cutover runbooks.

📁 16 files🏷 v1.0.0
Production-ready
✓ Instant download✓ Lifetime updates✓ MIT licensed✓ MIT license✓ Secure checkout (Stripe)

📋 What's Inside 16 files

  • ✓ README.md—
  • ✓ manifest.json—
  • ✓ assessment/source_assessment.py—
  • ✓ assessment/migration_wave_planner.py—
  • ✓ extractors/sql_server_extractor.py—
  • ✓ extractors/postgresql_extractor.py—
  • ✓ extractors/mysql_extractor.py—
  • ✓ extractors/oracle_extractor.py—
  • ✓ extractors/file_bulk_extractor.py—
  • ✓ extractors/rest_api_extractor.py—
  • ✓ validation/reconciliation.py—
  • ✓ validation/data_sampling.py—
  • ✓ runbooks/cutover_runbook.md—
  • ✓ runbooks/decommissioning_checklist.md—
  • ✓ dashboards/migration_progress.sql—

📁 File Structure 16 files

data-migration-factory/
├── README.md
├── manifest.json
├── assessment/
│ ├── source_assessment.py
│ ├── migration_wave_planner.py
├── extractors/
│ ├── sql_server_extractor.py
│ ├── postgresql_extractor.py
│ ├── mysql_extractor.py
│ ├── oracle_extractor.py
│ ├── file_bulk_extractor.py
│ ├── rest_api_extractor.py
├── validation/
│ ├── reconciliation.py
│ ├── data_sampling.py
├── runbooks/
│ ├── cutover_runbook.md
│ ├── decommissioning_checklist.md
├── dashboards/
│ ├── migration_progress.sql
├── guides/
│ ├── migration_methodology.md

📖 Documentation Preview README excerpt

Data Migration Factory

Product 15 | Datanest Digital

[https://datanest.dev](https://datanest.dev)

Price: $79 | Version: 1.0.0 | Category: Data Engineering

---

Overview

Data Migration Factory is a production-ready framework for migrating data from

heterogeneous source systems into Databricks Lakehouse. It provides structured

assessment tooling, battle-tested extractors for the most common source platforms,

automated reconciliation, and operational runbooks that reduce migration risk and

compress project timelines.

Whether you are consolidating on-premise databases, moving from legacy warehouses,

or ingesting from SaaS APIs, this toolkit gives you repeatable, auditable migration

pipelines from day one.

What's Included

Assessment
FileDescription
`assessment/source_assessment.py`Databricks notebook that catalogs source tables, columns, volumes, row counts, and dependency graphs.
`assessment/migration_wave_planner.py`CLI tool that scores tables by complexity and groups them into prioritized migration waves.
Extractors
FileDescription
`extractors/sql_server_extractor.py`SQL Server full + incremental extraction via Change Tracking / CDC.
`extractors/postgresql_extractor.py`PostgreSQL logical replication extractor with slot management.
`extractors/mysql_extractor.py`MySQL binlog-based CDC extractor.
`extractors/oracle_extractor.py`Oracle LogMiner-based CDC extractor.
`extractors/file_bulk_extractor.py`Flat file (CSV / JSON / Parquet) bulk and incremental loader.
`extractors/rest_api_extractor.py`REST API pagination framework with retry, backoff, and schema inference.
Validation
FileDescription
`validation/reconciliation.py`Source-to-target row count, hash, and aggregate reconciliation.
`validation/data_sampling.py`Statistical sampling comparison with configurable thresholds.
Dashboards
FileDescription
`dashboards/migration_progress.sql`SQL-based dashboard queries for tracking migration waves, throughput, and quality.
Runbooks & Guides
FileDescription
`runbooks/cutover_runbook.md`Step-by-step cutover procedures: parallel run, validation gates, switchover, rollback.
`runbooks/decommissioning_checklist.md`Post-migration source decommissioning checklist.

... preview truncated, see full README in product download.

📄 Code Sample .py preview

assessment/source_assessment.py# Databricks notebook source # MAGIC %md # MAGIC # Source Assessment # MAGIC **Data Migration Factory** | Datanest Digital | https://datanest.dev # MAGIC # MAGIC Catalogs existing source tables, columns, row counts, data volumes, # MAGIC and inter-table dependencies. Writes results to a Unity Catalog # MAGIC assessment schema for downstream wave planning. # COMMAND ---------- # MAGIC %md # MAGIC ## Configuration # COMMAND ---------- dbutils.widgets.text("jdbc_url", "", "JDBC Connection URL") dbutils.widgets.text("jdbc_user", "", "JDBC Username") dbutils.widgets.text("jdbc_password", "", "JDBC Password (secret scope:key)") dbutils.widgets.text("source_system_name", "unknown", "Source System Name") dbutils.widgets.text("catalog", "migration", "Target Catalog") dbutils.widgets.text("schema", "assessment", "Target Schema") dbutils.widgets.text("source_schema_filter", "%", "Source Schema Filter (SQL LIKE)") dbutils.widgets.dropdown("source_type", "sqlserver", ["sqlserver", "postgresql", "mysql", "oracle"], "Source Database Type") # COMMAND ---------- import hashlib import json import logging from dataclasses import dataclass, field, asdict from datetime import datetime, timezone from typing import Optional from pyspark.sql import SparkSession, DataFrame from pyspark.sql import functions as F from pyspark.sql.types import ( StructType, StructField, StringType,

⚙ Requirements & Compatibility

RequirementDetails
Databricks Runtime≥ 13.3 LTS
Python>=3.10
LicenseMIT (see license-terms page)

📅 Changelog

v1.0.0 — Initial release.

Purchases include lifetime updates. Check the product page for the latest version.

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