DATABASE MODERNIZATION
Move the database. Modernize the estate around it.
Datachecks helps retire legacy database platforms by migrating the data, procedural logic, jobs, integrations and dependent workloads required to run them on modern target platforms.
LEGACY DATABASE ESTATE
Oracle / SQL Server / DB2
Schemas
Tables
Views
PL/SQL / T-SQL
Stored Procedures
Jobs
CDC
ETL
Dependencies
DATACHECKS
SNOWFLAKE / DATABRICKS / MODERN TARGET
WHEN THIS SERVICE FITS
When the database has become the constraint.
01
Legacy platform cost
The database is expensive to operate, scale or maintain.
02
Modernization pressure
The organization wants to move workloads to a modern cloud data platform.
03
Procedural complexity
Years of SQL, stored procedures, jobs and business logic make migration difficult.
04
Platform retirement
The goal is to safely decommission the legacy database and dependent workloads.
WHAT ACTUALLY GETS MODERNIZED
A database migration is bigger than schemas and tables.
THE DATABASE ESTATE
16 AREAS MODERNIZED
A database migration is complete only when the target can safely replace the legacy database and the workloads around it.
PRIMARY DATABASE MODERNIZATION SCENARIOS
Common database modernization paths.
Oracle → Snowflake
Modernize Oracle data, PL/SQL, procedures, jobs, ETL and downstream dependencies into Snowflake.
Explore Oracle → Snowflake
Oracle → Databricks
Move Oracle data and dependent workloads into a Databricks-native architecture.
Explore Oracle → Databricks
SQL Server → Snowflake
Modernize SQL Server databases, T-SQL, SSIS and scheduled jobs into Snowflake.
Explore SQL Server → Snowflake
SQL Server → Databricks
Move SQL Server data, T-SQL workloads and dependent pipelines into Databricks.
Explore SQL Server → Databricks
Also supporting DB2 and other database modernization scenarios based on source and target architecture
LEGACY DATABASE → TARGET PATTERN
Modernize the implementation—not just the syntax.
LEGACY DATABASE
MODERN TARGET
Tables / Views
Target tables / views
PL/SQL / T-SQL
Target-native SQL / Python / Spark
Stored Procedures
SQL / target-native services / redesigned implementation
Scheduled Jobs
Target-native or external orchestration
CDC
Modern ingestion / streaming pattern
ETL
Native pipelines / dbt / modern ELT
Security
Target governance / RBAC
Dependencies
Modern downstream architecture
CONVERT
MODERNIZE
RETIRE
Not every source component should be translated one-to-one. Datachecks determines what should be converted, redesigned or retired.
THE DIFFICULT PARTS
The hard work usually lives in the logic around the database.
Complex PL/SQL / T-SQL
Stored procedures and packages
Stateful processing
Temporary table patterns
Source-specific functions
Scheduler dependencies
CDC semantics
ETL coupling
Security translation
Hidden business rules
Downstream application dependencies
Business reconciliation
Repeatable patterns are automated. Complex patterns become explicit exceptions with owners and evidence.
HOW DATACHECKS DELIVERS
From database discovery to production cutover.
01
Assess
02
Discover
03
Map
04
Translate
05
Migrate
06
Validate
07
Reconcile
08
Cutover
AI Agents
Database discovery, translation and reconciliation at estate scale.
Native Migration Tools
Destination-native capabilities used where they are strongest.
Migration Experts
Architecture, exceptions and every sign-off.
Migration Evidence
Object-level proof connected across the lifecycle.
Automation at scale. Human judgment where it matters.
NATIVE TOOLS + DATACHECKS
Use platform-native migration capabilities where they are strongest.
Datachecks works with destination-native migration tools and adds whole-estate discovery, semantic mapping, exception handling, business validation and migration evidence around them.
NATIVE MIGRATION TOOLS
Assessment
Conversion
Data movement
Target execution
+
DATACHECKS
Dependencies
Semantic mapping
Exceptions
Business equivalence
Migration Evidence
+
MIGRATION EXPERTS
Architecture
Review
Critical decisions
PRODUCTION-READY TARGET
We do not rebuild what the destination platform already does well.
MIGRATION EVIDENCE
Prove every migrated database object.
Datachecks connects source objects, target mappings, translations, exceptions, validation and reconciliation evidence across the lifecycle.
Explore Migration Evidence
OBJECT MIGRATION PASSPORT
CUSTOMER_ORDERS
SOURCE · ORACLE
FIN.CUSTOMER_ORDERS
TARGET · SNOWFLAKE
CURATED.CUSTOMER_ORDERS
Mapping
APPROVED
Translation
COMPLETE
Exceptions
3 / 3 RESOLVED
Tests
64 / 64 PASSED
Reconciliation
MATCHED
STATUS
READY
WHAT THE CUSTOMER RECEIVES
What the modernization delivers.
Database Estate Inventory
Objects, code and dependent workloads in scope.
Dependency Map
Upstream, downstream and operational relationships.
Migration Classification
Convert / modernize / redesign / retire.
Target Mapping
Approved source-to-target architecture.
Modernized Artifacts
Target-native code and migration outputs.
Validation & Cutover Evidence
Proof required for production transition.
PART OF DATA ESTATE MIGRATION
Database Modernization is one type of Data Estate Migration.
When the database is the center of gravity, this service focuses the broader Datachecks migration model on database objects, procedural logic, jobs, integrations and dependent workloads.
FAQ
Frequently asked questions
What happens to PL/SQL, T-SQL and stored procedures?
Are scheduled jobs and CDC in scope?
How is database security and role translation handled?
What about downstream applications that depend on the database?
Is this the same as Data Platform Modernization?
How is equivalence proven before the legacy database is retired?
Planning to retire a legacy database?
Start with the database estate, dependent workloads and target architecture. Datachecks can assess the complexity and take the migration through production readiness.