Move Your Data Without the Drama
You need data migration that works the first time. Whether you are looking for a data migration company to move your databases to the cloud, need experienced data migration experts to transfer database systems between platforms without downtime, or want to migrate data from a legacy environment to a modern stack, the concern is always the same: can you guarantee nothing gets lost? Your team gets end-to-end data migration services that cover everything from planning and mapping through to validation and post-migration support. That includes data migration for enterprise systems with complex schemas, large volumes, and strict compliance requirements. The approach is built around custom data migration workflows that fit your systems and your timeline. Ready for a data migration quote? Tell us what needs to move.
Data migration projects typically cost between $20,000 and $500,000 depending on data volume, complexity, and the number of source and target systems. Simple database migrations take 4 to 8 weeks. Enterprise-scale migrations involving multiple systems and data transformation take 3 to 12 months.
Core Capabilities and Features
Move Between Database Engines Safely
Your data moves between database engines: Oracle to PostgreSQL, SQL Server to MySQL, MongoDB to DynamoDB, or any other combination. This includes schema conversion, stored procedure translation, data type mapping, and performance tuning on the target platform. Automated conversion tools are used where possible and edge cases are handled manually.
- Schema conversion, stored procedure translation, and data type mapping included
- Performance tuning on the target platform after migration
- Automated conversion tools used with manual handling for edge cases
Move On-Premise Data to the Cloud
Your on-premise databases and data stores move to cloud platforms (AWS, Azure, Google Cloud). This covers infrastructure setup, security configuration, data transfer, and performance validation. Hybrid scenarios are also handled where some data stays on-premise while other datasets move to the cloud.
- Infrastructure setup, security configuration, and performance validation
- Supports AWS, Azure, and Google Cloud as target platforms
- Hybrid scenarios handled where some data stays on-premise
Modernize Your Analytics Infrastructure
Your analytics infrastructure moves from legacy warehouses (Teradata, Netezza, Oracle) to modern cloud warehouses (Snowflake, BigQuery, Redshift). This includes ETL pipeline migration, report and dashboard migration, and historical data transfer.
- ETL pipeline migration to cloud-native processing services
- Report and dashboard migration to the new warehouse platform
- Full historical data transfer with validation and reconciliation
Why It Matters
If you have ever lost a customer record during a system switch, watched a report break because a field was mapped wrong, or spent a weekend in the office running manual fixes after a migration that was supposed to take two hours, you understand why this matters. Your data is not just rows in a database. It is years of customer relationships, transaction history, compliance records, and business intelligence. Losing it, corrupting it, or migrating it incorrectly does not just create a technical problem. It creates a trust problem, internally with your team and externally with your customers. The businesses that handle migration well are the ones that invest in doing it properly from the start: thorough discovery, careful mapping, rigorous testing, and verified reconciliation. It is not glamorous work. But it is the foundation everything else is built on.
By the Numbers
83%
Of data migration projects either fail or significantly exceed their budgets and timelines. Poor scoping and data quality issues are the most common causes.
Source: Gartner / Bloor Research
30%
Average cost overrun on data migration projects, with schedule slippage averaging 41%. Most of this is caused by data quality problems discovered mid-project.
Source: Oracle / Bloor Group
$9.7-15M
Annual cost to organisations from poor data quality. Data issues that exist before migration get amplified when moved to a new system without cleaning.
Source: Gartner, 2025
64%
Of organisations cite data quality as their top data integrity challenge. This is the number one factor that turns simple migrations into complex, expensive ones.
Source: Precisely Data Integrity Report, 2025
65%
Of cloud migrations are now completed on time and within budget, up from 54% in 2022. The improvement is driven by better tooling and more experienced migration teams.
Source: IDC / Medha Cloud, 2025
"Data migration is where trust is built or broken. Every record that arrives correctly in the target system is a promise kept. Every record that does not is a problem someone will have to explain. That is why we validate everything, not just a sample."
Technologies
Our Tech Stack
Our Process
How we turn ideas into reality.
Discovery
Your source systems, data models, volumes, quality issues, and dependencies are audited. Every table, field, format, and relationship is documented. This produces a migration assessment with risk areas flagged.
Mapping and Design
Field-level mapping is created between source and target systems. Transformation rules, validation checks, and reconciliation logic are defined. The migration architecture is designed: ETL pipelines, staging environments, and rollback procedures.
Build and Test
Migration scripts and pipelines are built, test migrations run with sample data, results validated against expected outcomes, and iterations continue until every edge case is handled. Testing is never skipped to save time.
Execute and Validate
The production migration runs in a controlled window. Every record is validated against the source, counts and checksums are reconciled, and your team confirms before the old system is decommissioned. Nothing goes live until everything matches.
Pricing
Investment Overview
Data Volume
Migrating 10 GB is a different project from migrating 10 TB. Larger datasets require more infrastructure, longer transfer windows, and more validation time.
Data Quality
Dirty data with duplicates, missing fields, inconsistent formats, and orphaned records takes significantly more time to clean and map than well-structured data. This is often the single biggest variable in project cost.
Schema Complexity
Simple flat tables migrate quickly. Complex relational schemas with foreign keys, triggers, stored procedures, and custom data types require careful conversion and testing.
Everything we do at Techneth is built around making data move reliably between the systems that matter. If you want to understand our approach before committing, you can read more about our team and how we work. Or explore the full range of digital product and development services we offer, like data migration. And if you already know what you need, get in touch directly and we will find time to talk.
Frequently Asked Questions
Everything you need to know about this service.
- What is data migration?
- Data migration is the process of moving data from one system, format, or environment to another. This can involve moving databases between platforms, transferring data to the cloud, converting data formats during a system upgrade, or extracting data from a legacy system being decommissioned. The goal is to get your data to the target system accurately, completely, and without disruption to your business.
- How long does data migration take?
- Simple database migrations with clean data and straightforward schemas typically take 4 to 8 weeks. Mid-complexity projects involving multiple source systems and data transformation take 2 to 6 months. Enterprise-scale migrations with large volumes, complex relationships, and compliance requirements can take 6 to 12 months.
- Can you migrate data without downtime?
- Yes. For systems that cannot afford downtime, change data capture (CDC) and real-time replication keep the source and target systems in sync during the migration period. Once the target is fully caught up and validated, the cutover happens with minimal or zero interruption.
- How do you ensure data quality during migration?
- Data profiling runs on the source system before migration to identify quality issues upfront. During migration, cleaning rules, deduplication, and validation checks are applied at every stage. After migration, row counts, checksum comparisons, and field-level spot checks between source and target confirm that everything transferred correctly.
- How much does data migration cost?
- Costs range from $20,000 for a straightforward single-database migration to $500,000 or more for enterprise-scale projects involving multiple systems, large volumes, and complex transformation requirements. The biggest cost variables are data quality, schema complexity, and whether you need zero-downtime migration. A discovery phase gives you an accurate estimate before committing.
- What is the difference between data migration and data integration?
- Data migration is a one-time (or periodic) transfer of data from one system to another. Data integration is an ongoing connection that keeps data synchronised between systems in real time or on a schedule. Many projects involve both: migrating historical data and then setting up integration to keep it current going forward.
Ready to get a quote on your data migration?
Tell us what you are building and we will put together a scoped proposal within 3 business days. Here is what happens when you reach out:
- 1You fill in the short project brief form (takes 5 minutes).
- 2We review it and come back with initial thoughts within 24 hours.
- 3We schedule a 30 minute call to align on scope, timeline, and budget.
- 4You receive a written proposal with fixed price options.
No commitment required until you are ready. Request your free data migration quote now.
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