Rigid Schemas Stop Fighting You
Move off tables that fight every schema change onto a flexible document model that matches how modern applications actually produce data.
Partners
Modernize Legacy Applications to MongoDB, with Flentas
Legacy relational databases and the applications built on them are where innovation goes to wait. Rigid schemas slow every change, and most of the budget goes to keeping the lights on. With MongoDB, Flentas modernizes legacy applications onto the flexible document model on MongoDB Atlas, using AI-powered tooling to move faster and with far less risk, delivered on AWS.
Key Benefits
Modernization, Not a Lift and Shift
The problem is rarely a single database. It is the accumulated technical debt around it — industry estimates put that debt at more than $1.5 trillion — and the way rigid data models slow everything downstream.
Technical Debt Actually Gets Paid Down
Most spend goes to keeping legacy systems running rather than building new capability. Modernization changes the data model, not just the hosting.
A Foundation Vector Search Can Use
Data locked in siloed relational systems cannot power retrieval-augmented generation. Atlas Vector Search makes the unified data AI-ready.
AI-Accelerated, Lower-Risk Migration
Relational Migrator and the Application Modernization Platform use AI to convert schemas, SQL, and stored procedures — automating the tedious, error-prone parts.
Proof Points
Up to 2/3Faster modernization timelines, reported by MongoDB
Up to 90%Less migration effort on some enterprise programs
$1.5T+Industry estimate of accumulated technical debt from legacy data platforms
How It Works
How We Deliver
We modernize iteratively, application by application, so value lands early and risk stays contained. There is no multi-year big-bang migration that stalls before it delivers.
1
Assess
We inventory the legacy estate, model the target document schema, and produce a prioritized modernization roadmap with a business case and a clear sequence.
2
Modernize
We migrate schema and data with Relational Migrator, refactor application code with AI assistance, stand up MongoDB Atlas on AWS, and test against the legacy system.
3
Operate
We run and optimize on Atlas, then extend the modern foundation into AI features such as vector search and retrieval-augmented generation.
Technology Stack
Technologies & Tools We Use
Modernization Assessment
Portfolio analysis of which applications to modernize first, dependencies between them, and the business case for each.
Schema & Data Migration
MongoDB Relational Migrator discovers the source schema, models the target document schema, and synchronizes data from Oracle, SQL Server, PostgreSQL, and more.
AI-Accelerated Refactoring
Automatic conversion of SQL queries and stored procedures to the MongoDB Query API, with application code generation for undocumented legacy logic.
MongoDB Atlas on AWS
A managed, secure, scalable Atlas environment on AWS, with the networking, security, and observability to run it in production.
AI Enablement
Atlas Vector Search makes the newly unified data ready for retrieval-augmented generation and other AI features.
Legacy Cost Reduction
Retire or offload expensive legacy database licences as workloads move to Atlas.
Use Cases
Industries & Scenarios We Serve
Oracle & Mainframe Offload
The most expensive and rigid legacy workloads targeted for a move to MongoDB Atlas on AWS.
Undocumented Legacy Logic
AI-assisted conversion rewrites stored procedures and SQL nobody fully documented, without a risky manual rewrite.
Applications Needing AI Features
Siloed relational data cannot support retrieval-augmented generation — modernization unlocks vector search as a byproduct.
Portfolios, Not Single Applications
A repeatable, assessment-led delivery model modernizes application by application, so a whole portfolio moves predictably.
Case Studies
Proof, Not Promises
500M+Events/Day Off a Legacy Analytics Estate
HPE needed a defined path off a costly legacy analytics estate. Flentas built a modern, cloud-agnostic data platform now processing more than 500 million events per day.
100%Of Reporting Migrated Without Disrupting Production
Cashew Payments needed live data migrated off its production database. Change-data-capture moved it into a modern, governed data lake on AWS with zero disruption.
“Every "simple" feature request turned into a two-week schema migration and a fight between three teams. We moved our core application to MongoDB with Flentas doing the modeling and the AI-assisted conversion of stored procedures nobody wanted to touch by hand. Regression testing that used to take us four days took four hours. That’s the number that got the rest of the roadmap approved.”
VP EngineeringSaaS Platform, AWS Estate
Get Started
Which Legacy Applications Should You Modernize First?
A modernization assessment maps your legacy estate, models the target on MongoDB, and hands you a prioritized plan with a business case — no obligation.
- AWS Advanced Consulting Partner
- 200+ Migrations Delivered
- 96.5% Client Retention