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Data migration options
Whether you are running Informatica, Talend, SSIS, or Alteryx, the decision of how to modernise is as important as the decision to modernise at all.
Three paths out of legacy ETL
Moving forward, you have three main options: manual rewrite, LLM accelerators, and an AI-native, automated migration. Each produces a different outcome, on a different timeline, with a different level of risk.
Let’s compare them.
Manual rewrite
Engineers read, interpret, and rewrite your legacy pipelines by hand. This is thorough in principle, but slow, typically taking 12 to 18 months for a complex enterprise estate.
It also depends on finding and retaining engineers who understand both the legacy platform and the target stack.
LLM accelerators
Engineers read, interpret, and rewrite your legacy pipelines by hand. This is thorough in principle, but slow, typically taking 12 to 18 months for a complex enterprise estate.
It also depends on finding and retaining engineers who understand both the legacy platform and the target stack.
AI-native migration
Flowline, Infinite Lambda’s end-to-end modernisation solutions, is purpose-built for Informatica PowerCenter and IDMC, Talend, SSIS, Alteryx, and other legacy systems.
It converts the legacy code, handles the validation and refactoring, and produces a first-pass business ontology in one continuous engagement.
Compare your options
Your data migration options at a glance
An AI-native, automated approach changes the economics of migration across every dimension that matters.
| Capability | Manual rewrite | LLM accelerators | Flowline |
|---|---|---|---|
| Timeline | Manual rewrite12–18 months | LLM accelerators6–12 months | FlowlineWeeks |
| ETL conversion | Manual rewriteFull rewrite, line by line | LLM acceleratorsTrial-and-error, pipeline by pipeline | FlowlineComprehensive, holistic: entire legacy system |
| Validation | Manual rewriteManual, error-prone | LLM acceleratorsNeeds additional tooling | FlowlineRow-level, accelerated, assured |
| Sequencing | Manual rewriteManual, error-prone | LLM acceleratorsNot handled | FlowlineAutomatic: avoids breaking changes and bottlenecks |
| Code quality | Manual rewriteVaries, inconsistent | LLM acceleratorsTranslated, inconsistent | FlowlineBest practices baked in via proprietary agent skills |
| Multi-platform | Manual rewritePer-platform, manual | LLM acceleratorsLLM-training dependent | FlowlinePurpose-built for PowerCenter, IDMC, SSIS, Talend |
| Semantics for AI/BI | Manual rewriteYes (manual) | LLM acceleratorsNo | FlowlineProto-ontology + full semantic model |
| Ongoing management | Manual rewriteHumans, indefinitely | LLM acceleratorsNo | FlowlineAutonomous: Flowline agents manage it forever |
The dimensions that matter most for AI readiness
If you have already done a migration evaluation, it has likely focused on timeline and cost.
While they are both crucial points, there are other dimensions that are equally important but often underestimated. They are also the ones that determine whether your migration actually enables AI at scale.
- Sequencing: a migration that does not handle dependency order automatically introduces risk at every step. Pipelines that move in the wrong order break downstream consumers, and fixing that manually costs more time than the conversion saved.
- Semantics for AI and BI: a migration that does not produce a semantic output leaves your organisation with a modern stack but no business context layer. Your agents still cannot reason reliably on your data.
- Ongoing management: a platform that still requires humans to manage it indefinitely has not solved the operational overhead problem. Flowline agents manage the estate autonomously after cutover.
Flowline vs manual rewrite
Manual rewrites are thorough, but at 12 to 18 months and a large team, they are rarely practical for a complex enterprise estate. Every line of code is rewritten by hand, validation is error-prone, and the business logic buried in your legacy jobs stays buried. Flowline does the same work in weeks, with deterministic coverage and an ontology to show for it.
Flowline vs LLM accelerators
LLM accelerators can speed up individual pipeline conversions, but they work pipeline by pipeline, with no handling of dependency sequencing and no built-in validation.
That means more time spent on coordination, more risk at cutover, and no semantic output at the end of it. Flowline takes the whole estate in one continuous motion: automated sequencing, row-level reconciliation, and a proto-ontology as a byproduct. The result is a migration that is faster, lower-risk, and leaves you with something an LLM accelerator never produces: a foundation your AI agents can actually reason on.
Purpose-built for the platforms you are leaving behind
Flowline has purpose-built conversion logic for Informatica PowerCenter, Informatica IDMC, Talend, SSIS, and Alteryx, with more being added as we speak.
Each platform embeds business logic differently. Flowline understands the structure of each one and converts with that knowledge built in, rather than applying a generic translation layer and leaving the gaps to your engineers.
Need more details?
Explore the path from your ETL system to the modern stack.
What you get beyond migration
Every legacy ETL estate contains business logic that was never meant to be shared or reasoned over. It lives in mappings, transformation rules, and job configurations.
As Flowline converts your estate, it reverse-engineers that logic and produces a first-pass business ontology: a structured map of your organisation's concepts, entities, and metric definitions. This becomes the foundation for your semantic layer and the business context your AI agents need. Neither a manual rewrite nor an LLM accelerator produces this as a byproduct.
AstraZeneca migrating a global data estate with Flowline
Data modernisation cost
Infinite Lambda’s Flowline modernises your legacy ETL system in a fully predictable way in terms of both time and budget.
The price of a migration depends on complexity, volume, and stack.
If you want to see where you stand, what it would take to modernise and how it compares to what you are currently spending on infrastructure, take our 5-minute self-assessment. It will give you a clear picture and help build your modernisation business case.
See Flowline in action.
Reach out and we will show you what Flowline finds on a legacy estate like yours and give you a quote.
We start with a Flowline crawl of your existing estate to map what you have, identify what needs to move, and give you a clear picture of the migration scope. No commitment on your side.
Success Stories
We work with modern organisations to strategise and build cutting-edge solutions, help them adopt data & AI innovation, and nurture key competencies for scaling in the long run.