Data synchronization cut from a full day to minutes: a secure rebuild for a large-data platform
A confidential technology company was running a slow, vulnerable product on Svelte and Firebase. Over a 12-month rebuild, Rollout IT replaced the data architecture, added a real backend, and turned a daily synchronization bottleneck into a process the product can rely on.
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Snapshot
| Field | Detail |
|---|---|
| Client | Confidential technology company (anonymized) |
| Industry | Technology, data-intensive application |
| Company stage | Existing product under scaling pressure |
| What we built | Frontend migration, backend rebuild, data pipeline, and security hardening |
| Tech stack | React, PostgreSQL, hosted proxy, self-managed VMs, Stripe, automated deployment |
| Time-to-value | 12-month project |
| Headline KPIs | Sync cut from a full day to minutes – security gaps closed – pipeline cleaned and deduplicated |
The challenge
The client had an application that was hard to trust at scale. The frontend ran on Svelte, while Firestore was being stretched into backend duties it was never built for. The result was lag, security exposure, and unreliable handling of large external datasets. Noisy data sources made it worse: information had to be filtered, cleaned, synchronized, and monitored before it could support the product at all. Left alone, the architecture would have capped growth and kept the security risk live.
Why the client chose Rollout IT
The project needed a partner willing to stabilize before scaling, not bolt features onto a shaky base. Rollout IT was chosen to own the foundations: proper backend ownership, safer data handling, an incremental frontend migration, and operational tooling the client's team could maintain after delivery.
The solution
We migrated the frontend from Svelte to React incrementally, which cut disruption while producing a more maintainable codebase. On the backend, we replaced the Firestore-as-backend setup with PostgreSQL and a dedicated service layer, separating application logic from storage and closing the security gap that the missing backend had created.
We then redesigned the data pipeline to filter irrelevant records, remove duplicates and errors, and synchronize external sources far more efficiently. A hosted proxy handled sources unavailable from Europe, and selected infrastructure moved to self-managed VMs to reduce IP-ban risk. To keep the system healthy long term, we added logging, fault tolerance, automated testing, automated deployments, and Stripe subscription integration. As a partner, Rollout IT took on the maintainability and security burden that the internal team could not carry alone, and left a system that is easier to monitor, debug, and extend.
Results
- Large-data synchronization dropped from a full day to several minutes.
- The security vulnerabilities caused by the missing backend layer were eliminated.
- A cleaned, deduplicated pipeline gave the product a dependable data foundation.
| Metric | Before | After | Timeframe |
|---|---|---|---|
| Data synchronization | Full day / several hours | Several minutes | 12-month project |
| Backend security | Firestore as backend, multiple vulnerabilities | Dedicated backend, safer auth and data handling | Rebuild phase |
| Data quality | Duplicates, errors, irrelevant records | Cleaned and filtered pipeline | Rebuild phase |
| Maintainability | Early-stage Svelte/Firebase constraints | React plus PostgreSQL architecture | 12-month project |
*Data agreed with the client. Client anonymized under NDA.*
The AI angle
No AI capability is claimed here. The business value is data reliability: faster synchronization, cleaner data, and stronger security add up to a product foundation the client can build on.
What's next
With the foundation stable, the natural next step is to quantify the operational upside: reduced support incidents, shorter debugging cycles, deployment frequency, and the subscription-revenue impact of the new Stripe integration. Rollout IT remains available to instrument and report those gains.
FAQ
What was the main result of the rebuild? Large-data synchronization went from taking a full day to completing in minutes, on a more secure and maintainable architecture.
Why replace Firebase/Firestore? Firestore was being used as a backend it was not designed for, which caused lag and security exposure. A dedicated backend on PostgreSQL closed that gap.
How long did the project take? A 12-month engagement covering the frontend migration, backend rebuild, data pipeline, and security work.
Can Rollout IT work on a confidential, NDA-covered product? Yes. This client is anonymized; the results are published with the client's agreement.
If data volume, legacy architecture, or security risk is slowing your product, book a rebuild consultation.