SparkLake migrates enterprises off expensive Informatica licenses and aging RDBMS warehouses onto Databricks and Azure Data Factory — cutting costs dramatically while unlocking modern, scalable data infrastructure.
Every quarter you stay on Informatica or an aging RDBMS warehouse, your competitors on modern platforms pull further ahead.
Informatica’s per-connector, per-core licensing model means costs scale with your data volume — not your value. Most enterprises overpay by 300–500% for pipelines that could run for a fraction of the price on open architecture.
Avg. $800K–$2M/yr in licensesTraditional row-based SQL warehouses weren’t built for petabyte-scale analytics. Your data teams spend more time tuning indexes and managing capacity than delivering business insights.
10–100× slower than columnar alternativesProprietary ETL tools create deep coupling between your business logic and a single vendor. Migrations become multi-year projects — giving vendors enormous leverage at renewal time.
Average 3.5 yr contract lock-inYour best engineers are babysitting fragile pipelines instead of building new capabilities. Legacy infrastructure consumes 60–70% of data team capacity just to keep the lights on.
~65% of team time on maintenanceSparkLake replaces your legacy stack with a proven, open-source architecture built on Databricks and Azure Data Factory.
What We Replace
We assess your existing pipelines, data models, and dependencies before writing a single line of code. No surprises mid-project.
Our tooling converts Informatica mappings and workflows to ADF pipelines and Spark notebooks at speed — dramatically reducing manual effort and human error.
We run legacy and modern systems in parallel until data parity is confirmed — then execute a zero-downtime cutover on your timeline.
Your engineering team gets hands-on training and documentation so they own the new platform from day one. No black-box handoffs.
A structured methodology that de-risks the migration at every stage.
We inventory every pipeline, mapping, data source, and dependency in your current environment. You receive a full migration roadmap with effort estimates and risk flags before any commitment to proceed.
Automated conversion of Informatica workflows to ADF pipelines and Databricks notebooks, followed by rigorous data reconciliation testing. Legacy and new systems run in parallel throughout.
Zero-downtime cutover to the new platform on your schedule. Post-migration we tune performance, establish monitoring, and enable your team to fully own and extend the new stack.
Databricks and Azure Data Factory aren’t just cheaper — they’re faster, more capable, and future-proof.
Eliminate per-core and per-connector licensing. Pay only for compute you actually use with auto-scaling clusters.
Databricks’ columnar Delta Lake format and Photon engine deliver order-of-magnitude improvements over legacy RDBMS warehouses.
Delta Lake, Parquet, and Apache Spark are open-source. Your data and logic are portable — no vendor lock-in, ever.
Auto-scaling clusters handle petabyte workloads on demand. No more capacity planning or weekend maintenance windows.
Databricks Unity Catalog and MLflow give your data science teams the governed, centralized foundation they need for production ML.
ADF integrates natively with your existing Azure services — Synapse, Purview, Key Vault, and 90+ built-in connectors out of the box.
Tell us about your current environment. We’ll come back within 48 hours with a high-level migration scope, estimated cost savings, and a proposed timeline — at no cost or obligation.