You bet on last decade's stack. The bill is now due.
Synapse, dedicated SQL pools, monolithic warehouses, on-prem Hadoop. The architecture that worked in 2018 is the bottleneck of 2026.
Synapse Dedicated Pools at capacity ceiling, AI workloads can't run, cloud bill grows faster than data. Fix it with a wave migration to Microsoft Fabric + OneLake + FinOps. 28% lower cloud bill, AI-ready foundation in zero downtime.
If half of these sound familiar, this is your fight.
No formal assessment needed, just an honest look at the daily friction.
Your warehouse can't keep up with the data you collect today.
Adding a new source means a multi-quarter integration project.
You're paying for capacity that's idle 80% of the time.
Your data engineers spend more time tuning than building.
Every new use case requires a new tool, a new licence and a new training plan.
Cloud bills grow faster than data volume.
Why it happens
Locked-in architecture
Choices made in 2018 (dedicated pools, proprietary formats, custom ETL) now constrain every new initiative.
No separation of storage and compute
Old patterns force you to scale both together, so you over-provision one to satisfy the other.
No platform thinking
Every new project bolts on its own toolchain, which compounds technical debt and operational cost.
What it costs you
Slow time-to-market
New initiatives wait six months for capacity, integration and security review, before any business value lands.
Cloud bill creep
Idle capacity, redundant copies, unsuspected data egress: waste that compounds quarter on quarter.
AI ceiling
GenAI and agentic workloads need OneLake-style storage with separated compute. Old stacks simply can't serve them.
The shortest path from problem to results.
Microsoft-first stack. Belgian and Estonian engineering. Senior team kickoff through delivery to support.
Microsoft Fabric backbone
OneLake, separated compute, open Delta format: the architecture standard for the next decade.
See solutionMigration roadmap with shortcuts
Move incrementally. Use Fabric shortcuts to keep operations running while you re-platform.
See solutionFinOps & capacity tuning
Right-size capacity, enforce auto-pause, govern workloads, so the bill matches the value.
See solutionWhen a Synapse-only stack moved to Fabric without downtime.
Synapse → Fabric · zero-downtime migration
A Belgian retailer with a Synapse Dedicated SQL Pool hitting capacity ceiling. We moved to Microsoft Fabric with OneLake shortcuts, kept Synapse running during transition, migrated workloads in waves. New AI initiatives now ship in weeks, not quarters. Cloud bill down 28% on first quarter.
Future-proof your data before the next bill arrives.
Free 60-minute architecture review: we'll show you the highest-impact moves.
Common questions, direct answers.
Why move from Synapse to Fabric?
Fabric is the SaaS evolution of Synapse: same underlying engine, different operating model. Separate compute, OneLake, integrated Power BI + AI. Microsoft's 2025+ investment is in Fabric, not Synapse Dedicated.
Should we move from Snowflake or Databricks too?
Snowflake/Databricks are excellent. Don't migrate just for the sake of it. Move when (a) AI workloads need OneLake, (b) Power BI Direct Lake gives you 10x performance, or (c) cost savings clear a 9-month payback.
What about lock-in to Microsoft?
Fabric uses open Delta Lake format. Your data leaves with you. The lock-in is on engineering practices, not the data layer. Compare to Snowflake or Databricks: same dynamic.
How long does a wave migration take?
Three to six months for a typical estate (10-50TB). First wave (one business domain) in eight weeks. Then expand 1-2 waves per quarter.
How do we manage cloud cost during migration?
FinOps from day one: tagging policy, capacity governance, auto-pause, anomaly detection. Most customers see cost flat-lining or dropping during migration, because old and new run in parallel for only the migration window.