Cloud Data Migration: Zero-Downtime Moves to Modern Platforms
Legacy warehouses, on-prem SQL Server clusters, aging Hadoop environments — they all need to move. The question isn't whether to migrate. It's how to do it without breaking production, losing data integrity, or burning 6 months on rework.
Platform-to-Platform
SQL Server → Fabric, Oracle → Snowflake, Hadoop → Databricks, Synapse → Fabric
Zero-Downtime Strategy
Parallel run, phased cutover, rollback plans, and data validation gates
Data Integrity Validation
Row-count reconciliation, hash comparisons, business-logic regression testing
Post-Migration Optimization
Performance tuning, cost optimization, and monitoring setup on the new platform
The migration problem isn't technical. It's architectural.
Most cloud data migrations fail not because the tools don't work, but because the migration plan doesn't account for the architecture gap between the old platform and the new one. Moving tables from SQL Server to Snowflake isn't a lift-and-shift — it's a re-architecture of storage patterns, query optimization, security models, and pipeline orchestration.
The biggest risk is the 6-month stall. Teams start migrating, hit unexpected complexity (stored procedure translation, performance regression, data type mismatches), and the project slides from "3 months" to "12 months with a consultant staff shortage." By then, the business case has eroded and stakeholders have lost confidence.
Xylity's approach starts with architecture assessment — mapping every source system, dependency chain, and downstream consumer before writing a single migration script. We match specialists who've completed the exact platform-to-platform migration path your project requires: Synapse to Fabric, Oracle to Snowflake, Hadoop to Databricks, or any combination in between.
Cloud data migration capabilities
Every migration engagement is led by specialists who've completed the exact source-to-target platform move your project requires — not generalists learning on your timeline.
Migration Assessment & Planning
Complete inventory of source systems, table dependencies, stored procedures, ETL jobs, and downstream consumers. Gap analysis between source and target platforms. Migration roadmap with parallel-run strategy, rollback plans, and resource requirements.
Schema & Data Model Conversion
Translating schemas, data types, constraints, and indexes from legacy platforms to cloud-native formats. This isn't one-to-one mapping — it's re-architecture to leverage the target platform's strengths: columnar storage, partitioning strategies, and native compression.
Stored Procedure & Logic Translation
The hardest part of most migrations. Converting T-SQL, PL/SQL, or BTEQ logic to the target platform's query language and execution model. Our specialists handle complex procedure chains, cursor-based logic, and performance-sensitive transformations.
Data Transfer & Pipeline Migration
Bulk data transfer using platform-native tools (ADF, Snowpipe, Databricks Auto Loader) with incremental sync for near-zero downtime. Pipeline migration from legacy ETL tools (SSIS, Informatica, Talend) to cloud-native orchestration.
See ETL development →Validation & Reconciliation
Row-count reconciliation, hash-based data comparison, business-logic regression testing, and performance benchmarking. We validate not just that data arrived — but that it produces the same business results as the source system.
Post-Migration Optimization
Performance tuning, cost optimization (warehouse sizing, compute auto-scaling, storage tiering), monitoring setup, and runbook creation. The migration isn't done at cutover — it's done when the new platform outperforms the old one.
Common source-to-target platform migrations
SQL Server → Fabric
On-prem SQL to Fabric warehouse and lakehouse, including SSIS to Fabric pipelines
Synapse → Fabric
Dedicated SQL pools to Fabric warehouse, ADF to Fabric pipelines, ADLS to OneLake
Oracle → Snowflake
PL/SQL translation, RAC to virtual warehouse, Exadata to Snowflake Data Cloud
Hadoop → Databricks
HDFS to Delta Lake, Hive to Databricks SQL, MapReduce to Spark jobs
Teradata → Cloud
BTEQ translation, workload migration, stored procedure conversion to any target
Netezza → Snowflake
Zone maps to clustering keys, NZPLSQL to Snowflake SQL, data distribution redesign
Redshift → Databricks
Redshift SQL to Spark SQL, Spectrum to Delta Lake, Glue to Databricks workflows
On-Prem → Multi-Cloud
Any on-premises data warehouse to Azure, AWS, or GCP cloud data platform
Migration specialists matched to your exact platform path
Architecture Assessment
We map your source platform, target platform, data volumes, dependencies, and migration constraints. The matching starts from your specific migration path.
Specialist Matching
Consultants matched for your exact source-to-target move. Oracle-to-Snowflake experience isn't the same as SQL-to-Fabric. We evaluate against your specific scenario.
Migration Execution
Schema conversion, logic translation, data transfer, and parallel-run validation. Your migration specialist contributes from week one with a delivery manager ensuring continuity.
Validate & Optimize
Data reconciliation, performance benchmarking, and post-migration optimization. The engagement continues until the new platform outperforms the old one.
Migration expertise for enterprises and IT services companies
Planning a data platform migration but can't find specialists who've done it before?
Cloud data migration is high-stakes: production downtime, data integrity risks, and timeline overruns are the norm. Xylity matches architects and engineers who've completed the exact source-to-target migration path your project requires — not generalists who'll learn on your timeline. Our consulting-led approach starts with architecture assessment, not resume matching.
Start a Consulting Engagement →Client needs a cloud migration but your bench doesn't have platform-specific specialists?
Cloud migration projects require specialists with specific source-to-target experience — Oracle to Snowflake, Synapse to Fabric, Hadoop to Databricks. When your bench doesn't cover the specific migration path, Xylity's network delivers curated profiles from specialists who've done that exact move before. First profiles in an average of 4.3 days.
Scale Your Migration Delivery →Cloud data migration — answered
Your data platform migration deserves
specialists who've done it before.
Tell us about your source platform, target platform, and timeline. We'll match migration specialists with proven experience on your exact path.