Accelerated migration to Databricks

Accelerate your ETL, analytics, Hadoop, and data warehouse migration and transformation to Databricks with LeapLogic

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Explore the transformation potential in your business
with Databricks

/ Assessment
  • Get answers to key questions
  • Will it make sense to design my future-state architecture using all cloud-native services (for orchestrating, monitoring, etc.)?
  • Will I know if I can meet my SLAs through Databricks Lakehouse or if I need cloud-native warehouses?
  • Data warehouse
  • Can I get schema optimization recommendations for partitioning, bloom filters, ZOrder indexing,, etc.?
  • ETL
  • Will my ETL processing SLAs impact my choice for an optimum Databricks cluster size?
  • Can I save provisioning and maintenance costs for rarely used workloads on Databricks?
  • Hadoop
  • Is my optimization strategy for Update/Merge on Databricks apt?
  • Analytics
  • Can I transform my analytics layer as well along with my data warehouse, ETL systems, and BI?
  • BI/Reporting
  • Can I use the processed data from my modern cloud-native data warehouse stack for my BI/reporting needs and leverage it with a modern BI stack?
/ transformation
  • Packaging and orchestration using Databricks-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse and ETL to Databricks migration – Databricks Lakehouse, Databricks Notebook, Databricks Jobs, Databricks Workflows, Delta Lake, Delta Live Tables
  • Analytics to Databricks migration – Databricks Lakehouse on AWS/Azure/GCP, PySpark
  • Hadoop to Databricks migration – Databricks Lakehouse on AWS/Azure/GCP, Presto query engine
/ validation
  • All transformed data warehouse, ETL, analytics, and/or Hadoop workloads
  • Business logic (with a high degree of automation)
  • Cell-by-cell validation
  • Integration testing on enterprise datasets
/ operationalization
  • Capacity planning for optimal cost-performance ratio
  • Performance optimization
  • Robust cutover planning
  • Infrastructure as code
  • CI/CD
  • Provisioning of Databricks Lakehouse and other required services

Automated workload transformation from Informatica to Databricks

Automated Teradata data warehouse migration to Databricks

Automated workload transformation from SAS to Databricks

Automated workload transformation from Hadoop to Databricks


Explore resources to support your transformation initiatives

Case Study

30% performance improvement by converting Netezza and Informatica to Azure-Databricks stack

Case Study

20% SLA improvement by modernizing Teradata workloads on Azure


Automated legacy ETL, Hadoop, analytics, and data warehouse platform migration to Databricks


Learn more about these benefits and best practices for cloud-native transformation