Your Migration Solution

The time to experience the benefits of the cloud is now—and LeapLogic makes migration possible, no matter your business workflows or needs

Explore the transformation potential in your business

What is your legacy source?
Pick your legacy data warehouse, ETL, or analytics system
ANY
ANY
What is your cloud destination?
Pick your target destination

Discover the power of smarter, faster transformation from Teradata

LeapLogic assesses and transforms diverse Teradata scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption

/ Source scripts
  • Stored procedures
  • DML and DDL
  • Shell scripts and macros
  • BTEQ, TPT, MultiLoad, FastLoad, FastExport, etc.
/ ETL scripts
  • Informatica, DataStage, Ab Initio, ODI
/ Analytics scripts
  • SAS, etc.
/ Logs
  • Assessment of EDW execution and application
/ Orchestration
  • Control-M, AutoSys, EPS, Cron Shell, etc.

Discover the power of smarter, faster transformation from Netezza

LeapLogic assesses and transforms diverse Netezza scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption

/ Source scripts
  • Stored procedures
  • DML and DDL
  • Shell
  • NZ SQL, Export/Load, etc.
/ ETL scripts
  • Informatica, DataStage, Ab Initio, ODI
/ Analytics scripts
  • SAS, etc.
/ Logs
  • Assessment of EDW execution
/ Orchestration
  • Control-M, AutoSys, EPS, Cron Shell, etc.

Discover the power of smarter, faster transformation from Oracle

LeapLogic assesses and transforms diverse Oracle scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption

/ Source scripts
  • Stored procedures
  • DML and DDL
  • Shell
  • PLSQL, SQL Loader/Spool, etc.
/ ETL scripts
  • Informatica, DataStage, Ab Initio, ODI
/ Analytics scripts
  • SAS, etc.
/ Logs
  • Assessment of EDW execution
/ Orchestration
  • Control-M, AutoSys, EPS, Cron Shell, Airflow, etc.

Discover the power of smarter, faster transformation from SQL Server

LeapLogic assesses and transforms diverse SQL Server scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption

/ Source scripts
  • Stored procedures
  • DML and DDL
  • Shell scripts with embedded SQL Server blocks
  • TSQL, etc.
/ ETL scripts
  • Informatica, DataStage, Ab Initio, ODI
/ Analytics scripts
  • SAS, etc.
/ Logs
  • Assessment of EDW execution logs
/ Orchestration
  • Control-M, AutoSys, EPS, Cron Shell, Airflow, etc.

Discover the power of smarter, faster transformation from Vertica

LeapLogic assesses and transforms diverse Vertica scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption

/ Source scripts
  • DDL
  • Shell
  • VSQL, Load, Export
/ ETL scripts
  • Informatica, DataStage, Ab Initio, ODI
/ Analytics scripts
  • SAS, etc.
/ Logs
  • Assessment of EDW execution
/ Orchestration
  • Control-M, AutoSys, EPS, Cron Shell, etc.

Discover the power of smarter, faster transformation from Informatica

LeapLogic assesses and transforms diverse Informatica code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption

  • Assesses XML files
  • Converts workflows and mappings to:
  • Cloud-native ETL: AWS Glue, Azure Data Factory, Google Dataflow, Cloud Data Fusion, etc.
  • Cloud-native warehouses: Databricks Lakehouse, Amazon Redshift, Azure Synapse, Google BigQuery, Snowflake
  • Open collaboration–based languages: PySpark, PyScala
  • Converts schema and maps data types for migration to the cloud or Hadoop

Discover the power of smarter, faster transformation from Datastage

LeapLogic assesses and transforms diverse Datastage code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption

  • Assesses XML/DSX files
  • Converts jobs and components to:
  • Cloud-native ETL: AWS Glue, Azure Data Factory, Google Dataflow, Cloud Data Fusion, etc.
  • Cloud-native warehouses: Databricks Lakehouse, Amazon Redshift, Azure Synapse, Google BigQuery, Snowflake
  • Open collaboration–based languages: PySpark, PyScala
  • Provides comprehensive ETL conversion reports
  • Converts schema and maps data types for migration to the cloud or Hadoop

Discover the power of smarter, faster transformation from
Ab Initio

LeapLogic assesses and transforms diverse Ab Initio code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption

  • Assesses ETL scripts/jobs
  • Converts ETL scripts/jobs to:
  • Cloud-native ETL: AWS Glue, Azure Data Factory, Google Dataflow, Cloud Data Fusion, etc.
  • Cloud-native warehouses: Databricks Lakehouse, Amazon Redshift, Azure Synapse, Google BigQuery, Snowflake
  • Open collaboration-based languages like PySpark, PyScala
  • Provides comprehensive ETL conversion reports
  • Converts schema and maps data types for migration to the cloud or Hadoop

Discover the power of smarter, faster transformation from SAS

LeapLogic assesses and transforms diverse SAS analytical scripts, so you can feel the freedom of the cloud quickly, with lower risk of disruption

  • Scripts and procedures
  • Macros, scheduler jobs, ad hoc queries
  • Constructs, functions, keywords, etc.
  • SAS-purposed ETL/data prep/procedural logic
  • Assessment of execution logs

Discover the power of smarter, faster transformation from Hadoop

LeapLogic assesses and transforms diverse Hadoop workloads, so you can feel the freedom of the cloud quickly, with lower risk of disruption

  • Assesses HQL and Spark SQL queries
  • Provides actionable recommendations for Amazon EMR, Azure HDInsight, GCP Dataproc, and Snowflake
  • Converts Hive queries to:
  • Presto query engine
  • Cloud data warehouse equivalent like Redshift SQL, Azure Synapse SQL, BigQuery SQL, SnowSQL
  • Migrates:
  • Data to Amazon S3 buckets/Azure Data Lake or Blob Storage/Google Cloud Storage/Snowflake
  • On-premise user base to AWS/Azure/GCP/Snowflake roles and policies
  • Operationalizes workloads in the target environment:
  • Provisioning through Infrastructure as Code on Amazon EMR or EC2, Azure HDInsight, Dataproc, Snowflake
  • Performance optimization to meet target SLAs

Meet your accelerated migration to AWS

With LeapLogic, your transformation to AWS will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

/ Assessment
  • Say yes to key questions
  • Can I identify anti-patterns in my existing code and resolve as per AWS coding techniques and standards?
  • Will it make sense to design my future-state architecture using all AWS-native services (for orchestrating, monitoring, etc.)?
  • Will I know which workloads can benefit from EMR vs. Redshift cloud data warehouses?
  • Can I save provisioning and maintenance costs for rarely used workloads on AWS?
  • Data warehouse
  • Can I get schema optimization recommendations for distribution style and distkeys, sort keys?
  • ETL
  • Will the assessment help me choose AWS services for meeting ETL SLAs?
  • Analytics
  • Will it be beneficial to convert analytical functions to Spark ML-based libraries?
  • Will my ETL processing SLAs impact my choice of an optimum Amazon EMR cluster size?
  • Hadoop
  • Is my optimization strategy for Update/Merge on AWS Redshift apt?
  • Can I get schema optimization recommendations for partitioning, bucketing, clustering etc.?
/ transformation
  • Packaging and orchestration using AWS-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse – Amazon EMR, Amazon Redshift, Snowflake on AWS
  • ETL – AWS Glue, Amazon Redshift, PySpark/Scala + Spark
  • Analytics – Amazon EMR, PySpark/Scala + Spark
  • Hadoop – Amazon Redshift, Snowflake on AWS, 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
  • Data warehouse – Provisioning of Amazon EMR/Amazon EC2/AWS Redshift/Snowflake, and other AWS services for orchestration, monitoring, security etc.
  • ETL – Provisioning of AWS Glue and other required services
  • Analytics – Provisioning of Amazon EMR and other required services
  • Hadoop – Provisioning of Redshift/Snowflake on AWS and other required services

Meet your accelerated migration to Azure

With LeapLogic, your transformation to Azure will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

/ Assessment
  • Say yes to key questions
  • Can I identify anti-patterns in my existing code and resolve as per Azure coding techniques and standards?
  • Will it make sense to design my future-state architecture using all Azure-native services (for orchestrating, monitoring, etc.)?
  • Will I know which workloads can benefit from HDInsight vs. Synapse cloud data warehouses?
  • Can I save provisioning and maintenance costs for rarely used workloads on Azure?
  • Data warehouse
  • Can I get schema optimization recommendations for distribution style, indexing techniques, partitioning etc.?
  • ETL
  • Will the assessment help me choose Azure services for meeting ETL SLAs?
  • Analytics
  • Will it be beneficial to convert my analytical functions to Spark ML-based libraries?
  • Will my ETL processing SLAs impact my choice of an optimum Azure HDInsight cluster size?
  • Hadoop
  • Is my optimization strategy for Update/Merge on Azure Synapse apt?
  • Can I get schema optimization recommendations for partitioning, bucketing, clustering etc.?
/ transformation
  • Packaging and orchestration using Azure-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse – Azure HDInsight, Azure Synapse, Snowflake on Azure
  • ETL – Azure Data Factory, Azure Synapse, PySpark/Scala + Spark
  • Analytics – Azure HDInsight, PySpark/Scala + Spark
  • Hadoop – Azure Synapse, Snowflake on Azure, 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
  • Data warehouse – Provisioning of ADLS/HDInsight/Synapse/Snowflake, and other Azure services for orchestration, monitoring, security etc.
  • ETL – Provisioning of Azure Data Factory and other required services
  • Analytics – Provisioning of Azure HDInsight and other required services
  • Hadoop – Provisioning of Synapse/Snowflake on Azure and other required services

Meet your accelerated migration to GCP

With LeapLogic, your transformation to GCP will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

/ Assessment
  • Say yes to key questions
  • Can I identify anti-patterns in my existing code and resolve as per GCP coding techniques and standards?
  • Will it make sense to design my future-state architecture using all GCP-native services (for orchestrating, monitoring, etc.)?
  • Can I save provisioning and maintenance costs for rarely used workloads on GCP?
  • Data warehouse
  • Can I get schema optimization recommendations for partitioning, bucketing, clustering, etc.?
  • ETL
  • Will the assessment help me choose GCP services for meeting ETL SLAs?
  • Analytics
  • Will it be beneficial to convert my analytical functions to Spark ML-based libraries?
  • Will my ETL processing SLAs impact my choice of an optimum Dataproc cluster size?
  • Hadoop
  • Is my optimization strategy for Update/Merge on BigQuery apt?
/ transformation
  • Packaging and orchestration using GCP-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse – BigQuery, Dataproc, Snowflake on GCP
  • ETL – Cloud Data Fusion, Dataflow, Dataproc, PySpark/Scala + Spark
  • Analytics – Dataproc, PySpark/Scala + Spark
  • Hadoop – BigQuery, Snowflake on 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 cut-over planning
  • Infrastructure as code
  • CI/CD
  • Data warehouse – Provisioning of Dataproc/BigQuery/Snowflake, and other GCP services for orchestration, monitoring, security etc.
  • ETL and analytics – Provisioning of Cloud Data Fusion, Dataflow, Dataproc and other required services
  • Hadoop – Provisioning of BigQuery/Snowflake on GCP and other required services

Meet your accelerated migration to Snowflake

With LeapLogic, your transformation to Snowflake will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

/ Assessment
  • Say yes to key questions
  • Can I identify anti-patterns in my existing code and resolve as per Snowflake coding techniques and standards?
  • Will it make sense to design my future-state architecture using all Snowflake-cloud–native services (AWS/Azure/GCP) for orchestrating, monitoring, etc.?
  • What should be the optimum auto-scaling rule for my Snowflake cluster based on my reporting needs?
  • Data warehouse
  • Can I get schema optimization recommendations for partitioning, bucketing, clustering, etc.?
  • ETL
  • Will my ETL processing SLAs impact my choice for an optimum Snowflake cluster size?
  • Hadoop
  • Is my optimization strategy for Update/Merge apt for Snowflake on AWS/Azure/GCP?
/ transformation
  • Packaging and orchestration using Snowflake-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse – Snowflake on AWS/Azure/GCP
  • ETL – Snowflake on AWS/Azure/GCP
  • Hadoop – Snowflake, 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 Snowflake and other required services

Meet your accelerated migration to Databricks

With LeapLogic, your transformation to Databricks will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

/ Assessment
  • Say yes to key questions
  • Can I identify anti-patterns in my existing code and resolve as per Databricks Lakehouse coding techniques and standards?
  • 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, bucketing, clustering, 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?
/ transformation
  • Packaging and orchestration using Databricks-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse and ETL – Databricks Lakehouse on AWS/Azure/GCP
  • Analytics – Databricks Lakehouse on AWS/Azure/GCP, PySpark/Scala + Spark
  • Hadoop – 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

Meet your accelerated migration to Spark

With LeapLogic, your transformation to Spark (Hadoop) will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

/ Assessment
  • Say yes to key questions
  • Can I identify anti-patterns in my existing code and resolve as per Hadoop’s coding techniques and standards?
  • Will I know if I can meet my SLAs through Spark or if I need cloud-native warehouses?
  • Data warehouse
  • Can I get schema optimization recommendations for partitioning, bucketing, clustering, etc.?
  • ETL
  • Will my ETL processing SLAs impact my choice for an optimum Hadoop cluster size?
  • Analytics
  • Will it be beneficial to convert my analytical functions to Spark ML-based libraries?
/ transformation
  • Packaging and orchestration using Hadoop-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse – Hadoop (Spark SQL and HQL), Python/Scala/Java
  • ETL – Hadoop (Spark SQL and HQL), Python/Scala/Java, Amazon EMR/Azure HDInsight/Dataproc
  • Analytics – Hadoop (Spark SQL and HQL)
/ 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
  • Data warehouse – Provisioning on Hadoop and Hive, and of other services for orchestration, monitoring, security etc.
  • ETL – Provisioning on Hadoop/Hive/Amazon EMR/Azure HDInsight/Dataproc
  • Analytics – Provisioning on Hadoop

Please choose at least one specific source or destination

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Explore real results

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

CASE STUDY

50% cost and time savings when transforming Informatica workflows and Oracle EDW to AWS

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Transform your workload, transform your reality