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dbReplika – High Volume Data Replication for SAP to Snowflake and Databricks

Modern Data Platforms Powered by SAP Integration

We specialize in building robust data platforms on SAP, cloud, and open-source ecosystems. Our innovative replication tool seamlessly integrates and transfers SAP data into modern cloud data platforms like Snowflake or Databricks, empowering businesses to harness actionable insights with ease with No-Code and 1-Click setup. Leverage our expertise to transform your data landscape and drive smarter decision-making. Let us help you bridge the gap between SAP and the cloud.
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      SAP BW 7.5, SAP S/4HANA and BW/4HANA compatible

      dbReplika enables you to replicate business rich SAP data sources and providers to your cloud platform of choice like Snowflake or Databricks. We Support on-premise SAP BW 7.5, SAP S/4HANA and BW/4HANA source systems without the need of any cloud subscription.
      Product Description

      Replication Options

      Managed by External Scheduler
      The triggering of a replication process is done through the execution of a docker image that accepts the login credentials to the SAP system, which triggers the data replication. This docker image can be run locally or in cloud and can be attached to most orchestration tools with ease. The docker image is part of the standard delivery package.
      Managed by SAP BW Scheduler
      If a customer would like to have an orchestration-free setup, we offer the possibility to transfer the data to targets like Snowflake and Databricks directly. Snowflake/Databricks will be configured to poll the new data. All API artefacts needed for the communication between SAP, Databricks or Snowflake are part of the standard delivery package.
      Performance Metrics
      Performance is influenced by the size of the records and the level of parallelization, which depends on the specific customer scenario. For instance, with a record size of 600 characters and 5 parallel jobs, it is possible to transfer approximately 100 million records in several minutes.
      Data Security
      dbReplika by design ensures that data never leaves the networks and systems of the customer. dbReplika runs as an SAP Add-on in the customer on-premise or SAP Private Cloud SAP system and doesn’t need any cloud subscription.

      Replication Features

      This set of features is included in the standard installation. We deliver up to 4 feature releases per year, so you can continuously expect new capabilities and enhancements tailored to your needs. Additionally we offer you 3 different support plans.
      Configuration
      The dbReplika GUI allows users to activate a datasource for replication in less than a minute!
      • Low-code & No-code reduced development costs
      • Low entry barrier for new team members
      • Ease of knowledge Transfer
      Delta
      dbReplika uses the standard BW Delta frameworks, thereby ensuring an SAP compliant delta by design!
      • All ODP Delta Datasources supported
      • Custom delta extractors supported
      • Recovery of prior delta states of requets
      Filters
      DTPs can be configured for partial replication of data by using the standard DTP filter capabilities!
      • Standard DTP filters are supported
      • DTP routines as filters are supported
      • Custom filter logic supported

      dbReplika vs. other Vendors

      Feature Matrix dbReplika Other Vendors
      1-Click replication setup   Yes   No
      Low-Code / No-Code Yes   Partially
      Cost efficient Yes   No
      Usage based pricing   Low   High
      Hidden follow up costs   No   Yes
      Replication performance   Fast Slow
      Transfer method Highly optimized oData, RFC, JDBC, ODBC
      S3 support Yes Partially
      CDS View support Yes Partially
      Custom datasource support Yes No
      SAPI datasource support Yes No
      ODP datasources support Yes Violating SAP Note 2814740
      HANA DB Log usage Not needed Violating SAP Note 2814740
      Database trigger Not needed Violating SAP Note 2814740
      Middleware needed Not needed Partially needed
      SSH connection needed Not needed Partially needed
      SAP BTP Cloud Not needed Partially needed
      SAP® Datasphere Not needed Partially needed
      SAP Cloud connector Not needed Partially needed
      SAP Java connector Not needed Partially needed
      SAP JDBC / ODBC Adapter Not needed Partially needed
      External scheduler Optional Partially needed
      BW scheduler support   Yes No
      Databricks ETL content Inbound Stage None or outdated
      Databricks Notebooks Supported Partially
      Databricks Job support Supported Partially
      Snowflake ETL content Inbound Stage None or outdated
      Snowflake Notebooks Supported Partially
      Snowflake Stage Supported Partially
      Snowflake Snowpipe Supported Partially

      Supported Systems

      This set of systems is included in the standard installation. Additionally we offer you a tailored system integration if you use another cloud data warehouse.
      Source Systems
      • SAP BWonHANA® >= 7.5
      • SAP S/4HANA® >=1709
      • SAP BW/4HANA®
      Source Type
      • Datasources (BW, ODP, SAPI, CDS Views)
      • Composite Provider & ADSO
      • Custom Tables via CDS Views
      Target Systems
      • Snowflake
      • Databricks
      • Other vendors on request

      SAP Compliance

      We respect all SAP notes related to log based replication, ODP API restrictions and database triggers.
      Our codebase does not use any technology which is mentioned in the SAP notes below.
      SAP Note 2814740

      Database triggers in ABAP Dictionary

      Database triggers cannot be created or managed in the ABAP Dictionary. Despite this, triggers are taken into account or handled in the case of table changes. The ABAP Dictionary distinguishes between manageable and non-manageable triggers.

      Operations that cannot be handled:

      • The addition or deletion of a primary key column
      • Centralized oversight of all business rules operating in the system
      SAP Note 3255746
      Unpermitted usage of ODP Data Replication APIs
      • The usage of RFC modules of the Operational Data Provisioning (ODP) Data Replication API is NOT permitted by SAP by customer, or third-party applications to access SAP ABAP sources (On-Premise or Cloud Private Edition)
      • Such modules are only intended for SAP-internal applications and may be modified at any time by SAP without notice.
      • Any and all problems experienced or caused by customer or third-party applications (like MS/Azure) using RFC modules of the Operational Data Provisioning (ODP) Data Replication API are at the risk of the customer and SAP is not responsible for resolving such problems.
      SAP Note 2971304
      SAP has not certified any supported interfaces for redo log-based replication
      • SAP has not certified or offered any supported interfaces in the past for redo log-based information extraction out of SAP HANA’s persistence layer (log volumes as well as log backups in files or external backup tools).
      • To be clear, there is no published or ever existed API for the redo-log information extraction by SAP or any similar planned functionality in the current roadmap for SAP HANA and SAP HANA Cloud!
      • Any solution on the market is consequently based on 3rd-party reverse engineering of redo-log (transactional log) functions of SAP HANA outside of SAP reach.

      Frequently asked questions

      01.How is our solution different from SAP OpenHub?
      • No management view in S/4HANA, deltas cannot be repeated
      • OpenHub has no end-to-end solution
      • Code has many bugs and long-term strategy and support is unclear
      • OpenHub can’t be integrated to external orchestration tools
      • Large data transfers cannot be split and parallelized
      • Poor performance, export of multiple millions of records can take hours
      • Inflexible setup of CDS Views, problems with long fieldnames
      02.How does our solution support Snowflake and Databricks?
      • OpenHub doesn’t provide options to write to Snowflake and Databricks
      • OpenHub has no out-of-box S3 Integration
      • OpenHub has no Databricks Notebook support
      • OpenHub has no Databricks Job support
      • OpenHub has no Snowflake Notebook support
      • OpenHub has no Snowflake Stage support
      • OpenHub has no Snowflake Snowpipe support

      Challenges in SAP Data Replication to Snowflake

      Performance Bottlenecks
      • SAP table locking during extraction
      • Network bandwidth limitations during large data transfers
      • Resource contention in production environments
      • Slow processing of wide tables with numerous columns
      Data Consistency Issues
      • Handling complex SAP data types and conversions
      • Maintaining referential integrity across tables
      • Managing delta changes in clustered tables
      • Synchronizing data across different time zones
      Operational Complexities
      • Complex SAP authorization requirements
      • Limited extraction windows during business hours
      • High memory consumption during full loads
      • Monitoring and alerting across multiple systems
      Integration Hurdles
      • SAP module-specific extraction logic
      • Custom ABAP code compatibility
      • Pool and cluster table replication
      • Handling of SAP buffer synchronization
      Cost Management
      • Snowflake compute costs during large loads
      • Storage costs for historical data versions
      • Network egress charges
      • Development and testing environment expenses
      Best Practices
      • Implement incremental loading where possible
      • Use parallel processing for large tables
      • Schedule resource-intensive loads during off-peak hours
      • Optimize table structures and indexes
      • Regular monitoring and performance tuning

      Challenges in SAP Data Replication to Databricks

      Performance Issues
      • SAP extractor performance limitations
      • High latency during peak business hours
      • Memory pressure during large table processing
      • Slow processing of hierarchical data structures
      Architecture Complexities
      • Delta Lake table optimization challenges
      • Cluster configuration for varying workloads
      • Managing schema evolution
      • Handling of concurrent write operations
      Data Quality Concerns
      • ABAP data type conversion challenges
      • Maintaining data lineage
      • Complex transformation logic validation
      • Handling of SAP null values and special characters
      Operational Challenges
      • Job orchestration across environments
      • Resource allocation for multiple workloads
      • Managing compute costs for large datasets
      • Monitoring distributed processing tasks
      Integration Hurdles
      • SAP connector stability issues
      • Authentication and authorization complexity
      • Network security configuration
      • Managing CDC (Change Data Capture) failures
      Best Practices
      • Implement auto-scaling policies
      • Use optimized file formats (Delta/Parquet)
      • Set up proper partitioning strategies
      • Deploy robust error handling mechanisms
      • Establish clear SLAs for data freshness