Sapper – Legacy Modernization Platform
Rich Library of Data Sources
Out of the box integrations with many applications, databases, streaming services, and various other sources including Hadoop Distributed File System (HDFS). All standard connection methods and data formats are supported.
Common IT Challenges Solved by Sapper
Hybrid Cloud Integration
Enterprise Data Lake
Migration
Realtime Reporting
Geographical Distribution
High Availability
Key Features
Intrinsic support for batch processing, streaming & Change Data Capture (CDC)
Guaranteed Delivery and Transactional Consistency supported where required.
DSL driven Data Validation and transformations
Scaled to handle 1 Million+ events per minute for both Ingress and Egress
Extensible framework for building custom connectors
Integrated authentication and authorization
Change Data Capture (CDC)
Sapper uses the CDC Data Integration approach that allows high-velocity data to achieve reliable, low latency, and scalable data replication using fewer computation resources. Change Data Capture (CDC), enabled companies to deliver new data changes to BI (Business Intelligence) tools and team members in real-time, keeping them up to date.
Companies need access to real-time data streams for Data Analytics. Sapper mainly uses Log-Based CDC to ensure no performance impact on the sources. Only the changed data is transferred for faster performance. CDC excludes the process of bulk data loading by implementing incremental loading of data in nearly real-time.
Sapper CDC engine provides you a rare ability to read newly written data from HDFS volumes and sync it to any target to save a considerable amount of time.
CDC Connectors
CDC Features
Snapshot: Initial snapshot of a database’s current state can be taken if a connector is started and not all logs still exist. Typically, this is the case when the database has been running for some time and has discarded transaction logs that are no longer needed for transaction recovery or replication. There are different modes for performing snapshots.
Filters: You can configure the set of captured schemas, tables and columns with include/exclude list filters.
Masking: The values from specific columns can be masked, which contains sensitive data.
Monitoring: Most connectors can be monitored by using JMX.
Message transformations: Message transformations can be done for Message routing, Content-based routing, and Filtering.
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Fully Automated and Reliable Data Pipelines for Faster Analytics
Sapper’s fully managed and automated data pipeline loads all your data to the warehouse or data lakes at scale in real-time, ready for analysis.

