Migrate 3x Faster with 1/3 the Resources
Infoworks Replicator is changing the way enterprises migrate their data to the cloud.
End-to-end automation enables enterprises to rapidly migrate large scale Hadoop data lakes to the cloud in a fraction of the time and with one-third the resources required for legacy hand-coding and point tool processes.
Running as a service, Replicator maintains continuous operation and synchronization between on-premises Hadoop source and cloud destination clusters, ensuring data migration at scale without risk of data loss or business disruption.
Seamlessly migrate data and metadata with Replicator, or extend to the full Infoworks Platform to migrate workloads and automate your cloud data platform – for ultimate analytics agility and scale.
Powers faster migrations and reduces resource requirements to speed time to value.
Continuous operation and synchronization ensures zero business disruption.
Migrate petabytes of data and metadata to any cloud seamlessly.
Automate your cloud data platform post-migration to accelerate deployment of new analytics use cases.
Extend Hadoop migration to a fully automated modern data platform
Simplify, automate, accelerate cloud migration of data and workloads and automate your data platform for analytics agility and scale.
Rethink your Hadoop migration to the cloud
Seamless migration so your business-critical enterprise data gets to the cloud fast.
Automated Code Free Migration
End-to-end automation of Hadoop data and metadata to any cloud.
Maintains continuous operation and data synchronization between Hadoop and cloud clusters.
Automated fault tolerance of the process removes significant overhead
Automated restart upon network or node failure from point of failure.
Administration of network resource utilization for replication
Administrators can statically or dynamically allocate the network utilization allowed per replication session using static and dynamic network throttling.
Integration with data transformation pipeline for any data shaping requirements
Users can insert key rotation and other data shaping requirements into the end-to-end pipeline
Support for most common data and file formats
ORC, Parquet, CSV, Managed & External tables, Bucketed tables, Text, Avro, Sequence, and Partitioned are supported.
Tunable scalability for petabyte size clusters
Users have the ability to control parallelism for diff computation and data replication tasks.
Flexible deployment modes
Deploy as source cluster, destination cluster, or a third cluster.