AUTOMATE HADOOP DATA LAKE MIGRATION TO THE CLOUD

Migrate 3x Faster with 1/3 Fewer Resources

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INFOWORKS REPLICATOR IS CHANGING THE WAY ENTERPRISES MIGRATE THEIR DATA TO THE CLOUD

Enterprises can now migrate on-premises Hadoop to the cloud in a fraction of the time, and with fewer resources than traditional approaches. 

Through end-to-end automation, on-premises Hadoop data and metadata are rapidly migrated, and scarce expensive data talent is freed to focus on higher-value business priorities – making obsolete hand-coding and labor-intensive legacy point tool processes. 

Since Replicator runs as a service, continuous operation and synchronization between on-premises Hadoop and cloud clusters ensure data migration at scale without risk of data loss or business disruption, and Replicator is part of the Infoworks Platform so you can successfully migrate and automate your modern data platform for ultimate analytics agility and scale.

Automation

Faster migration and fewer resources means lower migration cost.

Synchronization

Continuous operation and synchronization for zero business disruption.

Unlimited Scale

Move petabytes of data and metadata to any cloud seamlessly

Extensibility

Automated modern data platform accelerates 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

Continuous Synchronization
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. Automatically restarts from point of failure instead of from the beginning.

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, Partitioned

Tunable scalability for petabyte size clusters
Ability to control parallelism for diff computation and data replication tasks

Flexible deployment modes
Source cluster, destination cluster, or a third cluster