Sanlam selected Data Migrator both to perform the initial migration and the ongoing replication of changes from production to the DR environment. Data Migrator replicates changes as they occur in production so that data is kept consistent, enabling Sanlam to support a near-zero recovery time objective (RTO) and recovery point objective (RPO).
In the use case of a Hadoop to Amazon S3 data migration and replication, GoDaddy found Data Migrator to be the optimal approach to deliver the best time to value, rather than running a more time-consuming and costly manual migration project internally.
KOBIC used the Cirata technology to automate file transfer 13 times faster in both directions between Hadoop-based Big Data Analysis Program Execution Cluster (HDFS) and Linux-based Genomic Analysis Program Execution Cluster (Lustre). They were able to reduce the overall average time to analyze user genomic data of Bio-Express service by more than 30%.
AMD had consistent data in real time across both cloud and on-premises solutions, offering near-zero RPO and enabling hybrid cloud agility to drive the business forward.
Daimler migrated an on-premises data lake to Azure without blocking operations in their live production environment. The on-premises solution would have been nothing more than a dead end because it would have been too inflexible and expensive.
Upgrading systems with no downtime to move to a new version of CDH with zero downtime, Envest | Yodlee replicated data across two Cloudera clusters in real time, operating the current and target environments in parrallel before completing switchover.
Using big data to fight dementia to drive large-scale analytics workloads, the University of Sheffield securely replicated its medical dataset to the cloud - helping to accelerate diagnosis and improve outcomes for dementia sufferers.
HM Health Solutions protects next-generation healthcare services with an always-on data lake ensuring consistent data at its production and DR cluster. The data science team at HM Health Solutions is achieving its goal of providing advanced AI and ML capabilities to stakeholders across the organization, 24/7.
Using a global workforce Juniper Networks enables round-the-clock, round-the-world access to key business data by replicating multiple, distributed Hadoop clusters in the US and India