Cirata announced support for IBM General Parallel File System (GPFS), a cluster file system used for IBM Spectrum Scale data lakes. The newly released Live GPFS support, included in Cirata Data Migrator 2.5, significantly reduces latency between storage changes and replication or migration results, while also improving the performance and scalability of GPFS-resident data assets migrating to the cloud.
Cirata Data Migrator lowers data latency while enhancing data migration performance for better data integration outcomes. The new Cirata Live GPFS capability initiates data transfer from a source GPFS file system as changes occur, without disruption to the storage environment. Ideally suited for cloud migrations, disaster recovery processes and continuous data migration use cases, Cirata Data Migrator with Live GPFS not only improves migration scale and performance but also supports fine-grained control and audit logging for assured compliance in increasingly multicloud data management environments.
According to Gartner®, “81% of respondents in organizations using public cloud said their organizations were using more than one cloud service provider (CSP).” “As the number of CSPs an organization uses increases, the complexity of managing them also increases. This can have negative consequences, such as performance issues associated with data latency, unplanned cost overruns or data egress fees, and difficulties with data integration.”(1)
“Modern multicloud workloads require high performance access to a common set of data to support scale-out storage and high availability. This is performed by IBM GPFS with great efficiency,” said Paul Scott-Murphy, Chief Technology Officer, Cirata. “By supporting this valued IBM GPFS capability as a Live source, Cirata Data Migrator gives organizations leveraging GPFS-resident data assets the confidence that they can flexibly migrate and replicate data with high performance and control to nearly any target, anywhere.”
Cirata Data Migrator with Live GPFS delivers the following benefits:
- Reduces latency: By taking action immediately after change, Cirata Data Migrator minimizes the latency between source storage modifications and the actions to transfer or modify content at the targets. This can minimize recovery point objectives (RPO), and assist in architecting solutions with zero recovery time objectives (RTO).
- Improves scale: Cirata Data Migrator avoids the need to repeatedly scan a source file system to identify change when Live migration is in effect. This is particularly beneficial for systems with very large numbers of storage items, allowing vastly more scalable outcomes and minimizing the overhead imposed on storage.
- Enhances performance: By avoiding the need to repeatedly scan source storage, Cirata Data Migrator with Live GPFS avoids an entire class of overhead that solutions relying on scheduled jobs incur. The result is higher performance, and reduced computational overheads.
- Enables finer control: Cirata Data Migrator offers fine-grained control of which data assets participate in migration. The Live GPFS feature incorporates these mechanisms natively, so that techniques like path mapping and pattern-based exclusion of file system content are incorporated into the core processing performed during data transfer, exposing all of the fine-grained selectivity directly to users if wanted.
- Delivers auditable, accurate outcomes: Every action taken in response to changing source data is logged in auditable form, complementing the detailed reporting already available from migration verification to help ensure that migration outcomes are complete and accurate.
Cirata Data Migrator is a fully automated solution that automates Hadoop data transfer and integration and moves on-premises HDFS data, Hive metadata, local filesystem, or cloud data sources to any cloud or on-premises environment, even while those datasets are under active change. Cirata Data Migrator requires zero changes to applications or business operations and moves data of any scale without production system downtime, business disruption, and with zero risk of data loss. Migration targets supported include the Hadoop Distributed File System, Alibaba Cloud Object Storage Service, Amazon S3, Azure Data Lake Storage Gen 2, Google Cloud Storage, IBM Cloud Object Storage and Oracle Object Store.
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1 Gartner, How to Optimize for Multicloud Data Management Deployments, Masud Miraz, Adam Ronthal, 13 May 2024. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
