One Algorithm Is All You Need to Optimize Endless Batch Processes, from the Mainframe to the Cloud’ – Innovative Startup, KeyGen Data LLC, Secures Patent for Process Method: HyperBatch

KeyGen Data LLC announced it had recently been granted the first in a series of upcoming patents for HyperBatch, a proprietary algorithm that significantly optimizes batch processes while demonstrably saving companies time and money. KeyGen Data LLC will soon begin reviewing and issuing licensing agreements for the use of HyperBatch – both directly and in other software products that help a wide variety of companies and industries. Interested parties and tech partners are invited to contact KeyGen Data LLC directly for details.

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“Rapid advancements in speed and security have allowed cloud-based systems to successfully perform transaction-based processing and transitioning from legacy mainframe platforms,” said Rabin Das, Product Manager. “Unfortunately, all large-scale batch processing applications are really limited in performance when migrated to the cloud, because current cloud-based solutions are extremely inefficient in processing batch systems; especially when large amounts of data and complex processing are involved. Companies are forced to pay the excessive cost of their mainframe investments to support their batch processing needs, while moving only online transaction processing (OLTP) systems to cloud. And still, this results in 40 to 60% of their processing needs being retained on the mainframe. We’re happy to reveal that HyperBatch has solved this problem.”

The HyperBatch Difference

HyperBatch is a patented process framework designed to dramatically reduce the cost and improve the performance of batch processes migrating to a cloud environment. While other methods treat batches as vertical layers, the HyperBatch method treats batch data, or sequential data, as horizontal layers within a set of keys, implementing a top-to-bottom approach. This new concept of data processing allows the batch program to process millions of layers of data simultaneously against batch processing business rules. This also opens multiple opportunities for new research and development to further expand on HyperBatch’s capabilities.

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When compared to batch processes performed on a mainframe, the HyperBatch solution yields between 20-to-60-times the improvement in performance at much lower operating costs. And existing cloud-based batch processes benefit from a far better performance when leveraging the HyperBatch method too. The HyperBatch process dramatically reduces the execution time of the batch function itself, but also eliminates significant overhead associated with pre-sorting because the HyperBatch algorithm combines the two tasks into a single optimized process, further reducing both processing time and cost.

“As our software rolls out in multiple industries, we expect to see cloud vendors like AWS, Azure, and Google Cloud getting a major boost in migration of legacy systems to their platforms,” explained Rabin Das. “Currently available legacy migration solutions to the cloud, such as code refactoring, do not incorporate or employ any new methods for tackling the core issue of batch processing: data being processed one row at a time.”

“HyperBatch renders the ‘cursor’ processing option available in all relational database management systems (RDBMSs) obsolete,” said Das. “Our new process delivers hundredfold performance gains and ease of code conversion for complex rules. Large legacy systems have millions of rows to process in a batch system on a daily, weekly, or monthly basis. The cost in time and money to run these systems is staggering. Because HyperBatch is so much faster and cheaper to operate, it allows businesses to run a monthly, weekly, or even daily batch, delivering more up-to-date data for reporting and analytics.”

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