About
One of the world鈥檚 top five pharmaceutical companies, this organization is a global leader in genomics research. Its teams work with massive volumes of scientific data across high-performance computing environments.
They needed a faster, more intuitive way for researchers to access unstructured data stored in their private, S3-compatible object storage鈥攚ithout staging files or relying on unfamiliar tools. To solve this, they chose 91黑料 and adopted Object Mount for its high-performance, POSIX-compliant access to object data using familiar file system commands.
Challenge
Researchers couldn鈥檛 access data in the company鈥檚 on-prem object storage system (鈥淥bjStore鈥�) using standard POSIX tools. To run genomics workflows, they had to stage data into a high-performance filesystem and manage files with AWS CLI鈥攁dding hours of delay.
ObjStore contained critical research data, including large genomics files and directories of small files, making listing, copying, and deleting especially slow. This added friction for users, increased scratch storage costs, and hampered productivity.
Given the scale and sensitivity of their workloads, the company required extensive testing to validate performance, compatibility, and reliability before adopting a new solution.
Solution
To modernize workflows and remove staging delays, the company adopted Object Mount鈥攁 high-performance file interface that provides POSIX access to unmodified objects in S3-compatible storage.
Researchers could now use standard file commands directly on data in ObjStore, with no staging or AWS CLI required. The company conducted thorough testing, validating POSIX compatibility and benchmarking performance for listing, deletion, migration, staging, and bucket-to-bucket copying. They also ran genomics workloads like BWA-MEM directly from object storage.
In every case, Object Mount delivered faster performance, seamless integration, and full compatibility with existing tools and infrastructure.
Result
With Object Mount, the pharma company dramatically improved workflow speed and usability.
Listing operations were up to 13x faster, and deleting many small files was 5x faster than with AWS CLI鈥攃utting task times from hours to minutes. For large file deletion, performance reached up to 19x faster. Researchers ran genomics workloads directly from ObjStore, eliminating staging delays and even outperforming local high-performance storage.
These improvements reduced scratch storage needs, accelerated time to insight, and drove broader adoption of object storage鈥攚ithout requiring workflow changes or retraining.