Transparent Compression
Eideticom’s transparent compression solution provides real time data compression services, offering superior offloading CPU usage for the host.
NoLoad can be utilized in Userspace without changes to the operating system while Kernelspace requires zero application changes.
99%
Lower CPU Usage
36%
Lower Power
Offload Computation with Transparent Compression
Eideticom’s NoLoad Transparent Compression solution offers a versatile and high-performance approach to optimizing your storage needs without requiring any environment changes. Our platform accelerates a wide range of database applications, by offloading compute-intensive operations from the CPU to specific hardware accelerators.
Book a Demo
Transparent Compression for High-Performance Computing
In HPC data centers, speed and performance are paramount and often limited by CPU-bound compression. Our transparent compression technology changes that. By delivering line-rate compression, it meets the high-speed requirements for HPC data centers while allowing for other important tasks in data science. Our NoLoad solution integrates into file systems without any need to alter the software stack.
Book a DemoTransparent Compression for FinTech
Eideticom’s transparent compression (TC) solution produces significant cost savings for Financial Institutions tasked with generating and storing vast amounts of data as efficiently as possible. By implementing TC, fintech companies efficiently compress their data and offload CPU-intensive tasks to perform critical business logic, such as transaction processing or complex financial calculations.
Our solution results in optimized storage, significant cost savings, and the ability to handle high-frequency trading data with minimal latency. TC enables high performance and scalability as data needs grow, while preventing bottlenecks in data throughput. Through seamless and risk-free integration into existing infrastructure, data is managed more efficiently, enhancing both operational performance and cost efficiency without compromising their ability to process real-time data.
