MemVerge Announces $24.5 million Funding Milestone and New Stealth Product Release

MemVerge announced $24.5 million in Series A funding for stealth, which will be used to significantly expand its engineering, sales and marketing teams in Silicon Valley as well as to accelerate the development of its Memory-Converged infrastructure (MCI) technology. Investors include Gaorong Capital, Jerusalem Venture Partners, LDV Partners, Lightspeed Venture Partners and Northern Light Venture Capital.

MemVerge announced $24.5 million in Series A funding for stealth, which will be used to significantly expand its engineering, sales and marketing teams in Silicon Valley as well as to accelerate the development of its Memory-Converged infrastructure (MCI) technology. Investors include Gaorong Capital, Jerusalem Venture Partners, LDV Partners, Lightspeed Venture Partners and Northern Light Venture Capital.

In addition to MemVerge’s new stealth product, they also announced what the company is calling the first system that completely removes “boundaries between memory and storage” to power demanding data-centric enterprise workloads. This new MemVerge solution offers memory and storage services from a single distributed platform and is designed to easily integrate with existing applications so organizations can better deal with constant machine-generated data. Featuring Intel Optane DC persistent memory technology, MemVerge indicates that their new Memory-Converged Infrastructure (MCI) system boasts ten times more memory size and data I/O speed compared to other solutions on the market

MemVerge’s built proprietary Distributed Memory Objects (DMO) technology into their new system, creating a logical memory-storage convergence layer that harnesses Intel’s new persistent memory. The company believes this will enable data-intensive workloads to run “flawlessly” at memory speed, including AI, machine learning, big data analytics, IoT and data warehousing use cases. MemVerge also claims that their system expands memory seamlessly and stores data consistently across multiple systems, which will allow organizations to analyze huge amount of data (both large and small files) in real-time.

MemVerge indicates the following benefits of bridging memory and storage into one architecture:

• Massive and complex applications operate smoothly, at memory speed. The MemVerge system presents memory at scale for mission critical AI, big data and IoT applications – such as Presto, Apache Spark and TensorFlow – without the out-of-memory crashes that are common with current solutions. In today’s on-demand economy, where competitive advantage comes from immediate insights from data, enterprises can no longer afford to store data on HDDs or SSDs; memory and storage need to coincide on one system. WithMemVerge’s DMO technology, coupled with Intel Optane DC persistent memory, enterprises are able to complete analytics faster and with more predictability.
• Random access is as fast as sequential access. Data-centric workloads require storage with fast sequential access and random access; random access to the machine-generated data is too slow in today’s systems using HDDs or SSDs. This is particularly true in AI training, where enormous numbers of smaller files are being processed. MemVerge DMO technology makes it possible for a large number of small files can now be accessed with speeds as high as those accessing a small number of large files, allowing workloads such as AI training to be completed in less time and with fewer resources.
• Long-lasting system design offers greater data center reliability. Taking advantage of the high endurance of persistent memory, the MemVerge solution is more reliable than traditional storage systems. As persistent memory can withstand 100X more full writes than NAND flash SSDs, enterprises can worry less about replacement of drives or potential data loss due to the failure of drives. Data is replicated consistently across multiple nodes to ensure there is no data inconsistency in case of failures.

Availability

MemVerge Beta program is slated for a release some time in June 2019.

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