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GigaSpaces Raises $12 Million to Accelerate AI Workloads with In-Memory Computing

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GigaSpaces Raises $12 Million to Accelerate AI Workloads with In-Memory Computing

author VentureBeat May 7, 2020

GigaSpaces, a startup developing in-memory computing solutions for AI and machine learning workloads, today announced it has raised $12 million. The funds will be used to scale expansion and accelerate product R&D, according to CEO Adi Paz.

It’s often been argued that in-memory computing is a critical piece of the big data analytics puzzle. It promises to mitigate slow data accesses by relying exclusively on data stored in RAM, minimizing the need to move data between storage and processors and theoretically speeding up the training time of machine learning algorithms. The result could be substantial cost savings in the case of algorithms that take days (or even weeks) to train.

GigaSpaces offers three core products in InsightEdge, XAP, and GigaSpaces Cloud.

InsightEdge powers analytics on streaming data enriched with historical context via a cloud-native, microservices-based architecture for cloud, on-premise, and hybrid environments. It supports multi-tiered storage across RAM, solid-state storage (SSD), storage-class memory, and persistent memory, and it ships with scalable frameworks like SQL and support for data lakes such as Hadoop, Amazon S3, Azure Blob Storage, and more.

As for XAP, it’s an app fabric that handles event-driven microservices and distributed apps. The in-memory data grid provides a set of data store features, such as transactions, indexes, and query language, as well as in-memory functions involving structured, semi-structured, and unstructured data — like messaging, event processing, data access, and transaction processing.

Lastly, GigaSpaces Cloud — the company’s fully managed service hosted on Amazon Web Services, Microsoft Azure, or Google Cloud Platform — offers a free deployment of InsightEdge with prebuilt apps, models, and business intelligence dashboards. Customers can take advantage of standard interfaces, like rest APIs and Spark, to deploy services, web apps, and more.

The in-memory computing market is estimated to be worth $23.15 billion (up from $5.58 billion in 2015), according to Markets and Markets, and there’s plenty of competition to go around. In February, Hazelcast raised $50 million for its speedy in-memory compute services. And last year, managed AI startup H2O.ai raked in $72.5 million, in part to further develop its in-memory compute offerings.

But GigaSpaces appears to be growing at a rapid clip. Annual recurring revenue doubled in 2019 as its customer base — which now includes Bank of America, Morgan Stanley, BlueCross BlueShield, Charles Schwab, and UBS — tripled. This year, as a result of exponential cloud adoption driven by the pandemic, GigaSpaces expects to see a “record” jump in revenue.

Fortissimo Capital led the investment in three-year-old, New York-based GigaSpaces, joined by existing investors Claridge Israel and BRM Group. The round brings GigaSpaces’ total raised to $53 million, following a $20 million series D in January 2016.

This article was originally posted on VentureBeat on May 5th, 2020.

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