Singlestore, a database that provides the performance, simplicity and flexibility needed to power Enterprise AI, announced its official launch in Japan on August 4th. The move highlights the growing demand for high-performance, optimized data infrastructure in one of the world's most technologically advanced markets. This expansion further highlights single store leadership in providing real-time capabilities and underlying data strategies essential to building next-generation high-performance enterprise AI applications.
With this expansion, Singlestore brings the ultra-low latency AI-Reaid database platform to one of the world's largest and most innovation-driven economies. The move is helping Japan accelerate its national AI strategy, companies seeking more and more scalable, real-time data platforms, like single stores, and is helping large global Fortune 500 companies to develop next-generation AI applications.
“Expansion to Japan is a strategic and iconic step in the single store's mission to promote global AI advancement,” said Raj Verma, CEO of single store. “Japan is one of the most technologically advanced economies in the world and is excited to use A-Optimised data capabilities in real time to drive the next wave of innovation.
This expansion is a time of great growth for single stores. The company achieved US$100 million in just four years, valuing more than US$1 billion, following its recent funding round in 2022, rising from US$10 million to over US$100 million. The Single Store currently has customers from over 50 countries, and the expansion to Japan is expanding around the world.
Veteran enterprise technology leader Tadashi “Troy” nishoka will promote single store work in Japan as managing director, bringing deep experience from working in Japan's cloud and data markets. Under Nishida's leadership, the company will expand its local footprint with a focus on strategic recruitment, partnerships with key cloud and systems integrators, and servicing industries such as financial services, manufacturing, communications and healthcare.
“Our goal is simple. Japanese companies will be able to realize their AI ambitions by giving them the performance, scale and simplicity they need,” Nishino said. “We are deeply committed to understanding the unique needs of Japanese companies and maximizing the possibilities of AI, tailoring to the country's culture of accuracy, quality and continuous improvement to become a reliable partner for Japanese companies.”
The expansion of single store to Japan is based on the deep presence of the entire APAC region, with a strong presence in customers from 12 countries, regional hubs in Singapore and India. The company already serves more than 100 customers in the region, including leading companies such as Nikkei, Samsung, Tata, DBS Bank, Posco and 6sense.
“Since partnering in 2017, Single Store has trusted its outstanding performance and innovative approach,” says Hajimeno, software engineer and engineering manager at Nikkei. “It's now a core part of the data platform, and we're bolstering real-time analytics that supports around 1,500 journalists with Nikkei Online Edition. With a single store, we've reduced data latency from 45 minutes to just 200 milliseconds.
As businesses around the world aim to integrate legacy databases, accelerate AI adoption and modernize their infrastructure, Singlestore is a database of choices to build that future in real time. Its Unified Platform has its own support for hybrid transactions and analytical processing, vector and full-text search, and low-latency streaming inguest, making it ideal for powering modern AI applications. Singlestore features support incorporating serverless inguest, integrated AI functions and developer-optimized workflows, providing flexibility and power for modern teams to build intelligent and responsive AI applications. Native handling of both structured and semi-structured data, compatibility with platforms like Snowflake, Postgres, SQL Server, Oracle, MySQL, and scalability across cloud environments, helps organizations dramatically reduce complexity and latency while consolidating data architectures.
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