Crate.io has raised $11 million in Series A funding to push development of its vision for an open source SQL database for real-time machine data and IoT applications. The funding round was led by Zetta Venture Partners and Deutsche Invest Equity with participation from Mike Chalfen, Momenta Partners and Charlie Songhurst. According to the company, existing investors Draper Esprit, Vito Ventures and Solomon Hykes also participated in the round, which will be used to boost the growth and adoption of both the commercial and open source offerings. The Crate Machine Data Platform plays a crucial role in helping firms put machine data to work faster. The company's aim is to make the job of building the data management "plumbing" that forms the foundation for IoT systems easier with the help of this platform.
Brisbane startup FloodMapp has raised $1.3 million, as it looks to take its flood-prediction tech to the rest of Australia, and into hurricane-prone areas of the US. The funding comes from several VC firms, including Allectus Capital, Transition Level Investments, Jelix Ventures and Mercurian, as well as from a number of individual investors. Founded by Juliette Murphy and Ryan Prosser, FloodMapp combines big data analytics and machine learning techniques with traditional hydrology and hydraulic modelling approaches. The tech measures river height and rainfall data in real-time, and uses underlying elevation and topography to predict how and where water will flow over the land, Murphy tells StartupSmart. This allows the team to "predict a map of the inundated areas" and share that data with third parties.
New York-based Cherre real estate data and analytics platform announced it has raised $16 million in growth funding. Including this round of funding, Cherre has raised a total of $25 million. Intel Capital led the funding round. Navitas Capital, Carthona Capital, Zigg Capital, Dreamit Ventures, and Silicon Valley Bank (new growth debt relationship) also participated in the round. Cherre's artificial intelligence platform empowers large enterprises, insurance companies, banks, and investors with a platform to instantly collect, augment, resolve, and analyze datasets in real-time from hundreds of thousands of public, private, and internal sources.
Google sibling Sidewalk Labs has confirmed the latest project spinout from its incubator. Replica, originally known as Model Lab, is touted as a "next-generation urban planning tool" and began life as a Sidewalk Labs project in April, 2018. In truth, Replica Inc. has actually been an independent entity since March, and a June corporate filing describing its business somewhat enigmatically as "quality fish reproductions" was spotted by Redtail a few months back. Now it seems Replica is willing to go on the record about its new life as a standalone company and has also revealed a fresh tranche of funding. But first -- what exactly does Replica do?
WIRE)--NVIDIA GPU Technology Conference - Fuzzy Logix, Inc., provider of high performance, in-database analytics, and Kinetica, provider of the fastest GPU-accelerated database, today announced a partnership to offer a joint solution that will allow customers of both companies to leverage high performing advanced analytics with acceleration of 100-500x on 1/10th the hardware over CPU-only based solutions. The joint solution will initially be targeted at the most time-sensitive and compute-heavy applications in financial services, retail, and healthcare, where speed and scale are critical for real-time data insights and competitive advantage. By combining technologies, Kinetica's in-database analytics capabilities will be extended by hundreds of additional GPU-accelerated and highly-parallelized, machine learning and predictive analytics algorithms from Fuzzy Logix. At the same time, those analytic functions will now also be able to take full advantage of Kinetica's distributed GPU pipeline via its User Defined Functions (UDFs). "Leveraging GPUs for analytical workloads is on the rise, particularly among financial services, life sciences and retail organizations that often deal in extremely large data volumes with high scaling and real-time processing requirements," said Jim Curtis, Senior Analyst, Data Platforms & Analytics at 451 Research.