According to Intel, by 2020, the average internet user will generate approximately 1.5GB of data per day. Smart cars, meanwhile, will generate 4,000 GB each daily, not to mention connected hospitals, flights, factories and more. In short, tech companies are going to have huge amounts of data to sift through for ads, logistics and resource management services, and artificial intelligence.
So how do these companies deal with Big Data?
Technology experts believe we’re approaching a culmination of data influx, coupled with a lack of purging of old data. They foresee cloud storage shortages in the future that could hamper how our smartphones, apps, and computers operate, as well as longer processing times for IoT devices and services. Data compression is not yet effective enough to counter this problem, and even then this technique hinders how AI can access these stores to learn.
Terark is a tech start-up focusing on storage engine development and storage optimization. With several patents for storage and data processing technology, we developed a cutting-edge storage engine, TerarkDB.–https://www.terark.com/en/aboutus
Terark’s system keeps the data searchable without needing to unpack it, meaning machine learning systems and others can easily access its stores without overloading their own servers.
Terark is composed of a team of just 10 people, and the startup itself is only about two years old. In that short time, it’s even managed to attract high profile investors like Alibaba, which has signed a $1 million contract with the startup to use its compression system for the Alibaba Cloud.