Big data is fundamentally different when compared to fast data. Since both of them are related to disk drives, many people think they have the same function. But, there are several differences. The most significant difference between the two is the space they take up. Big data sits idle. They are always at rest. It doesn’t matter whether there are petabytes or terabytes involved. They tend to take up much more space in the hard drive than fast data.
Fast data, on the other hand, is always in motion. They have different requirements and characteristics, and they run on a different technology altogether. Fast data tends to travel at a speed of milliseconds.
Fast before big
The technology used these days focuses more on fast data instead of big data. Companies prefer to use a technology that ingests and analyzes incoming data streaming at a very high speed. This is not the only criteria that satisfy them. In fact, it creates more reasons for the big data vs fast data debate. Fast data also tends to act quicker than big data. Since big data only takes up space and is unable to move, they can’t react or analyze live streaming actions.
Fast data enters the pipeline, analyzes the live streams, and produces the output, all within a few milliseconds. Quite recently, experts tried to combine the best features of fast data with big data to provide the expressiveness and familiarity required in an SQL query language. The primary objective of this collaboration was to improve the scalability and speed of NoSQL.
Why big data is still necessary
The comparison in big data vs fast data will always favor the latter, but the former also has some exclusive features that make it necessary. Banking transactions solely rely on big data. The traditional database tools are not enough to handle the ups and downs of the financial market. So, the volume of data is often crucial here. Yes, fast data is also essential, but yup cannot overlook the function of big data in these sectors.
Apart from baking transactions where volume is key to keep the record of thousands of transactions, big data also offers the variety the fast data can’t. Social networking sites, blog posts, and various other articles also rely on the diverse nature of big data. It is often linked with different documents such as PDF, excel, word, txt, etc. Their use in different sources like the data generated from sensors that allow access logs to different websites or even the traffic of a router – everything depends on how diverse big data is.
While companies are trying to combine big data and fast data to provide a better facility for the users, it is clear that they are interdependent. Yes, speed is what people want right now, but if you take away the financial records of millions, what will the speed of transaction do alone, especially if a user wants to check all his transaction records from day one?