Data quering can be an intensive task if there is a lot of data. Metrics such as completion of data completion time (latency), and data integerty from multiple sources (real time database constraints). Also Boston University is looking to replace the DNS system due to insecurities. Even with DNSsec being baked into ipv6 and as an extension for ipv4 there are massive inefficiencies. Consider the mail server having to touch addresses beyond the intranet. UDP is a mess and horribly insecure with UDP hole punching. VPN software is horribly complex and some just use udp hole punching because they cannot figure out tunneling. Exposed to this is udp based DBMS. I believe that natural language processing through microservices can provide an API that can restructure uncoupling of the internet through the actor state framework. How do we as humans aquire data on the internet. we are used to human readable natural language processing through search engines such as Google, Bing, Wolfram Alpha, etc. short effective grammatically correct phrases can not only enable humans to better search the internet but as autonomous cars need to communicate, they might not have just milliseconds in order to communicate. Yes, normalization is nice but with real time databases it cannot always be assumed. That‘s the long answer to the question.
1) data manipulation language tokenization as natural language becomes increasingly common
2) reconstruction if pieces are missing
3) uncoupling
4) standard compliant
5) if accidential exposure occurs how bad is it?
you, my friend are working on an exciting project at an opportune and significant time.

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