To summarize, in this post I’ve: Clarified terminology, specifically narrowing the definition of “streaming” to apply to execution engines only, while using more descriptive terms like unbounded data and approximate/speculative results for distinct concepts often categorized under the “streaming” umbrella. Assessed the relative capabilities of well-designed batch and streaming systems, positing that streaming is in fact a strict superset of batch, and that notions like the Lambda Architecture, which are predicated on streaming being inferior to batch, are destined for retirement as streaming systems mature. Proposed two high-level concepts necessary for streaming systems to both catch up to and ultimately surpass batch, those being correctness and tools for reasoning about time, respectively. Established the important differences between event time and processing time, characterized the difficulties those differences impose when analyzing data in the context of when they occurred, and proposed a shift in approach away from notions of completeness and toward simply adapting to changes in data over time. Looked at the major data processing approaches in common use today for bounded and unbounded data, via both batch and streaming engines, roughly categorizing the unbounded approaches into: time-agnostic, approximation, windowing by processing time, and windowing by event time.
tl;dr: major labels.
Despite having revenue coming in from ads and subscriptions, SoundCloud still relies on outside investment. While the company received $150 million in a funding round at the end of last year, it pales next to the reported $526 million Spotify gained in June, and if one report is to be believed, SoundCloud is running very low on cash. Furthermore, sources suggest that potential investors are waiting to see what happens with Sony and Universal before ploughing in more money. With the high sums reported to be involved, it’s a stalemate that could potentially break the company whether it decides to pay or not.
Air-gapped networks are isolated, separated both logically and physically from public networks. Although the feasibility of invading such systems has been demonstrated in recent years, exfiltration of data from air-gapped networks is still a challenging task. In this paper we present GSMem, a malware that can exfiltrate data through an air-gap over cellular frequencies. Rogue software on an infected target computer modulates and transmits electromagnetic signals at cellular frequencies by invoking specific memory-related instructions and utilizing the multichannel memory architecture to amplify the transmission. Furthermore, we show that the transmitted signals can be received and demodulated by a rootkit placed in the baseband firmware of a nearby cellular phone.