The lambda architecture is based on dividing the Big Data ecosystem into different layers depending on how the data is
processed and managed: in real time (speed layer), making queries on stored data (batch layer) and the serving layer
that shows the results of the queries made. This type of architecture is widely used for the implementation of
different Big Data systems.
References:
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Marz, N., Warren, J.: Big Data: Principles and best practices of scalable
real-time data systems. New York; Manning Publications Co. (2015).
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Darwish, T.S.J., Bakar, K.A.: Fog Based Intelligent Transportation Big
Data Analytics in The Internet of Vehicles Environment: Motivations, Architecture, Challenges, and Critical
Issues. IEEE Access. 6, 15679–15701 (2018). https://doi.org/10.1109/ACCESS.2018.2815989.
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Psomakelis, E., Tserpes, K., Zissis, D., Anagnostopoulos, D., Varvarigou,
T.: Context agnostic trajectory prediction based on lambda architecture. Future Gener. Comput. Syst. (2019). https://doi.org/10.1016/j.future.2019.09.046.
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