Q. What is the primary goal of the CAP theorem in distributed storage systems?

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Q. Why is it challenging to implement a fault-tolerant BASE architecture for Big Data management?

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Q. How does the CAP theorem impact the design of Big Data solutions?

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Q. What role does the concept of "eventual consistency" play in the CAP theorem?

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Q. What characterizes Big Data solutions in terms of data management aspects?

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Q. What is the trend in data structures for Big Data?

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Q. According to the CAP Theorem, what are the three main features that a distributed storage system can provide?

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Q. What does the property of "consistency" mean in the context of the CAP Theorem?

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Q. How does the CAP Theorem impact Big Data solutions?

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Q. What properties are described by the ACID paradigm in relational databases?

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Q. What is one of the primary challenges associated with the database size in Big Data problems?

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Q. Which factor significantly influences the performance of data management in Big Data solutions?

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Q. What is the main factor that influences the performance of data management in terms of data modeling?

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Q. Which category of NoSQL databases is known for its effectiveness in handling time series data and data from multiple sources?

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Q. In which situation are document stores like MongoDB and CouchDB typically used?

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Q. Which NoSQL database category is suitable for modeling relationships among data and is often used in fields such as geospatial analysis and network analysis?

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Q. What does the CAP theorem state about distributed storage systems?

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Q. Which property of the CAP theorem refers to the system's ability to provide the same data to all clients after an operation?

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Q. What is the main difference between the ACID and BASE properties in the context of database transactions?

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Q. Which category of NoSQL databases is known for its high scalability and suitability for managing large lists of elements?

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