Q. In which application domains is the interoperability with SQL and NoSQL databases relevant?

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Q. Which application domains typically involve unstructured or semistructured data?

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Q. Which application domains may involve content-based analysis and video processing?

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Q. What is important in terms of data access for rendering, representation, and navigation of results in various domains?

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Q. Which domain requires concurrent access and data consistency?

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Q. What feature may be strongly desirable for scientific and research applications, financial data, and health care?

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Q. In which domains can faceted query results be very interesting?

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Q. When is fast indexing most relevant in different domains?

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Q. What approach may be suitable for contexts requiring complex and deep data processing?

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Q. In which applications is the possibility of supporting statistical and logical analyses on data via specific queries and reasoning important?

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Q. In which contexts is the continuous processing of data streams particularly important?

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Q. Which approach is based on complex event processing (CEP) and improves the speed of analysis in real-time monitoring?

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Q. In which domains is the speed of analysis not a primary feature?

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Q. Which products are among the most flexible and adaptable to different situations and contexts of applications?

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Q. Which technology is successfully used in the field of social media Internet services and social media marketing for managing large volumes of messages and chats?

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Q. What advantage does RDF-3X provide in handling small data?

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Q. In which field is MonetDB primarily used for managing a large amount of images?

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Q. What is one of the key advantages of HDT in data compaction?

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Q. In which contexts is RDF-HDT especially suited?

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Q. What is one of the key advantages of eXist's query engine in scientific and academic research applications?

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