Database - DBMS Concepts MCQ Questions and Answers

Test your knowledge of Database - [DBMS Concepts] section with these interactive multiple-choice questions.

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101. What is a temporal database?

  • a) A database that tracks time-varying data with built-in time support
  • b) A database optimized for time-series data only
  • c) A temporary in-memory database
  • d) A database that automatically deletes old records
Answer: A - Temporal databases manage data with temporal dimensions (valid-time and transaction-time).

102. Which SQL standard introduced temporal features?

  • a) SQL:2011
  • b) SQL:1999
  • c) SQL:2003
  • d) SQL:2008
Answer: A - SQL:2011 added SYSTEM_VERSIONING and application-time period support.

103. What is a graph database optimized for?

  • a) Storing and querying interconnected data with nodes and relationships
  • b) Graphical data visualization
  • c) Storing images and multimedia
  • d) Generating statistical graphs
Answer: A - Graph databases excel at traversing complex relationships (e.g., social networks, recommendation systems).

104. Which query language is used in Neo4j?

  • a) Cypher
  • b) Gremlin
  • c) GraphQL
  • d) SPARQL
Answer: A - Neo4j uses Cypher, a declarative graph query language.

105. What is columnar storage in databases?

  • a) Storing data by columns rather than rows for analytical queries
  • b) A type of vertical partitioning
  • c) A backup storage format
  • d) A method to encrypt columns
Answer: A - Columnar storage improves compression and speeds up aggregate queries (used in Redshift, BigQuery).

106. What is the purpose of the SQL SYSTEM_TIME period?

  • a) To track when data was stored in the database (transaction-time)
  • b) To measure query execution time
  • c) To schedule database maintenance
  • d) To record system uptime
Answer: A - SYSTEM_TIME captures when data became current in the database (as opposed to application-time).

107. Which of the following is NOT a graph database?

  • a) Neo4j
  • b) Amazon Neptune
  • c) ArangoDB
  • d) MongoDB
Answer: D - MongoDB is a document database, though it can model graph-like structures.

108. What is a property graph model?

  • a) A graph structure where nodes and relationships can have properties
  • b) A database for real estate data
  • c) A method to index graph properties
  • d) A visualization technique
Answer: A - Property graphs allow key-value pairs on both nodes (vertices) and edges (relationships).

109. What is the purpose of the SQL VALIDTIME clause?

  • a) To query data as it appeared at a specific application-time
  • b) To validate time formats
  • c) To check database uptime
  • d) To measure query performance
Answer: A - VALIDTIME (in temporal SQL) filters data based on application-time periods.

110. What is a hypertable in time-series databases?

  • a) A virtual table that automatically partitions data by time
  • b) A table with extra time columns
  • c) A compressed historical data table
  • d) A wide table with many columns
Answer: A - Hypertables (e.g., in TimescaleDB) manage time-series data partitioning transparently.

111. Which of the following is a RDF query language?

  • a) SPARQL
  • b) Cypher
  • c) Gremlin
  • d) GraphQL
Answer: A - SPARQL queries semantic web data stored as RDF triples.

112. What is the purpose of the SQL PERIOD FOR clause?

  • a) To define temporal periods in temporal tables
  • b) To specify report generation periods
  • c) To limit backup retention periods
  • d) To define maintenance windows
Answer: A - PERIOD FOR declares valid-time or transaction-time periods in SQL:2011 temporal tables.

113. What is a triple store in graph databases?

  • a) A database that stores subject-predicate-object triples
  • b) A backup with three copies
  • c) A three-column table
  • d) A type of index
Answer: A - Triple stores specialize in RDF data (e.g., "Alice-knows-Bob").

114. What is the difference between valid-time and transaction-time?

  • a) Valid-time is when data was true in reality, transaction-time is when it was recorded
  • b) Valid-time tracks transactions, transaction-time tracks business validity
  • c) They are synonyms
  • d) Valid-time is for applications, transaction-time is for backups
Answer: A - Valid-time represents the real-world time period, transaction-time the database's view timeline.

115. Which algorithm is commonly used for graph pathfinding?

  • a) Dijkstra's algorithm
  • b) Bubble sort
  • c) Consistent hashing
  • d) B-tree traversal
Answer: A - Dijkstra's finds shortest paths between nodes in weighted graphs.

116. What is temporal projection in queries?

  • a) Retrieving data as it appeared at a past time
  • b) Forecasting future database states
  • c) Estimating query execution time
  • d) A visualization technique
Answer: A - Temporal projection enables "time travel" queries on historical data.

117. What is a graph database index-free adjacency?

  • a) Direct pointer-based navigation between nodes without index lookups
  • b) A graph without indexes
  • c) A special adjacency matrix
  • d) An optimization for isolated nodes
Answer: A - Native graph databases traverse relationships physically, avoiding index hops.

118. What is the purpose of the SQL SEQUENCE data type?

  • a) To generate ordered numeric values
  • b) To store DNA sequences
  • c) To track query execution order
  • d) To implement queues
Answer: A - SEQUENCE objects generate unique numbers (often for surrogate keys).

119. What is a graph database's advantage for fraud detection?

  • a) Efficiently traversing relationships to find suspicious patterns
  • b) Better storage of financial amounts
  • c) Faster aggregation of totals
  • d) Built-in fraud detection algorithms
Answer: A - Graph databases excel at pattern matching across relationships (e.g., detecting rings).

120. What is temporal normalization?

  • a) Structuring temporal data to minimize redundancy while preserving time semantics
  • b) Converting all timestamps to UTC
  • c) Regular database normalization with time columns
  • d) A backup rotation scheme
Answer: A - Temporal normalization extends traditional normalization with time-aware constraints.
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