What are the advantages of using Type 3 Slowly Changing Dimensions (SCD) over other types?

  • Allows for easy querying
  • Captures both current and historical data
  • Facilitates easy updates
  • Requires less storage space
Type 3 SCD is advantageous as it captures both current and historical data. It maintains a separate column for historical changes, providing a snapshot of changes over time without excessive storage requirements. This is particularly useful for scenarios where a limited history is needed.

_______ indexing is an approach where the index is built on multiple columns to speed up queries involving those columns.

  • Clustered
  • Composite
  • Non-clustered
  • Unique
Composite indexing is an approach where the index is built on multiple columns. This technique is beneficial for optimizing query performance, especially when queries involve those specific columns.

How do graph databases typically handle queries involving traversing relationships?

  • By converting them into SQL queries
  • By ignoring relationships in queries
  • By restricting the depth of traversal
  • By using specialized graph query languages like Cypher
Graph databases typically handle queries involving traversing relationships using specialized graph query languages like Cypher. Cypher is designed to express patterns and relationships in the graph, making it more intuitive and efficient for querying graph databases compared to traditional SQL queries.

What are some strategies for handling data partitioning in distributed Key-Value Stores?

  • Consistent Hashing, Range Partitioning, and Composite Key Partitioning
  • Indexing, Normalization, and Horizontal Partitioning
  • Replication, Atomicity, and Data Warehousing
  • Vertical Partitioning, Denormalization, and Sharding
Strategies for handling data partitioning in distributed Key-Value Stores include Consistent Hashing, Range Partitioning, and Composite Key Partitioning. These techniques help distribute data evenly across nodes, ensuring efficient data retrieval and storage in distributed environments.

How does data partitioning work in column-family stores?

  • Data is partitioned based on column names
  • Data is partitioned based on row keys
  • Data is partitioned based on timestamp
  • Partitioning is not applicable in column-family stores
In column-family stores, data partitioning is typically based on row keys. Rows with similar or related keys are stored together, allowing for efficient retrieval of data within a specific partition. This enhances performance by minimizing the need to scan the entire database for relevant records.

What is the significance of query caching in database performance tuning?

  • It decreases the storage space required for query results
  • It enhances the security of SQL queries, preventing unauthorized access
  • It increases the complexity of SQL queries, leading to better performance
  • It reduces the need to re-execute identical queries, improving response time
Query caching plays a crucial role in database performance tuning by storing the results of frequently executed queries in memory. This reduces the need to re-execute identical queries, thereby improving response time and overall system performance. However, it is essential to manage query caching effectively to ensure that cached data remains consistent and up-to-date.

A _______ key uniquely identifies a record within a table.

  • Candidate
  • Composite
  • Foreign
  • Primary
A Primary Key uniquely identifies a record within a table. It ensures that each row in the table is unique, and it serves as the basis for establishing relationships with other tables.

Each row in a column-family store is identified by a unique _______.

  • Cell
  • Column
  • Key
  • Value
Each row in a column-family store is identified by a unique key. This key is used to retrieve and distinguish the row from others in the same family. The key is crucial for efficient data retrieval in column-family stores.

Scenario: A social media platform wants to implement a recommendation system based on users' connections and interactions. Which type of database would be most suitable for storing and querying this data, considering its highly interconnected nature?

  • Document Database
  • Graph Database
  • NoSQL Database
  • Relational Database
For a recommendation system based on interconnected data, a Graph Database would be most suitable. Graph databases excel at representing and querying relationships between entities, making them ideal for scenarios where the connections between data points are crucial, such as social networks.

_______ is a technique used to improve query performance by limiting the partitions that need to be scanned.

  • Clustering
  • Indexing
  • Replication
  • Sharding
Sharding is a technique used to improve query performance by limiting the partitions that need to be scanned. It involves dividing a large database into smaller, more manageable parts called shards, which can be processed independently.