High-throughput streaming with Bigtable

What is Bigtable particularly suited for?

• Low-throughput applications

• Highly structured data

• Real-time lookup capacity with high throughput

• Small data volumes less than 1 TB

What is a limitation of BigQuery mentioned in the script?

• High latency

• Limited storage capacity

• Lack of SQL support

• Inability to handle structured data

What is the primary index used in Bigtable?

• Column index

• Row Key

• Timestamp index

• Metadata index

How does Bigtable handle "hot spots" of activity?

• It deletes the overactive Tablet

• It splits the Tablet in two

• It moves the Tablet to another cluster

• It compresses the Tablet

What is a common use case for Bigtable mentioned in the script?

• Processing small transactional data

• Running SQL queries and joins

• Storing machine learning model training data

• Handling time-series data such as CPU usage

How does Bigtable store data?

• In relational databases

• In tables with rows and columns

• In unstructured text files

• In blockchain format

What design principle does Bigtable use for speed?

• Complex indexing

• Multiple secondary indexes

• Reduced Instruction Set Computing (RISC)

• Hierarchical data structures

What is a constructed Row Key used for in Bigtable?

• To add multiple indexes

• To avoid scanning the entire table

• To enable SQL-like joins

• To increase data redundancy

How does Bigtable ensure efficient data retrieval from Column Families?

• By compressing all data

• By using multiple secondary indexes

• By grouping related rows into families

• By sorting all rows alphabetically

What happens when data is deleted in Bigtable?

• It is immediately removed

• It is marked for deletion and skipped during processing

• It is archived in a separate database

• It triggers a table reorganization immediately