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Vansh Khandelwal

Stealthย โ€ขย 1m

๐‚๐ก๐จ๐จ๐ฌ๐ข๐ง๐  ๐ญ๐ก๐ž ๐ซ๐ข๐ ๐ก๐ญ ๐๐š๐ญ๐š๐›๐š๐ฌ๐ž ๐ข๐ง ๐ฐ๐ž๐› ๐๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ฆ๐ž๐ง๐ญ. ๐’๐๐‹ ๐๐š๐ญ๐š๐›๐š๐ฌ๐ž๐ฌ, like MySQL and PostgreSQL, use structured query language (SQL) for structured data, ensuring ACID compliance for reliability. They're ideal for complex queries and transactions. ๐๐จ๐’๐๐‹ ๐๐š๐ญ๐š๐›๐š๐ฌ๐ž๐ฌ, such as MongoDB and Cassandra, handle unstructured data with flexible schemas. They excel in scalability and performance for large datasets. Types include document, key-value, column-family, and graph databases. ๐๐ž๐ฐ๐’๐๐‹ ๐๐š๐ญ๐š๐›๐š๐ฌ๐ž๐ฌ, like Google Spanner, combine SQL's ACID properties with NoSQL's scalability, suitable for web-scale applications. When choosing, consider data structure, scalability, consistency, and query needs. SQL suits structured data and complex queries, while NoSQL is best for scalability and varied data types. NewSQL offers a balanced approach.

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