Here's a comprehensive paper on the concept of "database" (abbreviated as "db"):
MongoDB (Document), Cassandra (Wide-column), Redis (Key-value). C. Vector Databases Here's a comprehensive paper on the concept of
Selecting a database depends on the specific needs of a project: IBM’s IMS (Information Management System) is a classic
If you are building a new application, ask these three questions: This is how social media giants handle billions of users
The first databases were navigational, using hierarchical structures (like a family tree) or network structures. IBM’s IMS (Information Management System) is a classic example. While revolutionary, these systems were rigid; if you wanted to view the data differently, you often had to rebuild the entire DB.
Splitting a single logical DB into multiple physical DBs across servers. This is how social media giants handle billions of users.
Today, we want the best of both worlds: the ACID compliance of SQL and the scalability of NoSQL. This has given rise to (Google Spanner, CockroachDB) and Cloud Databases (Amazon RDS, Azure SQL, Snowflake).
