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Clear filtersINNER JOIN returns only rows that have a match in both tables, while LEFT JOIN returns every row from the left table and fills the right table's columns with NULL when there is no match.
DELETE removes selected rows and can be rolled back, TRUNCATE quickly removes all rows and keeps the table structure, and DROP removes the entire table including its structure.
A primary key uniquely identifies each row in its own table and cannot be NULL, while a foreign key is a column that references the primary key of another table to link the two.
Volumes are storage managed by Docker that lives outside a container鈥檚 writable layer, so data such as database files survives when the container is removed or replaced.
Normalization is organising tables to reduce redundancy and update anomalies: 1NF means atomic values, 2NF removes partial dependencies on part of a composite key, and 3NF removes dependencies between non-key columns.
ACID stands for Atomicity, Consistency, Isolation and Durability: a transaction either fully succeeds or fully fails, keeps the data valid, does not interfere with other transactions, and survives crashes once committed.
An index is a separate sorted data structure (usually a B-tree) that lets the database find rows without scanning the whole table, at the cost of extra storage and slower writes.
A clustered index defines the physical order in which the table's rows are stored, so there can be only one per table, while a non-clustered index is a separate structure that points back to the rows.
IEnumerable runs the query in memory using delegates, while IQueryable builds an expression tree that a provider such as Entity Framework translates into SQL, so filtering happens in the database.
Choose SQL when your data is relational and you need transactions, joins and strong consistency; choose NoSQL when you need flexible schemas, very high write throughput or horizontal scaling for a specific access pattern.
Isolation levels (Read Uncommitted, Read Committed, Repeatable Read, Serializable) control how much concurrent transactions can see of each other's changes, trading consistency against concurrency to prevent dirty reads, non-repeatable reads and phantom reads.
Read the execution plan with EXPLAIN to find full scans and expensive joins, add or fix indexes for the filter and join columns, select only the columns and rows you need, and rewrite predicates so indexes can be used.
Generate a short unique code for each long URL (for example by base62-encoding a unique ID), store the mapping in a key-value or relational database, serve redirects through a cache because reads far outnumber writes, and record analytics asynchronously.
The CAP theorem says that during a network partition a distributed system must choose between consistency (every read sees the latest write) and availability (every request gets a response); you cannot have both while the partition lasts.
Replication copies the same data to several servers to improve read capacity and availability, while sharding splits the data across servers so each holds only a part, which increases write capacity and total storage.