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SQL databases require a predefined schema, with strict data types for each column. NoSQL databases allow for dynamic, flexible schemas without the need to predefine the structure.

SQL databases support complex JOIN operations, allowing for the combination of data from multiple tables. NoSQL databases generally lack native JOIN operations and instead advocate for denormalized data models or application-level joins.

SQL databases offer ACID transactions, ensuring atomicity, consistency, isolation, and durability. NoSQL databases prioritize availability and partition tolerance over strict ACID compliance, with varying degrees of support for transactions.

SQL databases have built-in mechanisms for data replication, which can be master-slave or master-master. NoSQL databases are generally designed with replication in mind from the outset, often providing automatic sharding and built-in, distributed replication.

SQL databases typically scale vertically, requiring more powerful hardware to improve performance. NoSQL databases are designed to scale horizontally, by distributing data across multiple servers or nodes.

SQL databases use normalized data models to reduce data redundancy and ensure data integrity. NoSQL databases often use denormalized data models, which can increase performance by reducing the need for JOIN operations.

SQL databases handle concurrency via locking mechanisms and transactions to maintain consistency. NoSQL databases handle concurrency differently, often by eventual consistency models and other non-locking approaches like last-write-wins.

SQL databases support a range of structured data types like integer, float, char, varchar, etc. NoSQL databases, depending on the type (key-value, document, columnar, graph), can support a wide range of unstructured data types like JSON, XML, and more.

SQL databases use the structured query language (SQL) with its standardized syntax. NoSQL databases use various query languages or APIs, which are often proprietary and non-standardized.