NoSQL Versus SQL: 7 Critical Differences
posted by Anna Mar, December 16, 2012NoSQL databases were developed by companies such as Google, Yahoo and Facebook as a means for dealing with massive quanities of data.
As the name suggests, NoSQL databases don't use standard query language (SQL). They also have profoundly different performance characteristics and architectures from traditional relational databases (SQL databases).
The key differences to remember are:
1. NoSQL is about big data (mostly)
NoSQL tools evolved as a means of managing large volumes of data. In other words, they scale horizontally.2. NoSQL databases are less structured
Data in a NOSQL database doesn't necessarily follow a fixed schema. It's ideal for processing mixed sets of structured and unstructured data.3. NoSQL doesn't maintain complex relationships between data
NoSQL is about accessing large amounts of data with simple data structures such as collections of key/value pairs. Complex relationships between data aren't typically maintained.4. NoSQL doesn't give many guarantees
Relational databases guarantee atomicity, consistency, isolation and durability (ACID) of transactions. NoSQL makes no such guarantees.In many cases, NoSQL databases may only guarantee that data will eventually be consistent if there's enough time and processing power.
5. NoSQL is distributed and fault-tolerant
NoSQL is typically a distributed processing technology (e.g. deployed to cloud). Data may be replicated many times across the architecture with no single point of failure.6. NoSQL lacks the run-time power of SQL
SQL is far more flexible for runtime operations. It can leverage relationships between data to execute complex queries.7. NoSQL and SQL Databases Are Often Used Together
NoSQL and SQL databases solve different problems.NoSQL can process large amounts of structured and unstructured data. SQL can represent complex relationships between data and process complex queries.
It's common for a single solution to leverage both NoSQL and SQL technologies.
Big Data
Technologies built to handle data volume, variety and velocity.
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