PostgreSQL, a popular open-source relational database system can be used as a hybrid database to handle both structured and semi-structured data. PostgreSQL’s support for JSON and JSONB object types allows for flexible data modelling and can solve many of the same problems that NoSQL databases are made to address. By Leslie S. Gyamfi.
The rise of digital technology in this age has made data a pivotal component for businesses, leading to the need for efficient database management systems.
The main parts of this article:
- SQL vs. NoSQL
- Specific features of PostgreSQL also applicable to NoSQL
- JSON and JSONB object types can help bridge the NoSQL
- JSON and JSONB: What are the differences?
- Working with JSON data in PostgreSQL
- Querying JSON data
- Querying JSON arrays
- Working with JSONB data in PostgreSQL
- Indexing JSONB data using the ‘GIN’ index
- Cases where PostgreSQL’s NoSQL features can be particularly useful
- A comparison of JSON in Postgres and NoSQL
While NoSQL databases like MongoDB are known for their flexibility and ability to handle unstructured data, some relational databases like PostgreSQL offer support for JSON and JSONB data types along with its relational database management system features, thus providing a practical and fully-fledged alternative to NoSQL databases. With its SQL-based querying capabilities and ACID compliance, PostgreSQL is an attractive option for developers who need NoSQL scalability, but still require the power of SQL. Nice one!
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