JSON (JavaScript Object Notation) has become a standard data-interchange format, particularly for semi-structured data. JSON databases are part of the NoSQL family of databases that offer flexibility in storing varied data types and easily accommodating changes in data model or project requirements. The flexibility of a JSON database comes from the way data is stored—as documents instead of rigid tables. Read on to know more.
Table of Contents:
- What are JSON databases?
- Advantages of JSON databases
- JSON database examples
- The best database for JSON
What are JSON databases?
A JSON database is a document-type NoSQL database, ideal for storing semi-structured data. It’s much more flexible compared to the row-columns format, which is fixed and expensive when it comes to implementing even small schema changes.
With relational databases, JSON data needs to be parsed or stored using the NVARCHAR column (LOB storage). However, document databases like MongoDB can store JSON data in its natural format, which is readable by humans and machines.
There are two ways to store JSON data in a JSON database:
1. Store the whole object in a single document.
Example:
Here, the author details are inside the book document itself. This technique is also known as embedding because the author subdocument is embedded in the book document.
2. Store parts of objects separately and link them using the unique identifiers (referencing).
One author may write multiple books. So, to avoid duplicating data inside all the books, we can create separate author document and refer to it by its _id field:
Advantages of JSON databases
Just like traditional databases, JSON document databases manage data partitioning, indexing, clustering, replication, and data access on their own. Apart from this, JSON databases offer many advantages.
JSON databases are faster and have more storage flexibility
NoSQL databases, in general, have more storage flexibility and offer better indexing methods. In a document database, each document is handled as an individual object, and there is no fixed schema, so you can store each document in the way it can be most easily retrieved and viewed. Additionally, you can evolve your data model to adapt it to your changing application requirements. The schema versioning pattern makes use of the flexible document model to allow just that.
JSON databases provide better schema flexibility
The best part of a JSON document database is the schema flexibility—i.e., it supports whatever way you want to store your data. You can have all the information that you need to access together (embedding) in one document or take the liberty of creating separate documents and then linking them (referencing). It’s very simple to even query the nested objects inside a document, like nested arrays or embedded documents.
JSON databases can easily map to SQL structures
Many developers are familiar with SQL. By storing data in a JSON database, developers can simply map SQL columns and JSON document key names. For example, the bookName key of a document can be mapped to the book_name column of the book table. Most JSON databases automate this mapping, which saves on a developer’s learning curve and reduces the development time.
JSON databases support different index types
Due to the availability of various index types, search queries are quite fast. For example, since MongoDB has no fixed schema, you can create a wildcard index on a field or set of fields to support querying that field. There are many other types of indexes, like O2-tree and T-tree, that make NoSQL databases highly performant.
JSON databases are better suited for big data analytics
JSON databases have a flexible schema and scale well vertically and horizontally, making them suitable to store huge volumes and a variety of big data. Document databases like MongoDB have a rich query language (MQL) and aggregation pipeline, eliminating the need for ETL systems for data processing and transformation. Further, these databases can easily pass data to popular data analysis programming languages like Python and R, without additional coding steps.
JSON database examples
There are many JSON databases:
The best database for JSON
JSON format stores data in the form of objects. The syntax is simple and readable for anyone. A JSON database like MongoDB stores the data in a JSON-like format (binary JSON), which is the binary encoded version of JSON, and is optimized for performance and space.
This makes the MongoDB database the best natural fit for storing JSON data. You can store details of an entire object in one document, making it easier to view and query. MongoDB is the most popular JSON database as it offers many other benefits, like:
- Flexible schema.
- Storage for semi-structured data.
- Speed, flexibility, and space efficiency.
- Retained data format, making it easier to map objects and run queries.
- No need for any additional processing, like parsing or creating complex large objects.