Best 14 Document Databases products
What is Document Databases?
Document databases are a type of non-relational database designed to store, retrieve, and manage document-oriented info, usually in JSON, BSON, or XML format. They focus on flexibility and scalability, making them great for handling semi-structured data without fixed schemas.
What are the top 10 IT Infrastructure Software products for Document Databases?
Newest Document Databases Products
Document Databases Core Features
- Stores data as documents rather than rows and columns
- Supports flexible schemas allowing varied document structures
- Provides powerful querying on document contents
- Scales easily horizontally across servers
- Often supports indexing on fields inside documents
Advantages of Document Databases?
- Flexible data models adapt quickly to change
- Easy to scale horizontally
- Better fits complex nested data than relational
- Simplifies development for evolving apps
- Usually offers fast reads and writes for doc data
Who is suitable to use Document Databases?
Ideal for developers handling content management systems, real-time analytics, and apps with evolving data structures. Great for startups and companies needing fast iteration on their data models.
How does Document Databases work?
Data gets stored in collections of documents. Each document contains key-value pairs and can differ in structure from others. The database indexes these documents to enable quick searches. Clients query and update documents via APIs with flexible query languages, often JSON-based.
FAQ about Document Databases?
Are document databases the same as relational databases?
Nope, document DBs store data as flexible documents rather than tables with fixed schemas like relational DBs.
Can I query nested data in document databases?
Yeah, most support powerful querying on nested fields inside documents.
Do document databases support transactions?
Many support multi-document transactions but usually less strict than relational DBs.
Are document databases good for big data?
They can handle large volumes if designed right, especially with horizontal scaling.
Is schema design important in document databases?
Even tho flexible, good schema design helps performance and maintainability.
