The term ‘NoSQL’ refers to nonrelational types of databases, and these databases store data in a format that’s different from relational tables. However, NoSQL databases can be queried using idiomatic language APIs, declarative structured query languages, and query-by example languages, which is why they are also referred to as “not only SQL” databases.
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With SQL databases, data is stored in a much more rigid, predefined structure. But with NoSQL, data can be stored in a more free-form fashion without those rigid schemas. This design enables innovation and rapid application development.
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Instead of scaling up by adding more servers, NoSQL databases can scale out by using commodity hardware. This has the ability to support increased traffic in order to meet demand with zero downtime. By scaling out, NoSQL databases can become larger and more powerful, which is why they have become the preferred option for evolving data sets.
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The scale-out architecture of a NoSQL database can be particularly valuable when data volume or traffic increases.NoSQL databases can also ingest data and deliver it quickly and reliably, which is why NoSQL databases are used in applications that collect terabytes of data every day, while also requiring a highly interactive user experience.
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NoSQL databases automatically replicate data across multiple servers, data centers, or cloud resources. In turn, this minimizes latency for users, no matter where they’re located. This feature also works to reduce the burden of database management, which frees up time to focus on other priorities.
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NoSQL databases are designed for distributed data stores that have extremely large data storage needs. This is what makes NoSQL the ideal choice for big data, real-time web apps, online shopping, online gaming, Internet of things, social networks, and online advertising applications.
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- It is document-oriented database.
- It stores data in JSON-like documents with optional schemas.
- Fast retrieval of individual documents, much like key-value stores, but can also support complex queries with aggregation pipelines.
- It also offers indexing, ad hoc queries and real-time aggregation to powerfully access and analyze data.
- It comes with higher availability, geographical distribution, and horizontal scalability.
- It also provides SSL, encryption and firewall security for its client, making it the top choice for application developers.
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- It is a column-oriented, non-relational database that works on the Hadoop Database File System.
- It is used when you randomly need real-time read/write access to Big Data.
- Excellent when aggregating values on particular columns, with strong compression and in-memory support.
- It provides linear scalability, consistent read/write, automatic configurable table sharding, easy-to-use Java API for client access, real-time queries and so much more.
- It is based on Google’s Bigtable, a distributed storage system for structured data to offer Bigtable-like capabilities for applications.
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- It is a graph-based NoSQL database.
- It provides an ACID-compliant transactional application backend, runtime failover, and cluster support.
- Fast for simple queries, but also efficient when answering questions about connections between data; excels when profiling data and determining clusters of related objects.
- The cypher query language, constant time traversals, drivers for programming languages like JavaScript, Java, Go, and Python, and flexibility offered by Neo4j makes it easier to work with.
- As Neo4j connects the data when stored in the database, it can quickly access the data again than conventional databases.
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- It is a Key-value store database.
- It supports many different data structures such as strings, lists, hashes, sets, sorted sets, etc.
- It is written in ANSI C and can be used with nearly all of the programming languages and Linux and OS X operating systems.
- Best for instantaneous retrieval when queries are not complex; useful for caching use cases.
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- It is a document-oriented, single node NoSQL database.
- It allows you to store your data with JSON documents and easily access it through a web browser.
- It uses multiple protocols and formats to store, process and transfer data.
- For demanding projects, CouchDB can scale up into a cluster of nodes with multiple servers.
- It has been designed with a crash-resistant structure and reliability that supports “offline first” apps and a system that redundantly saves data to keep it secure and available in case of emergency.