Need to know the benefits of NoSQL Databases?
This guide is for you.
NoSQL is a non-relational database management system that is a bit different from traditional relational database management systems.
Above all the design of NoSQL is in such a way that it stores distributed data on a large scale and has a fixed schema.
MongoDB is a NoSQL database that we widely use as it offers very quick write speeds, fast querying. Also, it can easily distribute large data sets across a cluster of servers.
NoSQL seems to work better on both unstructured and unrelated data. NoSQL databases give up some features of the traditional databases for speed and horizontal scalability.
In this context, we shall look into some advantages of NoSQL Databases.
Five Benefits of NoSQL Databases
The following are the main benefits of NoSQL Databases:
1. Elastic scaling
Scale-up was done for a long time by database admins. Scale-up means buying bigger servers as database load increases.
Nowadays, scale-out is found more reliable, scale-out means distributing the database across multiple hosts as load increases.
The economic advantages of scaling out on commodity hardware become irresistible.
Meanwhile, RDBMS might not scale out easily on commodity clusters. The design of NoSQL databases helps to expand transparently to take advantage of new nodes.
2. Big data
Over the decade, an increasing amount of data large volumes of data are being stored massively. The constraints of data volumes that are being managed by a single RDBMS are concerning some enterprises.
Today, NoSQL systems such as Hadoop handle the volumes of “big data” better than RDBMS.
3. Goodbye DBAs
Maintaining high-end RDBMS systems can be done only with the assistance of expensive, highly trained DBAs.
Generally, the design of NoSQL databases requires less management. Moreover, it does the automatic repair, data distribution, and simpler data models lead to lower administration and tuning requirements.
NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes.
The result is that the cost per gigabyte or transaction/second for NoSQL is many times less. Thus, allowing us to store and process more data at a much lower price point.
5. Flexible data models
NoSQL databases have fewer or no data model restrictions than RDBMS. However, NoSQL Key Value stores and document databases allow the application to store virtually any structure it wants in a data element.
A few characteristics associated with a NoSQL database
Following are a few characteristics of a NoSQL database:
1. It doesn't use SQL as its query language:
NoSQL database systems rose alongside major internet companies, such as Google, Amazon, and Facebook, which had significantly different challenges in dealing with huge quantities of data that the traditional RDBMS solutions could not cope with.
Above all, NoSQL database systems were made in such a way that they can manage large volumes of data that do not necessarily follow a fixed schema.
2. It may not give full ACID guarantees:
Usually, only eventual consistency is guaranteed or limiting transactions to single data items.
3. It has a distributed, fault-tolerant architecture:
Several NoSQL systems employ a distributed architecture. The system can easily scale out by adding more servers and can tolerate the failure of a server.
A database schema is the structure of a database system, described in a formal language supported by the database management system.
In NoSQL, a collection is a group of documents where documents represent a row and collections represent a table in a relational database.
In other words, collections are schema-free, which means they can store different types and structures of documents within a single collection.
5. Horizontally scalable:
To scale horizontally means to scale out. In a NoSQL system, the data store can be much faster as it uses scale-out.
Key Reasons to use a NoSQL database
Following are some of the use cases where it is sub-optimal to use a conventional database:
1. A relational database will not scale to our traffic at an acceptable cost.
2. Supplying data in small updates spread over time.
3. Generally, business models may generate a lot of temporary data that does not really belong in the main data store.
4. Relational database has already been denormalized.
5. When we need to run queries against the data that do not involve simple hierarchical relations.
Types of NoSQL datastores
The following section describes the different types of NoSQL datastores.
1. Key Value stores
Examples: Tokyo Cabinet/Tyrant, Redis, Voldemort, Oracle BDB
2. Document databases
Examples: CouchDB, MongoDB
3. Graph databases
Examples: Neo4J, InfoGrid, Infinite Graph
4. XML databases
Examples: Exist, Oracle, MarkLogic
5. Distributed Peer Stores
Examples: Cassandra, HBase, Riak
6. Object stores
Examples: Oracle Coherence, db4o, ObjectStore, GemStone, Polar