A nosql database can use tabular data, key-value collections, multilevel structures and graphs.
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NoSQL Database is a non-relational Data Management System, that does not require a fixed schema. It avoids joins, and is easy to scale. The major purpose of using a NoSQL database is for distributed data stores with humongous data storage needs. NoSQL is used for Big data and real-time web apps. For example, companies like Twitter, Facebook and Google collect terabytes of user data every single day. Show
NoSQL database stands for “Not Only SQL” or “Not SQL.” Though a better term would be “NoREL”, NoSQL caught on. Carl Strozz introduced the NoSQL concept in 1998. Traditional RDBMS uses SQL syntax to store and retrieve data for further insights. Instead, a NoSQL database system encompasses a wide range of database technologies that can store structured, semi-structured, unstructured and polymorphic data. Let’s understand about NoSQL with a diagram in this NoSQL database tutorial: In this NoSQL tutorial for beginners, you will learn NoSQL basics like:
Why NoSQL?The concept of NoSQL databases became popular with Internet giants like Google, Facebook, Amazon, etc. who deal with huge volumes of data. The system response time becomes slow when you use RDBMS for massive volumes of data. To resolve this problem, we could “scale up” our systems by upgrading our existing hardware. This process is expensive. The alternative for this issue is to distribute database load on multiple hosts whenever the load increases. This method is known as “scaling out.” NoSQL database is non-relational, so it scales out better than relational databases as they are designed with web applications in mind. Brief History of NoSQL Databases
Features of NoSQLNon-relational
Schema-free
 NoSQL is Schema-Free Simple API
Distributed
NoSQL is Shared Nothing. Types of NoSQL DatabasesNoSQL Databases are mainly categorized into four types: Key-value pair, Column-oriented, Graph-based and Document-oriented. Every category has its unique attributes and limitations. None of the above-specified database is better to solve all the problems. Users should select the database based on their product needs. Types of NoSQL Databases:
Key Value Pair BasedData is stored in key/value pairs. It is designed in such a way to handle lots of data and heavy load. Key-value pair storage databases store data as a hash table where each key is unique, and the value can be a JSON, BLOB(Binary Large Objects), string, etc. For example, a key-value pair may contain a key like “Website” associated with a value like “Guru99”. It is one of the most basic NoSQL database example. This kind of NoSQL database is used as a collection, dictionaries, associative arrays, etc. Key value stores help the developer to store schema-less data. They work best for shopping cart contents. Redis, Dynamo, Riak are some NoSQL examples of key-value store DataBases. They are all based on Amazon’s Dynamo paper. Column-basedColumn-oriented databases work on columns and are based on BigTable paper by Google. Every column is treated separately. Values of single column databases are stored contiguously. Column based NoSQL database They deliver high performance on aggregation queries like SUM, COUNT, AVG, MIN etc. as the data is readily available in a column. Column-based NoSQL databases are widely used to manage data warehouses, business intelligence, CRM, Library card catalogs, HBase, Cassandra, HBase, Hypertable are NoSQL query examples of column based database. Document-Oriented:Document-Oriented NoSQL DB stores and retrieves data as a key value pair but the value part is stored as a document. The document is stored in JSON or XML formats. The value is understood by the DB and can be queried. Relational Vs. Document In this diagram on your left you can see we have rows and columns, and in the right, we have a document database which has a similar structure to JSON. Now for the relational database, you have to know what columns you have and so on. However, for a document database, you have data store like JSON object. You do not require to define which make it flexible. The document type is mostly used for CMS systems, blogging platforms, real-time analytics & e-commerce applications. It should not use for complex transactions which require multiple operations or queries against varying aggregate structures. Amazon SimpleDB, CouchDB, MongoDB, Riak, Lotus Notes, MongoDB, are popular Document originated DBMS systems. Graph-BasedA graph type database stores entities as well the relations amongst those entities. The entity is stored as a node with the relationship as edges. An edge gives a relationship between nodes. Every node and edge has a unique identifier. Compared to a relational database where tables are loosely connected, a Graph database is a multi-relational in nature. Traversing relationship is fast as they are already captured into the DB, and there is no need to calculate them. Graph base database mostly used for social networks, logistics, spatial data. Neo4J, Infinite Graph, OrientDB, FlockDB are some popular graph-based databases. Query Mechanism tools for NoSQLThe most common data retrieval mechanism is the REST-based retrieval of a value based on its key/ID with GET resource Document store Database offers more difficult queries as they understand the value in a key-value pair. For example, CouchDB allows defining views with MapReduce What is the CAP Theorem?CAP theorem is also called brewer’s theorem. It states that is impossible for a distributed data store to offer more than two out of three guarantees
Consistency: The data should remain consistent even after the execution of an operation. This means once data is written, any future read request should contain that data. For example, after updating the order status, all the clients should be able to see the same data. Availability: The database should always be available and responsive. It should not have any downtime. Partition Tolerance: Partition Tolerance means that the system should continue to function even if the communication among the servers is not stable. For example, the servers can be partitioned into multiple groups which may not communicate with each other. Here, if part of the database is unavailable, other parts are always unaffected. Eventual ConsistencyThe term “eventual consistency” means to have copies of data on multiple machines to get high availability and scalability. Thus, changes made to any data item on one machine has to be propagated to other replicas. Data replication may not be instantaneous as some copies will be updated immediately while others in due course of time. These copies may be mutually, but in due course of time, they become consistent. Hence, the name eventual consistency. BASE: Basically Available, Soft state, Eventual consistency
Advantages of NoSQL
Disadvantages of NoSQL
Summary
Can NoSQL store structured data?NoSQL databases can store structured, semi-structured and unstructured data. Their main advantages focus on semi-structured (JSON, XML, not all fields are known) and unstructured. But, you can safely store BLOB in a RDBMS, e. g., Oracle Database and many others relational databases.
What type of data does NoSQL use?Overview. NoSQL databases store data in documents rather than relational tables. Accordingly, we classify them as "not only SQL" and subdivide them by a variety of flexible data models. Types of NoSQL databases include pure document databases, key-value stores, wide-column databases, and graph databases.
Do NoSQL databases have keys?Unlike relational databases, NoSQL databases are based on key-value pairs. Some store types of NoSQL databases include column store, document store, key value store, graph store, object store, XML store, and other data store modes. Usually, each value in the database has a key.
Is a NoSQL database used for graph theory?Graph Databases – A graph database is a type of NoSQL database that stores data as collections of nodes and edges rather than columns and rows. Each edge defines a relationship between two nodes, whereas each node represents a data point. To show how data points are connected, graph databases use graph theory models.
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