NoSQL database is used for distributed data stores with humongous data storage needs. NoSQL is used for Big data and real-time web apps. NoSQL is a non-relational DMS, that does not require a fixed schema, avoids joins, and is easy to scale. For example, companies like Twitter, Facebook, Google that collect terabytes of user data every single day.
- NoSQL database stands for “Not Only SQL” or “Not SQL.” Though a better term would 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.
Why NoSQL Database
- 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.”
History
- 1998- Carlo Strozzi use the term NoSQL for his lightweight, open-source relational database
- 2000- Graph database Neo4j is launched
- 2004- Google BigTable is launched
- 2005- CouchDB is launched
- 2007- The research paper on Amazon Dynamo is released
- 2008- Facebooks open sources the Cassandra project
- 2009- The term NoSQL was reintroduced
Features NoSQL
Non-relational
- NoSQL databases never follow the relational model.
- Never provide tables with flat fixed-column records.
- Work with self-contained aggregates or BLOBs.
- Doesn’t require object-relational mapping and data normalization.
- No complex features like query languages, query planners, referential integrity joins, ACID.
Schema-free
- NoSQL databases are either schema-free or have relaxed schemas.
- Do not require any sort of definition of the schema of the data.
- Offers heterogeneous structures of data in the same domain.
Data Models
- Key-value Pair Based
- Column-oriented Graph
- Graphs based
- Document-oriented
Key Value Pair Based
- Data 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”.
- 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 examples of column based database.
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.
A 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.
- 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
- Availability
- Partition Tolerance
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 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.
Advantages NoSQL Database
- Can be used as Primary or Analytic Data Source
- Big Data Capability
- No Single Point of Failure
- Easy Replication
- No Need for Separate Caching Layer
- It provides fast performance and horizontal scalability.
- Can handle structured, semi-structured, and unstructured data with equal effect
- Object-oriented programming which is easy to use and flexible
- NoSQL databases don’t need a dedicated high-performance server
- Support Key Developer Languages and Platforms
- Simple to implement than using RDBMS
- It can serve as the primary data source for online applications.
- Handles big data which manages data velocity, variety, volume, and complexity
- Excels at distributed database and multi-data center operations
- Eliminates the need for a specific caching layer to store data
- Offers a flexible schema design which can easily be altered without downtime or service disruption
Disadvantages of NoSQL
- No standardization rules.
- Limited query capabilities.
- RDBMS databases and tools are comparatively mature
- It does not offer any traditional database capabilities, like consistency when multiple transactions are performed simultaneously.
- When the volume of data increases it is difficult to maintain unique values as keys become difficult.
- Doesn’t work as well with relational data.
- The learning curve is stiff for new developers.
Open source options so not so popular for enterprises.
Summary
- NoSQL is a non-relational DMS, that does not require a fixed schema, avoids joins, and is easy to scale
- The concept of NoSQL databases beccame popular with Internet giants like Google, Facebook, Amazon, etc. who deal with huge volumes of data
- In the year 1998- Carlo Strozzi use the term NoSQL for his lightweight, open-source relational database
- NoSQL databases never follow the relational model it is either schema-free or has relaxed schemas
- Four types of NoSQL Database are 1). Key-value Pair Based 2). Column-oriented Graph 3). Graphs based 4). Document-oriented
- NOSQL can handle structured, semi-structured, and unstructured data with equal effect
CAP theorem consists of three words Consistency, Availability, and Partition Tolerance
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