What are non-relational databases?

Common non-relational databases include: 1. mongodb; 2. cassandra; 3. redis; 4. hbase; 5. neo4j; mongodb is a very famous NoSQL database and is a document-oriented open source database.

Common non-relational databases:

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1. MongoDB

MongoDB is the most famous NoSQL database. It is a document-oriented open source database. MongoDB is a scalable and accessible database. It's in c. MongoDB can also be used as a file system. In MongoDB, JavaScript can be used as the query language. MongoDB scales horizontally by using sharding. It is very useful in popular JavaScript frameworks.

People are really enjoying the sharding, advanced text search, gridFS and map-reduce features. Amazing performance and new features put this NoSQL database at the top of our list.

Features: Provides high performance; automatically sharded; runs on multiple servers; supports master-slave replication; data is stored in the form of JSON style documents; indexes any field in the document; because the data is placed in shards , so it has automatic load balancing configuration; supports regular expression searches; and is easy to manage in case of failure.

Advantages: Easy to install MongoDB; MongoDB Inc. provides professional support to customers; supports ad hoc queries; high-speed database; schema-less database; horizontally scalable database; very high performance.

Disadvantages: Connections are not supported; data volume is large; nested documents are limited; unnecessary memory usage is increased.

2. Cassandra

Cassandra was developed by Facebook for inbox search. Cassandra is a distributed data storage system for processing large amounts of structured data. Typically, this data is distributed across many common servers. You can also add data storage capacity to keep your service online, a task you can easily accomplish. Since all nodes in the cluster are identical, there is no need to deal with complex configurations.

Cassandra is written in Java. Cassandra Query Language (CQL) is a SQL-like language for querying Cassandra databases. Therefore, Cassandra ranks second among the best open source databases. Cassandra is used by some of the largest companies such as Facebook, Twitter, Cisco, Rackspace, eBay, Twitter, Netflix, and more.

Features: Linear scalability; Maintaining fast response times; Supporting properties such as atomicity, consistency, isolation, and durability (ACID); Supporting MapReduce using Apache Hadoop; Maximum flexibility in allocating data; Highly Scalable; peer-to-peer architecture.

Advantages: Highly scalable; no single point of failure; Multi-DC replication; tightly integrated with other JVM-based applications; more suitable for multi-data center deployment, redundancy, failover and disaster recovery.

Disadvantages: Limited support for aggregation; unpredictable performance; no support for ad hoc queries.

3. Redis

Redis is a key-value store. Furthermore, it is the most famous key-value store. Redis supports some C, PHP, Ruby, Python, Perl, Scala, etc. Redis is written in C language. Furthermore, it is licensed under BSD.

Features: Automatic failover; Keeps its database entirely in memory; Transactions; Lua scripts; Replicates data to any number of slave servers; Keys have limited lifespan; LRU evicts keys; Supports publish/subscribe.

Pros: Supports multiple data types; easy to install; very fast (about 110,000 groups executed per second, about 81,000 times per second); operations are all atomic; multi-purpose tool (in many use cases used in).

Disadvantages: No support for joins; Lua knowledge required for stored procedures; data set must fit well in memory.

4. HBase

HBase is a distributed, column-oriented open source database. The technology comes from the Google paper "Bigtable: A distributed storage of structured data" written by Fay Chang. system". Just like Bigtable leverages the distributed data storage provided by Google File System, HBase provides Bigtable-like capabilities on top of Hadoop.

HBase is a sub-project of Apache's Hadoop project. HBase is different from general relational databases in that it is a database suitable for unstructured data storage. Another difference is that HBase is column-based rather than row-based.

5. neo4j

Neo4j is called a native graph database because it effectively implements the attribute graph model, all the way to the storage layer. This means that the data is stored exactly as a whiteboard, and the database uses pointers to navigate and traverse the graph. Neo4j has community and enterprise versions of the database. The Enterprise Edition includes all the features Community Edition has to offer, plus additional enterprise needs such as backup, clustering, and failover capabilities.

Features: It supports unique constraints; Neo4j supports complete ACID (atomicity, consistency, isolation and durability) rules; Java API: Cypher API and native Java API; uses Apache Lucence index; Simple query language Neo4j CQL; includes UI for executing CQL commands: Neo4j Data Browser.

Advantages: Easily retrieve their adjacent nodes or relationship details without joins or indexes; Easy to learn Neo4j CQL query language commands; No complex joins required to retrieve data; Very easy to represent semi-structured data; Real-time applications for large enterprises High availability of programs; simplified tuning.

Disadvantages: Does not support sharding.

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