1, mongodb; 2, cassandra; 3, redis; 4, hbase; 5, neo4j. among them mongodb is a very famous NoSQL database, which is an open source document-oriented database.

Several common non-relational databases:

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 is in c++.MongoDB can also be used as a file system. JavaScript can be used as a query language in MongoDB. By using sharding MongoDB scales horizontally. It is very useful in popular JavaScript frameworks.

People really enjoy 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: offers high performance; automatic sharding; runs on multiple servers; supports master-slave replication; data is stored as JSON-style documents; indexes any field in a document; it has an automatic load-balancing configuration because data is placed in shards; supports regular expression searches; and is easy to manage in the event of a failure.

Pros: 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: does not support joins; large amount of data; nested documents are limited; increases unnecessary memory usage.

2, Cassandra

Cassandra is 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 and you can easily accomplish this task. 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. As a result, Cassandra is ranked second among the best open source databases. some of the biggest companies like Facebook, Twitter, Cisco, Rackspace, eBay, Twitter, Netflix, etc. are using Cassandra.

Features: linearly scalable;; maintains fast response time ; supports attributes such as atomicity, consistency, isolation, and durability (ACID); uses Apache Hadoop to support MapReduce; maximum flexibility in distributing data; highly scalable; peer-to-peer architecture.

Benefits: highly scalable; no single point of failure; Multi-DC replication; tight integration with other JVM-based applications; better suited for multi-data center deployments, 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. Moreover, it is the most famous key-value store.Redis supports some c++, PHP, Ruby, Python, Perl, Scala and so on.Redis is written in C language. Moreover, it is licensed under BSD.

Features: automatic failover; keeps its database entirely in memory; transactions; Lua scripting; replicates data to any number of slave servers; keys have a limited lifespan; LRU evicts keys; publish/subscribe support.

Pros: supports many data types; very easy to install; very fast (executes about 110,000 groups per second, about 81,000 times per second); operations are atomic; multipurpose tool (used in many use cases).

Disadvantages: no support for joins; knowledge of Lua required for stored procedures; datasets must fit well in memory.

4, HBase

HBase is a distributed, column-oriented open source database, the technology from the Google paper "Bigtable: A Distributed Storage System for Structured Data" written by Fay Chang. Just as Bigtable leverages the distributed data storage provided by Google's File System, HBase provides Bigtable-like capabilities on top of Hadoop.

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

5. neo4j

Neo4j is known as a native graph database because it effectively implements the attribute graph model all the way down to the storage layer. This means that the data is stored exactly as it would be on a whiteboard, and the database uses pointers to navigate and traverse the graph.Neo4j has a Community Edition and an Enterprise Edition of the database. The Enterprise Edition includes all the features that the Community Edition must provide, as well as additional enterprise requirements such as backup, clustering, and failover capabilities.

Features: it supports unique constraints; Neo4j supports full ACID (Atomicity, Consistency, Isolation, and Durability) rules; Java APIs: Cypher API and Native Java API; use of Apache Lucence indexes; Simple Query Language Neo4j CQL; UI included for executing CQL commands. Neo4j Data Browser.

Benefits: easy to retrieve its neighboring nodes or relational details without joins or indexes; easy to learn Neo4j CQL query language commands; does not require complex joins to retrieve data; very easy to represent semi-structured data; high availability for large enterprise real-time applications; simplified tuning.

Disadvantages: no support for sharding