12 free and open source NoSQL database Introduction

Naresh Kumar, a software engineer and enthusiastic blogger, has great interest in programming and new things, and is happy to share technical research results with other developers and programmers. Recently, Naresh wrote about 12 well-known free, open source NoSQL databases, and analyzed the characteristics of these databases.


now that the NoSQL database is becoming more and more popular, I'm here to summarize some of the great, free and open source NoSQL databases. In these databases, MongoDB the top, with a considerable amount of usage. These free and open source NoSQL databases are well scalable and flexible, and are ideal for large data storage and processing. Compared with the traditional relational database, these NoSQL databases have great advantages in performance. However, these NoSQL databases are not necessarily the best for you. Most common applications can still be developed using traditional relational databases. NoSQL databases are still less suited to mission-critical transaction requirements. I've made some brief introductions to these databases, so let's take a look at them.


1. MongoDB


MongoDB is a document-oriented database that uses JSON-style data formats. It is ideal for Web site data storage, content management, and caching applications, and can be configured to implement replication and high-availability features.


MongoDB has strong scalability and excellent performance. It is written using C + + and is based on document storage. In addition, MongoDB supports Full-text search, high availability across WANs and LANs, easy replication, horizontal scaling, rich document based queries, and flexibility in data processing and aggregation.


2. Cassandra


This is the Apache Software Foundation project, Cassandra is a distributed database that supports decentralized data storage, fault tolerance, and no single point of failure. In other words, "Cassandra is ideal for applications that cannot tolerate data loss."


3. CouchDB


This is also a project of the Apache Software Foundation, COUCHDB is another document-oriented database that stores data in JSON format. It is compatible with acid, like MongoDB, COUCHDB can also be used to store data and content on a Web site, and to provide caching. You can run MapReduce queries on couchdb via JavaScript. In addition, COUCHDB provides a very convenient web-based management console. It is ideal for Web applications.


4. Hypertable


Hypertable mimics Google's BigTable database system. Hypertable's creators will "become a highly available, petabytes of database open source standards" as the goal of hypertable. In other words, Hypertable's design goal is to reliably store large amounts of data across a number of inexpensive servers.


5. Redis


This is an open source, advanced key value store. Because hash, set, string, sorted set and list are used in the key, Redis is also called a data structure server. This system can help you perform atomic operations, such as increasing the value in the hash, the intersection of the set, string concatenation, difference set and set, and so on. Redis achieves high performance through an in-memory dataset. In addition, the database is compatible with most programming languages.


6. Riak


Riak is one of the most powerful distributed databases, providing easy and predictable scalability, providing users with rapid testing, prototyping, and application deployment capabilities to simplify the development process of applications.


7. Neo4j


neo4j is a nosql graph database with very high performance. It has all the features of a robust and sophisticated system that provides programmers with a flexible and object-oriented network architecture that allows developers to fully enjoy all the benefits of a database with full transaction characteristics. Compared with rdbms,neo4j, some applications have been improved in performance.


8. Hadoop HBase


HBase is a scalable, distributed large data storage. It can be used in real-time and random access to data. HBase has modular and linear scalability, and can ensure strict consistency in reading and writing. HBase provides a Java API for easy client access, configurable and automated table partitioning, as well as Bloom filters and block caching features.


9. Couchbase


Although Couchbase is a couchdb derivation, it has become a full-featured database product. The tendency for it to move to the document database will make MongoDB feel pressured. It is multi-threaded on each node, which is a major scalability advantage, especially when hosted on custom or Bare-metal hardware. With some very good integration features, such as integration with Hadoop, Couchbase is a great choice for data storage.


10. Memcachedb


This is a distributed key-value storage system that we should not confuse with a caching solution; instead, it is a persistent storage engine for data storage and retrieving data in a very fast and reliable way. It follows the Memcache protocol. Its storage backend is used in Berkeley DB to support features such as replication and transactions.


11. Revendb


Ravendb is a second-generation Open-source database that is document-oriented and modeless, so that objects can be stored easily. It provides a very flexible and fast query, providing out-of-the-box support for replication, multiple rent, and fragmentation allows us to achieve scalability with ease. It provides complete support for acid transactions while ensuring data security. In addition to high performance, it provides easy scalability through bundle.


12. Voldemort


This is a distributed storage system that is automatically replicated. It provides automated data partitioning capabilities, transparent server failure handling, pluggable serialization capabilities, stand-alone nodes, data versioning, and data distribution across a variety of data centers.


　　Readers, you don't know which NoSQL databases you have used, are or will use in your project. Today's NoSQL World complex, NoSQL database is also a dime, and some databases provide similar characteristics, this article is only a representative of the 12 NoSQL products. Have you ever used them? Do you use a product not described in this article? What features have they touched you to make you decide to use them? You are very welcome to share your experiences and views with us.