Nowadays, NoSQL databases are becoming more and more popular, and I have summarized some great, free and open source NoSQL databases here. Among these databases, MongoDB dominates the list and has considerable usage. These free and open source NoSQL databases are highly scalable and flexible, making them ideal for big data storage and processing. Compared with traditional relational databases, these NoSQL databases have great advantages in performance.
However, these NoSQL databases may not be the best for you. Most common applications can still be developed using traditional relational databases. NoSQL databases are still not well suited for those mission-critical transaction requirements. I have given a brief introduction to these databases, let’s take a look below.
1. MongoDB
MongoDB is a document-oriented database that uses JSON style data format. It is very suitable for data storage, content management and caching applications of websites, and can be configured to achieve replication and high availability functions.
MongoDB has strong scalability and excellent performance. It is written in C and is based on document storage. In addition, MongoDB also supports full-text search, high availability across WAN and LAN, easy-to-implement replication, horizontal expansion, rich document-based queries, and strong flexibility in data processing and aggregation.
2. Cassandra
This is a project of the Apache Software Foundation. Cassandra is a distributed database that supports decentralized data storage and can achieve fault tolerance and no single point of failure. wait. In other words, "Cassandra is well suited for applications that cannot tolerate data loss."
3. CouchDB
Also a project of the Apache Software Foundation, CouchDB is another document-oriented database that stores data in JSON format. It is ACID compatible. Like MongoDB, CouchDB can also be used to store website data and content, as well as provide caching, etc. You can run MapReduce queries on CouchDB via JavaScript. In addition, CouchDB also provides a very convenient web-based management console. It is very suitable for web applications.
4. Hypertable
Hypertable imitates Google's BigTable database system. The creators of Hypertable set "becoming the open source standard for highly available, petabyte-scale databases" as the goal of Hypertable. In other words, Hypertable is designed to reliably store large amounts of data across multiple cheap servers.
5. Redis
This is an open source, advanced key-value storage. Redis is also called a data structure server because of the use of hash, set, string, sorted set, and list in keys. This system helps you perform atomic operations, such as adding values to hashes, intersection operations on sets, string concatenation, differences and unions, etc. Redis enables high performance with in-memory datasets. In addition, the database is compatible with most programming languages.
6. Riak
Riak is one of the most powerful distributed databases. It provides easy and predictable scalability, providing users with fast testing, Prototyping and application deployment capabilities, thereby simplifying the application development process.
7. Neo4j
Neo4j is a NoSQL graph database with very high performance. It has all the features of a robust and mature system, provides programmers with a flexible and object-oriented network structure, and allows developers to fully enjoy all the benefits of a database with complete transaction features. Compared to RDBMS, Neo4j also provides many performance improvements for certain applications.
8. Hadoop HBase
HBase is a scalable, distributed big data storage. It can be used in real-time and random access scenarios to data. HBase has modular and linear scalability, and can guarantee strict consistency of reading and writing. HBase provides a Java API for easy client access; configurable and automated table partitioning; and features such as Bloom filters and block caching.
9. Couchbase
Although Couchbase is a derivative of CouchDB, it has become a fully functional database product. Its move toward document databases will put pressure on MongoDB. It is multi-threaded on every node, which is a major scalability advantage, especially when hosted on custom or bare-metal hardware. With some great 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, we should not confuse it with caching solutions; on the contrary, it is a persistent storage Engine for storing data and retrieving it in a very fast and reliable manner. It follows the memcache protocol. Its storage backend is used in Berkeley DB and supports features such as replication and transactions.
11. REVENDB
RAVENDB is a second generation open source database that is document storage oriented and schemaless, making it easy to store objects into it. It provides very flexible and fast queries, and makes scaling very easy by providing out-of-the-box support for replication, multi-tenancy, and sharding. It provides complete support for ACID transactions while ensuring data security. In addition to high performance, it provides easy scalability through bundles.
12. Voldemort
This is an automatically replicated distributed storage system. It provides automated data partitioning, transparent server failure handling, pluggable serialization, independent nodes, data versioning, and data distribution across various data centers.
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