NoSQL

NoSQL Databases List & Examples

With the proliferation of big data, there has been a corresponding increase in the number of NoSQL databases. For those who are new to the term, NoSQL databases are non-relational databases that are designed to handle large amounts of data. In this blog post, we will take a look at some of the most popular NoSQL databases.

NoSQL databases are a newer alternative to traditional relational databases that are designed to provide more flexibility and scalability. NoSQL databases are often used for big data applications that require real-time analysis or for applications that need to be able to handle a large amount of concurrent users. While NoSQL databases can offer some advantages over traditional relational databases, they also come with some trade-offs that you should be aware of before making a decision about which type of database is right for your application.

MongoDB

MongoDB is a powerful NoSQL database system that offers a flexible data model and scalability. It is a document-oriented database, which means that data is stored in JSON-like documents. MongoDB is a popular choice for web applications that need to store large amounts of data. MongoDB is easy to use and offers various important features:

  • MongoDB supports documents, which are similar to JSON objects. This makes MongoDB very flexible as it can store data of any type, without having to define a schema upfront.
  • MongoDB has an indexing feature, which makes data retrieval quick and efficient.
  • MongoDB offers a scalability feature, which allows it to handle large scale data.
  • It also offers a rich query language that makes data manipulation easy.
  • It is fully managed in cloud which allows one to leverage cloud services provided by MongoDB

One can access all the learning resources related to MongoDB on this page – MongoDB university.

Couchbase

Couchbase is a NoSQL document-oriented database system. It is available on the cloud and comes up with lot of value-added services. It is an open-source project and is notable for its cross-platform compatibility. Couchbase Server, the company’s flagship product, is built on an Apache CouchDB core. The key features of Couchbase Server are its scalability, high performance, and rich query language support. Couchbase also offers a number of other products, including Couchbase Mobile, Couchbase Sync Gateway, and Couchbase Eventing Service. While Couchbase is often compared to other NoSQL databases, such as MongoDB and Cassandra, it has a number of unique features that make it a powerful tool for many applications.

Couchbase is a popular choice for Internet of Things (IoT) applications, mobile apps, and real-time web applications. It is also very easy to use, with a simple SQL-like query language that makes it straightforward to work with data stored in the database.

Cassandra

Cassandra is a NoSQL database that is designed to provide high availability and scalability. Cassandra is a distributed database that replicates data across multiple nodes. This makes Cassandra highly available because if one node goes down, the data is still available on the other nodes. Cassandra is also scalable because it can easily add new nodes as needed. Cassandra is designed to handle large amounts of data. Cassandra is also highly configurable, allowing administrators to tune the system to their specific needs. Cassandra also has good performance, providing low latency and high throughput.

Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous master-less replication allowing low latency operations for all clients.

HBase

HBase is a non-relational, NoSQL database that runs on top of Hadoop. It is an open-source project that is part of the Apache Hadoop ecosystem. HBase is designed to provide quick access to large amounts of data. HBase features include: Automatic sharding of data across Hadoop nodes, Opportunistic locks to allow many readers and a single writer, Easy to use Java API for client access, Bulk imports of HFiles (Hadoop’s native file format), Coprocessors to enable user-defined filters, functions, and aggregation.

HBase can be used as the primary datastore for Hadoop applications or as a complement to Hadoop’s HDFS file system. HBase is not meant to replace HDFS; rather, it is meant to provide random real-time read/write access to very large datasets. When used in concert with HDFS and MapReduce, HBase provides a complete big data solution.

Redis

Redis is an open source, in-memory data structure store and NoSQL database that is often used as a key-value store. Redis features include built-in transactions, publish/subscribe messaging, and support for Redis Cluster. Redis features include support for data types such as strings, hashes, lists, and sets. Redis also has built-in support for atomic operations. Redis is written in C and has been designed to be fast and scalable. Redis is often used as a cache or a message broker. Redis can be used with programming languages such as Python, Ruby, and Java. Redis also supports disk persistence, which means that data will not be lost if the server is restarted. Redis can be used in a variety of applications, such as caching, session management, gaming Leaderboards, Geospatial indexes, and much more.

Neo4j

Neo4J is a powerful open-source graph database that is rapidly gaining popularity in the NoSQL world. Unlike traditional relational databases, Neo4J does not use tables and columns to store data. Instead, it uses a graph data model, which consists of nodes (vertices) and relationships (edges). This unique data model makes Neo4J well suited for applications that require highly connected data, such as social networks, fraud detection, and recommendations. Neo4J is also very scalable, meaning it can handle large amounts of data and high levels of traffic.

Neo4j is ACID-compliant and supports transactional commits and rollbacks of individual statements and transactions. Neo4j comes with a web-based user interface called Neo4j Browser that provides an interactive Neo4j console apart from visualizing Neo4j data structures such as nodes and relationships. In addition, Neo4j can be embedded in software that uses the Java Virtual Machine, making Neo4j accessible to software written in other programming languages. Some of the use cases of Neo4J are fraud detection, real-time recommendations, master data management (MDM), network analysis & visualization etc.

Google Cloud Datastore

Google Cloud Datastore is Google’s fully managed, cloud based NoSQL database service. It provides powerful yet easy-to-use features for storing and retrieving data. Google Cloud Datastore is built upon Google’s extensive experience in managing large datasets. As a result, it is highly scalable and can handle even the most demanding workloads. Google Cloud Datastore is also highly available, with automatic failover and consistent performance. Google Cloud Datastore is ideal for a wide range of applications, from small websites to large scale systems.

Google Cloud Datastore is built on Google’s BigTable data storage system and uses the same underlying technology as Google App Engine’s High Replication datastore. Google Cloud Datastore has a RPC-based API that is accessible from any programming language. There is also a Java API that can be used to access Google Cloud Datastore from within Google App Engine applications.

Amazon DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB automatically scales up or down to meet demand, so customers can use it without having to provision or change capacity in advance. Amazon DynamoDB provides comprehensive security and compliance features to help you meet your organizational needs. You can encrypt your data at rest using Amazon SSE or AWS KMS and control access to your tables using IAM policies. Amazon DynamoDB integrates with AWS CloudTrail to give you full visibility into all Amazon DynamoDB API calls made by or on behalf of your account in your AWS account. Amazon DynamoDB is a HIPAA Eligible Service, meaning that it can be used to store protected health information (PHI) under the Health Insurance Portability and Accountability Act (HIPAA). Amazon DynamoDB is also compliant with the Payment Card Industry Data Security Standard (PCI DSS). Amazon DynamoDB is available in multiple regions worldwide and supports cross-region replication. With cross-region replication, you can replicate your table data across multiple Amazon Regions to build global applications with low latency while maintaining local data availability. 

Amazon DynamoDB is a great choice for applications that require high performance at any scale. Amazon DynamoDB is available in all Amazon Web Services (AWS) Regions except AWS GovCloud (US). Amazon DynamoDB is also available on Amazon Elastic Compute Cloud (Amazon EC2) through Amazon’s Machine Images (AMI). 

Microsoft Azure Cosmos DB

Microsoft Azure Cosmos DB is Microsoft’s proprietary implementation of the NoSQL database. It offers high performance, horizontal scalability, and global distribution. Microsoft Azure Cosmos DB is a Microsoft Azure service that provides globally distributed, multi-model database services. It supports document, key-value, wide-column, and graph databases. It is Microsoft’s globally distributed, multi-model database. It offers elastically scalable storage and throughput, comprehensive SLAs, diagnostic logging, and built-in global distribution.

Conclusion

There are many different types of NoSQL databases available, each with its own strengths and weaknesses. In this blog post, we have looked at some of the most popular NoSQL databases. When choosing a NoSQL database for your application, it is important to consider your needs and choose the database that best meets those needs.

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

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