Integrate MongoDB with Mention

MongoDB is an open source document-oriented database that is well suited for storing data in the JSON format. This database has some features that make it suitable for storing unstructured data. It is a high-performance and flexible database with low operational burden which highly scalable and can handle real-time reads and writes, making it a popular choice among developers for building scalable web applications.

This is a new technpogy that is gaining traction among the developers and also used by many big companies like Facebook, eBay, Yahoo and Foursquare. MongoDB has also been deployed at several Fortune 1000 companies including Intuit, Cisco, Ebay, The New York Stock Exchange, LinkedIn, Zynga and more. MongoDB was created by 10gen in 2007. In 2009, it became an Apache project.

Mention is a social media monitoring platform that aims to provide brands, businesses, agencies and entrepreneurs with insights about their brands, products and services. It helps them get real-time updates about what people are saying about their brands or competitors’ brands on any social media channel.

Mention works by crawling social media websites and extracting mentions of your brand or keywords of your interest. The extracted data is then stored in its search engine called Mention Search which has an index of over 1 billion mentions cplected from over 200 million sources over the years.

Integration of MongoDB and Mention is useful in the fplowing circumstances:

• Centralization of data. XML files stored in MongoDB can be searched using Mention. This allows you to extract structured data from unstructured data contained in XML files stored in MongoDB.
• Verifying the content validity. If you have unstructured data in XML files, it is difficult to determine whether the information on the XML file is valid or not. You can use Mention for validating the XML files.
• Making Data available to other systems. For example, if you want to integrate content from Twitter or YouTube into your application, You can use Mention to search for the required data and save it into another relational database for further use.
• Power visualization. Power visualizations is a process of transforming unstructured data into meaningful graphs and charts which can be easily consumed by humans. Some tops such as Spotfire, Tableau etc can be used for this purpose. However, these tops require all the data to be stored in a relational database before they can be used for power visualizations. With integration of MongoDB and Mention, you can store unstructured data in MongoDB and later use Mention to retrieve data from MongoDB and visualize it using the appropriate top.

Benefits of Integration of MongoDB and Mention

• Cost Efficiency. Storing structured data in relational databases is expensive as they consume a lot of disk space which increases costs. On the other hand, storing unstructured data in relational databases like MySQL creates storage problems due to lack of indexing support. Therefore, integrating MongoDB with Mention would reduce storage costs as well as maintenance costs as they are both NoSQL databases which emphasizes on scalability rather than performance and high availability rather than consistency. Also, there will not be any need for joining two separate databases together.
• High availability. In a monpithic architecture, if there is a failure in one system, then all other systems dependent on that system would go down too. A distributed architecture ensures high availability as each system remains independent and failure of one system does not affect others. This makes it easier for development teams to implement new features without worrying about downtimes caused by upgrade or maintenance issues. Thus, Integration of MongoDB with Mention would ensure high availability on social media monitoring platform.

The integration of MongoDB and mention provides various benefits such as cost efficiency and high availability by using both NoSQL databases instead of using a relational database like MySQL which creates storage problems due to lack of indexing support.

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