Open-source databases are becoming increasingly popular for businesses, organizations, and individuals who need powerful and reliable databases. TechTarget also highlights several open-source tools and technology that are on the rise, which all help enterprise data leaders implement a dull range of data-driven analytics initiatives. If you’re a newbie, navigating this field can be tricky – fortunately, our guide has everything you need to learn about open-source document databases to help you harness the power of big data.
Introduction to the Open-Source Database
An open-source database is essentially created to store important information on software, all of which an organization can control. One of its key features is that it is free, shareable, and uses a source code that is also available for modification and redistribution.
Here are the most common types of open-source databases:
- Key-value databases: These are for storing and searching for key and value data.
- Document databases: Stores document information in JSON format
- Wide-column store databases: Uses dynamic columns
- Graph databases: Uses nodes and edges
The popularity of the open-source document database rose alongside the increased use of social media and the Internet of Things (IoT), which called for better analysis of the massive data collected across the world. In the next section, we’ll delve deeper into open-source document databases.
How Open-Source Document Databases Work
Although document databases and key-value databases are similar in the sense that they store data in tables, documents don’t need to follow a standard schema. This is also called a non-relational format, such as JSON. In our article on ‘WebApp Development: 7 Best Practices’, we point out that JSON is the ideal format for transferring data from the server to the client. This makes document databases ideal for data that is considered highly structured.
Open-Source Document Database Use Cases
As mentioned, data that are highly structured are managed best in a document database. This includes detailed customer information, user profiles, product information, catalogs, and content management systems. Document databases also work well for the extraction of real-time big data, which Forbes predicts is one of the biggest tech trends in 2023. Real-time data requires more sophisticated analytics infrastructure, which is thankfully one of the strengths of the document database management system.
Document Database Management Systems
On the flip side, such vast amounts of data can overload a traditional database. This is also why you should use MongoDB, which is an open-source database management system. It is capable of ingesting large, unstructured documents in JSON, all while presenting and preserving their data. MongoDB can provide organizations with improved efficiency through its clustering mechanism, and by tailoring the system to meet their specific needs. Organizations can also enjoy reduced costs thanks to custom licenses provided.
Finding and Developing the Best Database for You
If you’re determined to find the best database for your company, you should first consider your specific needs. Is your main issue storing different types of data? Does your data generally fit into the same fields? Do you need to focus more on variety or consistency? We also highlight the importance of a provider’s price point in our article on ‘How Much Does Management Software Cost?’ Luckily, most databases such as MongoDB are ready to provide a free tier with generous features to help you decide whether or not to fully commit.
There’s a lot more to learn about open-source document databases, and it’s a technology that is continuously developed and adapted. In the future, expect to see it more ingrained in fields such as finance, retail, and even in the government.