MongoDB, the most popular NoSQL database, is an Open-Source, Document-Oriented Database. The term ‘NoSQL‘ stands for ‘Non-relational.’ It means that MongoDB Open Source Database is not based on the table-like relational database structure. But instead provides an entirely different mechanism for data storage and retrieval. BSON is the name of this storage format (similar to JSON format).
Open Source Software is a software development community that accepts the Developer’s modified, Enhanced, or Bug-fixed code. The source code of open-source software or projects is available to the public. Its design can be modified and shared by any developer.
In this guide, you’ll know more about MongoDB Open Source Database and its versions that are available in the market.
Table of Contents
Introduction to MongoDB
MongoDB is a popular open-source NoSQL database written in C++. MongoDB is a Dynamic Schema Document-Oriented Database that stores data in JSON-like documents. It means that when storing your records, you don’t have to worry about the Data Structure, the number of fields or the types of fields used to store values. MongoDB documents are similar to JSON objects.
You can change the structure of records by simply adding new fields or deleting existing ones (referred to as Documents by MongoDB). This MongoDB feature makes it easier to represent Hierarchical Relationships, Store Arrays, and other more complex Data Structures. MongoDB is now used to store massive amounts of data by many tech behemoths, including Facebook, eBay, Adobe, and Google.
Key Features of MongoDB
When compared to other traditional databases, MongoDB has several distinguishing characteristics that make it a superior solution. Some of these characteristics are discussed further below:
- Database with Fewer Schemas: A Schema-Less Database enables the storage of various types of Documents in a single Collection (the equivalent of a table). In other words, multiple Documents can be stored in a single collection in the MongoDB database, each with its own set of Fields, Content, and Size. MongoDB provides users with a great deal of flexibility as a result of this feature.
- Indexed Document: Every field in a MongoDB Database Document is indexed with Primary and Secondary Indices, making it easier to retrieve data from the pool.
- Scalability: Horizontal scalability is enabled by sharding in MongoDB. The process of distributing data across multiple servers is known as sharding. Using the Shard Key, a large amount of data is partitioned into data chunks, and these data chunks are evenly distributed across Shards that span many Physical Servers.
- Replication: MongoDB ensures high data availability by replicating the data and distributing it across multiple servers so that if one fails, the data can still be retrieved from another.
Hevo Data is a No-code Data Pipeline that offers a fully managed solution to set up Data Integration for 100+ Data Sources (including 40+ Free sources) and will let you directly load data from sources like MongoDB to a Data Warehouse or the Destination of your choice. It will automate your data flow in minutes without writing any line of code. Its fault-tolerant architecture makes sure that your data is secure and consistent. Hevo provides you with a truly efficient and fully automated solution to manage data in real-time and always have analysis-ready data.
Get Started with Hevo for Free
Let’s look at some of the salient features of Hevo:
Sign up here for a 14-Day Free Trial!
- Fully Managed: It requires no management and maintenance as Hevo is a fully automated platform.
- Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer.
- Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis.
- Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
- Connectors: Hevo supports 100+ Integrations to SaaS platforms FTP/SFTP, Files, Databases, BI tools, and Native REST API & Webhooks Connectors. It supports various destinations including Google BigQuery, Amazon Redshift, Snowflake, Firebolt, Data Warehouses; Amazon S3 Data Lakes; Databricks; MySQL, SQL Server, TokuDB, MongoDB, PostgreSQL Databases to name a few.
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Live Monitoring: Advanced monitoring gives you a one-stop view to watch all the activities that occur within Data Pipelines.
- Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Is MongoDB Open Source?
The open-source community celebrates and embraces Open Exchange Principles, Rapid Software Development, Collaborative Developer Participation, Meritocracy, Transparency, and Community-Oriented Development for various projects and products.
The open-source community’s goal and vision are to benefit both programmers and non-programmers. The success of an open-source initiative is determined by the following factors:
- Increasing Project Awareness and Adoption.
- Keeping your discussion boards active with Information, Questions, and Challenges
- Putting on Real-world events for geographically dispersed communities
- Extending our understanding of, and appreciation for, Open-Source Software and Development Models, all with a common goal in mind.
MongoDB stores data in JSON-like documents in a flexible format. It means that fields can differ from one document to the next, and data structures can change over time. MongoDB’s architecture consists of collections and documents rather than tables and rows as in relational databases.
Each database is made up of collections, which are made up of documents. Because of the varying number of fields, each document can be unique. Each document’s size and content may differ from one another. MongoDB is a database that is highly scalable and performance-oriented.
MongoDB Underneath an Open-Source License
The licenses for all open source products are not the same. Different Software has various licenses and agreements. MongoDB wrote the code and owned the rights to it. There are two MongoDB versions.
For commercial use, you must pay for the license. The source code is owned by the company. MongoDB is a typical modern post-relational database. Through Ops Manager, they have added security features, and In-Memory Storage Engine, Administration, Authentication, and Monitoring Capabilities.
MongoDB Enterprise Advantages
Customers can get enterprise-grade capabilities, proactive support, the Customer Success Program, and a commercial license from MongoDB Enterprise.
- Management Service for MongoDB (MMS): MongoDB Management Service (On-Premises) offers disaster recovery and monitoring to ensure reliable operations.
- Superior security: Enterprise and government customers can integrate MongoDB into standard security systems thanks to Kerberos and LDAP authentication, auditing, and SNMP support.
- Training on-demand: MongoDB University training for developers and DBAs is available online, on-demand, and in a private, secure learning environment.
- Integration of Enterprise Software: MongoDB’s SNMP support makes it simple to integrate it with popular management and monitoring tools like Nagios.
- Certified operating system support: MongoDB Enterprise has been tested and certified for operational stability on Windows, Red Hat/CentOS, Ubuntu, and Amazon Linux.
You can download it for free and use it as you wish. You are not required to pay for the license. You are not permitted to make any changes to the source code.
MongoDB Community Edition Advantages
- High Efficiency: MongoDB is a High-Performance Data Persistence System. Support for embedded data models, in particular, reduces I/O activity on the database system. Indexes allow for faster queries and can contain keys from embedded documents and arrays.
- RQL (Rich Query Language): MongoDB has a robust query language that allows for reading and writing operations (CRUD), as well as Data Aggregation, Text Search, and Geospatial Queries.
- Exceptional Availability: MongoDB’s replication facility, known as a replica set, offers automatic failover and data redundancy.
A replica set is a collection of MongoDB servers that all maintain the same data set, thereby providing Redundancy and Increasing Data Availability.
- Horizontal Scalability: As part of its core functionality, MongoDB includes Horizontal Scalability. Data is distributed across a cluster of machines using sharding.
MongoDB Open Source Deployment and Setup
The deployment consists of two main steps: Installing MongoDB and creating a Database.
Windows: Run Windows Server 2008 R2, Windows Vista, or later to install MongoDB in a Windows environment (link resides outside IBM). Once you’ve decided on database architecture, you can download the most recent version of the platform from MongoDB’s download page (link resides outside IBM).
Mac: There are two approaches you can take when installing MongoDB on macOS. MongoDB, like Windows-based environments, can be installed directly from the developer website once you’ve decided on the type of build you’ll be using.
However, the easiest and most common way to install and run MongoDB on a Mac is to use the Terminal app and Homebrew (link resides outside IBM).
Making a Database
After installing MongoDB, you’ll need to create a directory to store your data. This can be accomplished locally or via public or private cloud storage solutions.
MongoDB Open Source Use Cases
Here are some use cases for MongoDB Open Source
MongoDB Open Source for Mobile Devices
MongoDB’s JSON document model allows you to store back-end application data wherever you need it, including on Apple iOS and Android devices and cloud-based storage solutions. With secondary and geospatial indexing, you can aggregate data across multiple environments, allowing developers to scale their mobile applications seamlessly.
MongoDB Open Source for Analytics in real-time
Gaining access to key metrics and business insights from large pools of data is critical as businesses scale their operations. MongoDB effortlessly converts JSON and JSON-like documents, such as BSON, into Java objects, making data reading and writing in MongoDB fast and incredibly efficient when analyzing real-time information across multiple development environments. This has benefited a variety of business sectors, including Government, Financial Services, and Retail.
MongoDB Open Source for CMSs (Content Management Systems)
CMSs are powerful tools that help to ensure positive user experiences when accessing E-Commerce Sites, Online Publications, Document Management Platforms, and other applications and services. You can easily add new features and attributes to your online applications and websites by using MongoDB, which has a Single Database and High Availability.
MongoDB Open Source for Data Warehouse, Enterprise
The Apache Hadoop framework is a set of open source modules, such as Hadoop Distributed File System and Hadoop MapReduce, that work with MongoDB to store, process, and analyze large amounts of data. MongoDB and Hadoop can be used by businesses to perform Risk Modeling, Predictive Analytics, and Real-time Data Processing.
MongoDB is a NoSQL database that is open source. MongoDB is available in two editions. One is MongoDB Open Source, which is free as part of the Open-Source Community, but for the other editions, you must pay a License fee. When compared to the free edition, this edition has some advanced features.
MongoDB Open Source is a leading NoSQL database that is widely used by professionals. Ideally, People recommend that developers use MongoDB Open Source.
To meet the growing storage and computing needs of data, you will need to invest some of your engineering bandwidth in integrating data from all sources, cleaning and transforming it, and finally loading it into a Cloud Data Warehouse for further Business Analytics. A Cloud-Based ETL tool, such as Hevo Data, can efficiently handle all of these challenges.
Visit our Website to Explore Hevo
Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources like MongoDB and a wide variety of Desired Destinations, with a few clicks. Hevo Data with its strong integration with 100+ sources (including 40+ free sources) allows you to not only export data from your desired data sources & load it to the destination of your choice, but also transform & enrich your data to make it analysis-ready so that you can focus on your key business needs and perform insightful analysis using BI tools.
Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.
Share with us your experience of MongoDB Open Sources in the comments below!