What is MongoDB?
MongoDB is a document-oriented, no sequel(NOSQL) database.
It replaces the concept of roles of conventional relational data models with something called Documents. It offers developers the flexibility with evolving data models. Since it is document-based MongoDB allows embedded documents, arrays, represent complex hierarchical relationships using a single record. It is also schema-free which means that the keys defined are not fixed as a result massive data migrations can be ruled.
Why use MongoDB?
When there is something like SQL why there is NOSQL or MongoDB used??
There are a few reasons why MongoDB is widely used
1. Flexibility: MongoDB is the notion of documents that can contain subdocuments nested in complex hierarchies that are really expressive and flexible.
2. Flexible Query Model: The user can selectively index some part of a document or a query Based on attribute values, regular expressions, or ranges.
3. Native Aggregation: Native Aggregation allows its users to extract and transform data from MongoDB and either loads them in a new format or export it from MongoDB to other data sources. It makes it extremely compatible.
4. Schema-less model: Applications get the power and responsibility to interpret different properties in different ways.
Characteristics of MongoDB
1. General-Purpose database: MongoDB can serve heterogeneous loads and multiple purposes with an application.
2. Flexible schema design: Document-oriented approaches with nondefined attributes that can be modified on the fly is the key contrast with MongoDB and any other relational DB.
3. Scalability and LoadBalancing: It’s built to scale both vertically but most importantly horizontally. Using Sharding and architect can share the load between different instances and achieve both read and write scalability. Loadbalancing happens automatically and transparently to the user by the shard balancer.
4. Aggregation framework: MongoDB offers extract, transform, and load frameworks that eliminate the need for complex data pipelines.
5. Native replication: Data will get replicated across a replica set without a complicated setup.
6. Security features: Both authentication and authorization are taken into account in MongoDB.
7. JSON: JSON is widely used across the web for frontend and API communication and as such it is easier when the database is also compatible with the same protocol.
8. MapReduce: It is an excellent tool to build data pipelines and MongoDB uses MapReduce readily.
Working of MongoDB
Data is stored in the documents with the help of key-value pairs. The data is stored in the BSON format. At the backend, it converts JSON data into a binary format known as BSON. MongoDB also makes provisions for nested data. All of these documents are stored in a collection. This collection hold multiple documents and since MongoDB is schema-less documents in one collection will not be similar. These collections are stored in the entire MongoDB database. As mentioned earlier MongoDB makes provisions for nested data this makes fetching of data extremely efficient when compared to other databases.
Applications of MongoDB
Several areas of technologies use MongoDB as a DBMS. Some of them are:
1. Internet of Things
2. Mobile applications
3. Real-time analysis
5. Catalog management
6. Content management
Companies using MongoDB
- Google and many more
Toyota Material Handling and Industry 4.0 — Creating a Smart Factory By Moving from Monolith to Microservices, Microsoft Azure and MongoDB Atlas
Huge wheels of cheese trundle across a factory floor riding automated forklifts that know exactly where, when, and how to move their cargo. Humans and their traditional forklifts support the work for some of the more tricky jobs but the real magic at the heart of this operation is how billions of data points get generated, managed, stored, and analyzed.
Industry 4.0 has arrived and Toyota Material Handling Europe is building both the machines and the data platforms, that will make this historic shift in manufacturing success. Toyota is famous for the quality of its vehicles. Now that same standard is being applied to how its development teams create Internet of Things software that will enable the move to smart, autonomous, and safer factories of the future.
“At Toyota, we aim to be number one in industry 4.0,” explained Filip Dadgar, Principal System Architect and IT-Manager at Toyota Material Handling Europe.
In a recent presentation in Stockholm, Filip described how Toyota Material Handling Europe has already connected over 100000 warehouse trucks with integrated telematics. The trucks are put to use in virtually every business from manufacturing and warehousing to transport.
Filips covers a number of interesting topics in his talk, which you can see in full below. He gives the background on Industry 4.0, the developer manifesto his team sign, and the core principles that guide their work. He also discusses the shift from a monolithic codebase towards a microservices approach, which was undertaken so the development teams could be more productive and the platform more user-friendly. Underpinning this change is MongoDB Atlas, MongoDB’s fully-managed, global cloud database service, which Toyota Material Handling runs on Microsoft Azure.
Filip explained what it was he liked about MongoDB: “The most beautiful part is the data model. Everything is a natural JSON document. So for the developers, it is easy, really easy for them to work with quickly. Spending time on building business value, rather than data modeling.”
But it wasn’t just the data model. Toyota Material Handling had eight evaluation criteria that were used to decide on which database platform they would use to make the switch:
- Performance — latency, scalable reads and writes to meet customer SLAs and accommodate significant growth in the future
- Automatic scalability, operations, and maintenance that enable developers to focus on applications, rather than backend database administration
- Security and compliance to safeguard highly sensitive business and personal data
- Data locality — able to host in Northwest Europe or West Europe in Microsoft Azure, therefore, ensuring close geographic proximity to factories for latency-sensitive operations
- Automatic backups and restore to provide fully-managed data protection and disaster recovery
- Cloud agnostic, giving customers the freedom to run anywhere, on any platform
- Developer friendly database with a flexible data model so that developers can continuously integrate new application functionality and stay ahead of market demands
- Ecosystem for developer productivity, using proven best practices and widely available skills
Filip also covers two other important elements of the decision: access to MongoDB University for fast and easy web-based developer training and quality relationships with the MongoDB team.