HVAC, HMI and integration platform for building automation based on Beckhoff PLC

Real-time mongoDB

MongoDB Overview

MongoDB is the leading NoSQL database, empowering businesses to be more agile and scalable. Fortune 500 companies and startups alike are using MongoDB to create new types of applications, improve customer experience, accelerate time to market and reduce costs.

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A New World

MongoDB was designed for how we build and run applications today.

New Apps

The applications serving, generating and interfacing with data have changed. Big Data, SaaS, social and mobile apps are the new norm.

New Data Types

New applications, users and inputs demand new types of data, like unstructured, semi-structured and polymorphic data.

New Data Volumes

Data volumes were once smaller, constrained and predictable. Today organizations must be prepared to support millions of users, thousands of queries per second and hundreds of terabytes of data.

New Development Methods

The methods we use to build applications have changed. With increasingly competitive markets and the need to adapt constantly, iterative development has become the standard.

New Architectures

The infrastructure on which we store data has changed. Companies are leveraging cloud computing, commodity hardware and virtualization.

What is MongoDB?

MongoDB is an open-source database used by companies of all sizes, across all industries and for a wide variety of applications. It is an agile database that allows schemas to change quickly as applications evolve, while still providing the functionality developers expect from traditional databases, such as secondary indexes, a full query language and strict consistency.

MongoDB is built for scalability, performance and high availability, scaling from single server deployments to large, complex multi-site architectures. By leveraging in-memory computing, MongoDB provides high performance for both reads and writes. MongoDB’s native replication and automated failover enable enterprise-grade reliability and operational flexibility.


The following is a brief summary of some of the main features:

Ad hoc queries

MongoDB supports search by field, range queries, regular expression searches. Queries can return specific fields of documents and also include user-defined JavaScript functions.


Any field in a MongoDB document can be indexed (indices in MongoDB are conceptually similar to those in RDBMSes). Secondary indices are also available.


MongoDB provides high availability and increased throughput with replica sets. A replica set consists of two or more copies of the data. Each replica may act in the role of primary or secondary replica at any time. The primary replica performs all writes and reads by default. Secondary replicas maintain a copy of the data on the primary using built-in replication. When a primary replica fails, the replica set automatically conducts an election process to determine which secondary should become the primary. Secondaries can also perform read operations, but the data is eventually consistent by default.

Load balancing

MongoDB scales horizontally using sharding.[9] The user chooses a shard key, which determines how the data in a collection will be distributed. The data is split into ranges (based on the shard key) and distributed across multiple shards. (A shard is a master with one or more slaves.)

MongoDB can run over multiple servers, balancing the load and/or duplicating data to keep the system up and running in case of hardware failure. Automatic configuration is easy to deploy, and new machines can be added to a running database.

File storage

MongoDB can be used as a file system, taking advantage of load balancing and data replication features over multiple machines for storing files.

This function, called GridFS, is included with MongoDB drivers and available with no difficulty for development languages (see "Language Support" for a list of supported languages). MongoDB exposes functions for file manipulation and content to developers. GridFS is used, for example, in plugins for NGINX[11] and lighttpd.

In a multi-machine MongoDB system, files can be distributed and copied multiple times between machines transparently, thus effectively creating a load-balanced and fault-tolerant system.


MapReduce can be used for batch processing of data and aggregation operations. The aggregation framework enables users to obtain the kind of results for which the SQL GROUP BY clause is used.

Server-side JavaScript execution

JavaScript can be used in queries, aggregation functions (such as MapReduce), and sent directly to the database to be executed.

Capped collections

MongoDB supports fixed-size collections called capped collections. This type of collection maintains insertion order and, once the specified size has been reached, behaves like a circular queue.

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