As more organisations have adopted IoT technology the amount of data that is generated has increased. IoT devices continuously produce and transmit data, thus generating Big Data that needs to be effectively analyzed. Selecting the right database is crucial to the success of an IoT platform and the device management platform that goes with it. In this article, the author discusses the most effective databases for IoT applications and the criteria by which such databases should be selected, namely, the scale and performance of the data and the compatibility of the databases’ solutions with IoT systems.
Main Characteristics Of Database For IoT Applications
When selecting a database for IoT use cases, it’s essential to evaluate its capabilities based on the following requirements:
High Write Throughput: IoT devices generate data in real-time hence the need for a database with high write throughput.
Scalability: The database must be somewhat designed to be horizontally scalable in order to support additional device networks as they emerge.
Low Latency: Real-time analytics applications entails little or no latency in the retrieval of data.
Support for Time-Series Data: Almost every IoT data contain time stamps, which makes support for time series databases required.
Integration with Analytics Tools: This means that integration with the machine learning and big data tools has to be close and easy.
The Best IoT Applications Database and IoT Data Analytics Database
1. InfluxDB
InfluxDB is a highly specialized database which is designed specifically for storing time-series data, which translates well to managing data received from IoT devices.
Features:
Designed specifically to cater for time series data.
In the querying methods, there are InfluxQL and Flux languages that support high performance in the operations.
It supports real time monitoring and can be used for analysis of data collected.
Compatible with Internet of Things platforms and other visualisation tools.
Due to the specific nature of the IoT data, in which time-stamped data is the most important, it turns out that InfluxDB is one of the best tools to analyze such information.
2. MongoDB
MongoDB is a generalized database that follows the NoSQL database and is elastic in its operation.
Features:
The lower structure is used to store unstructured IoT data into document-based storage.
Horizontal scaling which is divided by sharding.
Data support for Geographic Information System (GIS) & temporal data.
A big advantage is the compatibility with cloud-connected IoT platforms.
IoT use cases which require handling of data of heterogeneous structure and performing diverse analysis on it can leverage MongoDB effectively.
3. Cassandra
Apache Cassandra is a distributed data store that can handle availability and operational simplicity/complexity.
Features:
Made specifically for the operation of multiple IoT devices.
Superior write and read I/O operations per second.
Favourable position towards Distributed and Decentralised architectures.
Linear scalability that can only be applied to the increasing networks in the IoT structure.
Cassandra is basically one of the most suitable solutions for IoT applications that need steady throughput across the huge datasets.
4. TimescaleDB
Popular databases like PostgreSQL are the foundations of successfully implemented time-series data solutions like TimescaleDB.
Features:
Integrates the database function of social relationships with the optimization function of time-series.
Possibilities of the data partitioning at large scale.
Multi-table functionality supported by SQL.
Original compatibility with visualization tools such as Grafana.
High analytics IoT applications are best solved by TimescaleDB.
5. Firebase Realtime Database
Firebase provides a cloud based NoSQL database optimized for mobile and IoT and others.
Features:
Real time data update across multiple devices.
Low-latency performance.
Offline access and caching is supported.
Interoperability with other service platforms of Google Cloud.
Still, when it comes to Internet of Things segments such as smart homes and consumer electronics, Firebase can be most helpful.
6. Redis
Redis is a fast data structure server which is an in-memory database designed for internet of things IoT applications which require low latency.
Features:
The capability of passing large amounts of data with minimum latency, below one millisecond.
Integration with the data structure of hashes and list etc.
Real time messaging using Pub/Sub.
Options for persistent storage in relation to online IoT data that is critical for decision-making.
Redis is ideally suited for IoT applications where algorithms need to process data on the fly as in device management platform.
7. Azure Cosmos DB
Azure Cosmos DB is Microsoft’s distributed, schema-less database for cloud native applications available globally.
Features:
Direct fast-deep access, with complete deployment.
These system characteristics include support for multiple data models such as document, key-value, and graph.
The first is a native integration with Azure IoT Hub.
Performance and availability backed with service level agreements and guaranties.
Specifically, Cosmos DB is excellent for large IoT applications of an enterprise level that must work on an international level.
8. Amazon DynamoDB
AWS DynamoDB is a fully managed NoSQL database for applications that require high performance.
Features:
Fully managed and doesn’t include any servers with serverless structure.
The high scalability that can allow it to handle large amounts of data a>xIoT data.
Compatibility with AWS IoT Core.
Other additional specific security and access control characteristics are as follows:
In this case, DynamoDB is suitable to use when developing IoT platforms within an AWS environment.
9. CrateDB
CrateDB is a distributed SQL database designed for Internet of Things and machine data.
Features:
Manages both simplified and complex information with great efficiency.
Highest levels of IoT device consumption data.
From the developed structure, it is possible to identify the SQL support for the time-series data analysis.
Ideal model of growth for numerous industrial IoT uses.
Hence, CrateDB should be considered as one of the best solutions for Industrial IoT projects and for their data analytics.
10. SQLite
SQLite is a non-SQL relational database that mostly resides in the Internet of Things.
Features:
Low resource overhead required at the edge devices.
Easy to deploy with no need to download or install.
At all good for local data storage and also applicable for occasional data synchronization.
It is useful where the data needed is small or where the complete data storage is to be done in edge devices or IoT.
Conclusion
In fact, the database that you choose to use forms a very important part of your IoT platform and device management platform. For IoT analytics, there’s specialized time series databases such as InfluxDB and TimescaleDB, for massive IoT deployment, there would be scalable databases such as Cassandra and MongoDB.
IoT projects have different requirements including but not limited to scalability, real-time analysis, data structure of the project, and many others to consider when choosing the appropriate database for the project. The right decision can help you fully unlock your IoT application and its analytics capabilities.
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