New Databases Needed for IoT to Grow

The Internet of Things (IoT) holds great potential to benefit businesses and enterprises. Done right, it will allow your business to do a lot of things that have not been previously possible. But will your current database technologies be able to handle the Internet of Things?

The IoT has many business applications. It allows businesses to track their fleets and see if they are using their vehicles optimally. Not just vehicles, but all assets could be tracked. The IoT could tell a company when maintenance is required. It could help save businesses money by enabling them to see and assess critical situations remotely, as the sensors will be able to give them all information necessary without them being at the site.

The Internet of Things also means that machines are talking to other machines, freeing up your time to focus on other things. Anywhere from smart metering to network traffic monitoring to automotive and healthcare to facility management and manufacturing, and to inventory tracking, machines are sharing data with one another. This helps take tasks out of your hands by automating the things you have to do.

But together with the benefits, there are potential problems with the Internet of Things. One of the biggest is how enterprises should manage and store all that data coming in from various sensors and networks in a way that does not bleed your company coffers dry and in a way that is very efficient for use with your current applications.

If you are currently using an SQL database, for instance, then you are in trouble. What you will want in an IoT database is consistency, availability, and partition tolerance. Consistency is having everyone see the latest version after you have updated your database. Availability is when you can provide access to the database continuously. Partition tolerance means that the database would still be accessible even if one part of it is not. But it is said that when running a database that shares data, like SQL, you cannot really provide all three of these simultaneously.

SQL databases give you consistency first and then availability. They also ensure that the data that you are accessing is reliable. But in the process, it takes a lot of processing resources from all the logging, locking, latching, index management, and buffer management. And because of its focus on data integrity, SQL databases are difficult to scale, which makes them a very poor choice for the Internet of Things and big data.

NoSQL databases address these challenges. They are non-relational in that you are not forced to define your data to fit into the schemes of your relational database. This gives you a simple data structure that is also very flexible. NoSQL databases are not that burdened with many limitations when it comes to data structure and can support more data types. This makes it a good choice to handle the unstructured data that comes with the Internet of Things.

NoSQL databases put more value on availability and performance than consistency; the opposite is true for relational databases. The nature of data collected over the Internet of Things and big data is unstructured, making it a good match for NoSQL databases.

Another advantage that NoSQL databases have over relational databases is that you can merge data from different servers to work together. Relational databases are good if you have your data on one large server, but present a challenge when merging multiple servers. This ability of NoSQL databases to merge makes them easily scalable horizontally, meaning you do not have to worry about hardware capacity over time. It can also share your data automatically over several servers so that your data is evenly distributed among different servers.

NoSQL databases are also faster because it does not require computations on reads, and they allow for distributed processing using map reduce.

Then there are the newer cloud databases available out there. Some examples include Microsoft Azure, Amazon Web Services, and Rackspace. Because these databases live in the cloud, you could easily scale when you need to. You can get database-as-a-service in itself or you could get virtual machines to run your databases on. Not only are cloud databases scalable, you could also expect availability and reliability. What’s more, you only pay for the resources that you used and get the best technical people working on your database — without you hiring them.

In short, cloud databases blur the line between the benefits you are getting from relational and from NoSQL databases. For example, if you are comfortable working with SQL databases, Amazon RDS can be the one for you, because you get to work with an SQL database such as Oracle, MySQL, and Microsoft SQL Server but still get high scalability without worrying about database administration.

But if you are venturing out into NoSQL databases, you can easily do so even if you do not have a NoSQL database professional on your IT team by going with Amazon’s SimpleDB or DynamoDB. And with a cloud service, you won’t have to worry about another big cloud issue: storage.

In the end, however, the best databases for your own organization would depend on what types of data you are working with, which with the Internet of Things is varied with a lot of formats that you can work with. The best database for you would also depend on the use cases you have. Most businesses do not operate on an IoT island alone; they do have other considerations and requirements for their businesses. Relational databases and NoSQL databases both have their own strengths and weaknesses, while some businesses might not be comfortable porting their data to the cloud, so you’ll have to decide for yourself which approach will work best.

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