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One of the persistent questions which constantly challenge database administrators and developers are which technology to use? The analysis from various thoughts and inputs ultimately determines which ideal option to choose in order to suit your needs the best. The technology adopted should be able to manage the demand and volume to plan for a long-term sustainable strategy. It should also help reduce the support overhead and be good enough to get the enterprise decision-makers’ approval.

The complexity of decision-making is also compounded by how much buy-in is required and the constraints of existing technologies to merge with the new ones. For example, investing in an unknown technology means that understanding and learning it may cost you higher. Let’s explore this in terms of the choice of graph databases as enterprise DBMS.

In case if you are considering graph databases already, you may be wondering by the complex analysis it is able to handle and the simplicity with which it allows you to interact with the data. Again, you may be desperate to learning something new as well as want to experiment with the graph databases. But how can you be sure whether a graph database is the correct solution for your enterprise DBMS needs? What kind of investigations should you conduct in order to be certain of its value in your use case? What makes graph databases so special among other similar solutions to fit your project? 

Seeking answers for these queries, in this article, we will highlight some of the use cases which can guide you to or away from the usage of graph databases. There are no hard and fast rules to be followed, but rather explore some opportunities to evaluate whether the graph will fit your needs well before exploiting it further and adopting it.

Do a self-evaluation – whether you are desperate about the usage of a graph database?

Sometimes developers or administrators may strongly want to use something in order to learn a new technology, which they may choose based on the hype. The majority of us may know that we shouldn’t do this, but in real-world scenarios, we will probably not step back and think about the outcome of our actions until it’s too late to change the solution.

To crack this mindset, we have to put a problem analysis initially before evaluating different solutions. Try to answer the questions as to what is motivating you to use this technology? Will it provide anything extra which others cannot offer? Asking such questions will help you to understand why you should or shouldn’t use the new technology. For any database management support, including database planning, set up, remote administration, troubleshooting, backup, and restoration, you can rely on the top-notch support of

When should you avoid using graph databases?

As with all the enterprises, the graph database providers have a bias towards its products and usefulness. If you find the graph database features pass all the listed scenarios here, it will help you solidify your decision to use a graph database. If you use case only fits any of these scenarios, hopefully, it may offer many reasons against ending up with a wrong tool for a wrong job. Many use cases may not work well for the graph database, but this list is a few important ones you must consider.

Data is disconnected, and the relationships don’t really matter

Suppose you are dealing with typical transactional data and are less cared about how it relates to another transactional piece of data. In that case, a graph database is not an ideal solution to consider. Some use cases where the technology may simply store data, and analysis of inter-connections is important. Looking for individual pieces of data or even a unique list of items may also point to another solution, then graph database solutions may offer the most value from data, which is highly interconnected, and the analysis can be done at best for possible connections. If it not the use case, then graph database is not the ideal choice.

To optimize the writing and storing of data, but there is no need to read or query on data

This is an important add-on thing to be discussed as part of the above point we found. If the use cases are only looking for writing and storing data and do not expect to query or analyze the results, graph DBs may not work well. The requirement is for the write-only, which is transactional and simple queries with no SQL join statements are great indicators that your use case is not suited for graph databases.

You should consider that graph databases are mostly for transactional stores, which can quickly review the results in milliseconds. If your use case isn’t expected for utilizing this advantage, then you should probably want to find any other solution. 

Changing business leads and data capturing needs

If you have an inconsistent and ever-changing data type, which you need to collect and store, then graphic DB may not be an appropriate solution. Graphs are ideal for any or all of the data elements which can easily adapt to the changing business and data capturing needs. For example, in a case where you have to track the number of people calling you, one needs to just store only minima information as the name ID and the caller’s phone number in the table for this. As you do not have to retain any additional information or assign any relations to it, graph DB is not needed.

Suppose the requirement is expected to grow over time and the system is used as a major customer system where other types of data and analysis may be needed over time. In that case, graph databases can be considered. If the requirement is narrow in terms of the specific need of the application and the database is not expected to expand over time, then the usage of a graph database is not recommended.

By admin

Welcome to the intersection of technology and knowledge! I'm Rahul Shakya, a passionate tech enthusiast and the mind behind the bytes at With a knack for unraveling the intricacies of the digital realm, I embark on a journey to demystify the ever-evolving world of tech. Email: [email protected]