Like many IT-related businesses, the graph database market should experience an enormous increase in CAGR in the following years. Experts predict that the market will be worth $7.3 billion by 2030, which is a massive increase compared to $1.9 billion in 2023. Based on that assessment, the market value is expected to rise by 18% annually.
The reason behind such a major increase in value has to do with early adoption. Companies understand the importance of fast data processing and comprehensive analytics, which is why they’re not afraid to invest in various solutions regardless of the price.
Another major factor is the rise of AI and IoT. The increased popularity of artificial intelligence and Internet of Things devices will boost the demand for chart database solutions. Furthermore, as many companies become reliant on machine learning insights, they will need to invest in graph databases to stay on top of the competition.
In this article, we’ll analyze the market and its growth around the world.
Understanding graph database market
As the name indicates, graph databases are a type of databases heavily reliant on graphs. Given that graph structure offers great performance, scalability, and flexibility, it is a perfect method for storing data. By using products like NebulaGraph graph database, businesses can store their data and quickly retrieve it at any time.
Market drivers
There are several good reasons why these solutions have exploded in the last few years:
- Increased reliance on database tech
Companies that are in the manufacturing business are major users of graph database products. These solutions are vital for their data management, allowing them to oversee complex operational processes and transactions.
Compared to other types of systems, graph database tech provides numerous benefits for all commercial entities. They excel at problem-solving, which commonly occurs when analyzing large and complex data. With this technology, businesses can process large quantities of information in a minimal amount of time.
- Processing queries with low-latency
Due to the fact that many companies are turning to graph databases, legacy database providers are given the hard task of assimilating schemas into their existing infrastructure. While this strategy might seem a good way to save money, it will actually reduce query performance that runs beside the database.
By relying on graph database products, companies can change how they manage traditional trading activity. The increased demand for products that can deal with low-latency queries is another major reason why this market has been booming in the last few years.
Market challenges
The biggest issue with graph databases comes in the form of standardization. We also can’t neglect complex programming requirements.
The thing about graph databases is that companies need to run them on a single server. The reason behind this is that you can’t distribute such a technology in a low-cost cluster. As a result, you can expect a rapid decline in network performance.
Another major issue with this type of database is that programmers are forced to create inquiries in Java. Basically, graph databases are NoSQL, which prevents data saving. As a result, IT companies need to hire veteran developers, all of which come with a high price tag. Subsequently, the market is being developed much slower than some companies would like.
Graph database strategy
Staying on top of the current trends is the best way to maximize graph database technology. By implementing these solutions to your operational workflow, companies can retain a competitive edge regardless of their specific market situation. Among others, through graph database products, businesses can become more efficient and cost-effective while also gaining a tech edge.
Besides improving their strategic decision-making, implementing graph databases can have a major impact on customer experience. Without relying on data, businesses can easily lose their spot on the market, miss on potential revenue streams, or fall behind in manufacturing.
The best way for a brand to optimize its graph database technology is by attending live events and tradeshows, learning about current trends and technology, and performing thorough research. Keeping in touch with influential IT experts can also teach you how to best implement these solutions for your workflows.
Graph database regional analysis
Generally speaking, the growth of the graph database market is expected across the board. Although the US is leading the charge, powerful Asian economies aren’t lagging behind.
In North America, the rise of the graph database market will be propelled by increased reliance on high tech. Whether we’re talking about digital companies or anyone else that profits from these solutions, we’ll see the biggest adoption among brands that are heavily dependent on data analytics for their strategic and daily tasks.
A similar thing can be said for Asia Pacific. As IoT devices become more popular in the region, the graph database market will catch up with the increased demand. The technology is crucial for business owners, providing them with valuable information that will allow them to stay ahead of competitors.
On the other hand, the reason why the graph database market is growing in Africa and the Middle East has to do with data visualization software. On top of that, there are numerous governmental projects that are reliant on these products. As for Europe, the market growth stems from increased smart technology adoption.
Best graph databases in 2023
Graph database business is relatively new and dynamic. New names hit the market every month, each presenting businesses with innovative solutions to their daily problems. In 2023, some of the best graph databases are as follows:
- NebulaGraph
- IBM Cloud Databases
- Redis
- Stardog
- TigerGraph
- Apache Cassandra
- Virtuoso
- Fauna
- Infinite Graph
Choosing the right product isn’t easy. There are so many things that a company needs to consider, including:
- Scalability and performance
- Highly available solutions that can survive several system failures
- ACID compliance (Atomicity, Consistency, Isolation, and Durability)
- HTAP, OLAP, and OLTP application support
- Advanced graph data science
- Graph query languages
- Native graph processing and storage
- Open source foundation
- Community and many other factors
Of course, every business will have its specific requirements. Only by finding the right combination of features can you be certain that a product is suitable for your business needs.
