Big data is growing even bigger day by day. Today’s enterprise leaders need to leverage it to manage huge volumes of data and derive actionable insights from this. So, how can the CIOs and business decision-makers can generate such insights from their data?
As per expert opinion, to do this effectively, the new-age businesses need to stop collecting the data points, and better connect them. In other terms, relationships between these data points matter the most than standalone data points.
To leverage the benefits of establishing such data relations, organizations need to find a database management technology that can store relationship-based information at the primary objective. Now, graph databases effectively render this objective. The legacy RDBMS or relational database management systems are insufficient in handling this relationship aspect well while working with multiple data points. The tabular data model of RDBMS follows some rigid schemas, which makes it challenging for the admins to add any connections.
Given this, we can assume that graphical databases are the future. Graph databases store the relationships between various data points and identify and establish new kinds of relationships by adapting the data models to changing business requirements.
Advantages of graph databases
We may see how your enterprise may leverage the graph databases for a competitive advantage and gain business insights from connected data. There are many such things as fraud detection, real-time recommendations, MDM or master data management, access and identity management, etc., enabled by graphs databases. This is not a comprehensive list but does highlight the major and most appealing uses of graph database technologies.
Even when these are active, there are many other use cases for graph database technologies, including life sciences, healthcare, logistics, finance, gaming, governance, non-profit organizations, and so on. In our times, the CTOs and CIOs are under immense pressure to offer actionable insights to business decision-makers from their big data stores.
As the datasets grow bigger and wider, this task becomes more complex and challenging. They look for a technology that can determine the connections between various data points and service the most compelling conclusion.
Graph databases are perfect technological solutions, which allow the data professionals at various levels to explore the potential of data relationships than simply exploring the data points. There are no such limitations to harness these relationships between the data points as the user wishes.
All these make graph databases a rising tide later in the world of big data. Enterprises are tapping into the power of these databases to gain competitive advantages in the market. For analyzing your database requirements and implementation of an appropriate DB, you can consult with RemoteDBA.
Neo4j as a top graph database
As graph databases are on the hype now, you need to be very careful while choosing an appropriate graph DB for your enterprise DBMS project. Neo4j is one of the top choices in graph databases, which you can try out. As one of the first inventors of the graphs DB properties, Neo4j is a dominant mover in the graph DB market. The primary goals are to popularize the graph technology by bringing it on to the mainstream by connecting the customers, community, and partners.
From its beginning onwards, we can see that Neo4j is one such DB, which has a very vibrant community around it that consistently contributes to the Neo4j ecosystem. Now with about 50000 monthly downloads, Neo4j is undoubtedly the leader in the graph database sector.
Major advantages of Neo4j
1. High scalability and uncompromised performance
Experts have testified that Neo4j can deliver read and write applications in a lightning-fast mode based on your high-performance needs alongside protecting your integrity. This is the only enterprise-grade graph DB that can combine the native graph storage with scalable architecture by optimizing it for ACID compliance and speed by ensuring predictability.
2. Native graph storage and processing
Owing to the native graph storing and processing approach, Neo4j offers high performance and index-free adjacency, helping shorten the read and write time. It may even get better as the complexity of data grows. You can get reliably quicker transactions with a parallelized throughput even when the data grows into huge volumes.
3. Very easy to learn and use
Neo4j features a very mature user interface and an intuitive interaction approach. Being a graphic database, the built-in learning tools themselves is enough for the new users to easily understand and use the DB effectively. Thanks to the vibrant community around Neo4j, which brings up a simple training ecosystem to meet the needs of various use cases? There are plenty of training materials also available for the same online and expert-authored books.
4. Easy to handle
You simply choose Cypher or Java API to write the extensions for Neo4j. You have to just pick from the APIs and the drivers for major languages and enjoy many productivity enhancements through the intuitive UI of Neo4j.
5. High reliability for mission-critical applications
Neo4j is a solid graph DB, which got hardened this way through many testing and production years. This adds to this DB’s reliability, and on using Neo4j, you can also engage with the top graph experts offering support for the same. It is the only of its kind of graph DB, which the top-line analysts recognize as certified by Forrester and Gartner, for featuring production applications warranting inclusion in reports.
6. Easy to load data
Now, it is much easier than ever to get your data loaded onto Neo4j as the database offers excellent loading speeds even when the data sizes are huge. As another benefit, there is only a very low memory footprint, and you also custom choose how much data needs to be important irrespective of the size of data.
Along with these advantages, most Neo4j customers also find the cost of ownership of Neo4j is much lesser as they optimize their database environment for increased efficiency. Using Neo4j as the enterprise graph database system, one can choose among different licensing options and bundle it in a customized manner as you need. You can also custom your data replication and clustering capabilities, which make sense in your deployment.
