Challenge:
Ibexa, a DXP (Digital Experience Platform) provider, required a database solution capable of managing real-time data at scale to support their customers’ need for up-to-date information and personalized recommendations. Cassandra, known for its scalability, seemed like a suitable choice. However, Ibexa faced challenges in deploying and managing Cassandra, which diverted their attention and resources away from their core value as DXP developers.
Solution:
To address these challenges, Ibexa explored Database-as-a-Service (DBaaS) providers to find a solution that could effectively handle Cassandra management and offer comprehensive support for all Cassandra features. This solution utilized the power of Cassandra while offloading the burden of operational management.
With Cassandra on AWS, Ibexa streamlined their cloud-native application development process. The managed service took care of the complexities associated with operating a robust database like Cassandra, allowing Ibexa to focus on their core competencies and eliminate the need for extensive internal maintenance.
Results:
By adopting Cassandra, Ibexa gained confidence in the stability and reliability of their real-time data management within the DXP environment. They no longer needed to worry about node failures or other operational issues that could disrupt their services. This stability contributed to increased customer satisfaction with the simplicity and ease of use of the DXP platform, particularly in terms of real-time data management.
The flexibility of Cassandra allowed Ibexa to easily set up and configure their database across various cloud environments, including different zones within Amazon AWS. This adaptability enabled Ibexa’s customers to effortlessly adjust their configurations based on their evolving business needs.
Over time, Ibexa established a strong relationship with their managed service provider, participating in developer events and engaging with other users of Cassandra. As Ibexa progresses towards delivering more personalized B2B and B2C recommendations using machine learning and advanced algorithms, they intend to leverage these connections to continue enhancing the real-time personalization and performance of their platform.