The company’s real-time access to data is being used by major organizations such as Adobe, AppsFlyer, Barclays, Flipkart, and PayPal to enable AI and machine learning applications. However, Aerospike currently lacks vector capabilities, which it plans to develop and release this quarter. Vector capabilities are essential for enabling different generative AI use cases.
While Aerospike is working on vector capabilities, it emphasizes that vectors are not the only way organizations are using databases to enable AI. The platform supports predictive AI use cases without native vector support. Organizations currently use Aerospike for offline model training and storing the results. In the future, Aerospike aims to support a continuous learning process.
The combination of Aerospike’s multi-modal database capabilities, including graph database, and the upcoming vector support presents interesting possibilities. The synergy between vectors and graphs can bring more context and intelligence to AI applications. Some vectors can also be graphs, enabling a better understanding of the relationship between different entities.
Apart from enhancing AI support, Aerospike plans to add more core database capabilities to its platform. These improvements include enhanced multi-record transactions, point-in-time recovery, and improved observability and management functionality. As the database is being deployed into larger clusters and handling larger data sets, Aerospike aims to make cluster management easier.
With the funding secured, Aerospike is well-positioned to expand its real-time database capabilities for AI applications. As the demand for AI continues to grow, Aerospike’s platform will play a significant role in supporting organizations’ AI and machine learning efforts. The addition of vector capabilities and the integration of graph database functionalities will provide users with more powerful tools for data analysis and decision-making.