We are exploring how to manage and update large amounts of citizen data, which is estimated to be around 44 Zettabytes in size. To handle this massive volume of unstructured data, we have NoSQL solutions, big data computing platforms such as Hadoop and Spark, and advanced search engines like Neo4j, a graph database that can efficiently manage complex relationships between connected devices. We've been using citizen data for almost 20 years and found it challenging to meet analytic requirements with traditional databases, but graph databases helped us solve issues like ancestral trees online in real-time and system-wide searches of the entire database. Despite Neo4j's capabilities, there are still dependencies that prevent a full migration to the platform, such as character encoding problems and special characters. The report also highlights trends in database technology, with relational databases still dominant but graph databases gaining traction. To overcome data integration challenges, we need a complete solution that is declarative, built-in change capture mechanisms for popular RDBMS products, and a system that can recover from failure, scale for enterprise online transaction processing, and parallelize for high-throughput.