Elasticsearch improved its ability to store dates with nanosecond resolution starting from version 7.0 by replacing the outdated Joda-Time library with the Java Time API, which supports higher precision. This transition required significant code refactoring to ensure backward compatibility and maintain performance, particularly in indexing throughput and aggregation latency. The solution involved creating a new field mapper, date_nanos, to store dates as long values in nanoseconds despite the reduced date range up to the year 2262. Challenges arose during the migration, such as performance degradation due to exceptions and increased garbage collection times, which were addressed through optimization techniques like avoiding exceptions in date parsing and leveraging microbenchmarks for performance validation. Additionally, backward compatibility with existing Joda-Time-based methods was maintained by introducing a dual-format compatibility test and deprecating old methods with clear migration paths. Future updates aim to enhance the functionality across the Elastic Stack, including Kibana and Beats, for seamless integration and querying of nanosecond-precision timestamps.