Caesar.jl is a Julia package for factor graph-based simultaneous localization and mapping (SLAM) and state estimation. It provides a framework for building factor graphs with variables (poses, landmarks) and factors (constraints), solving via incremental inference (iSAM2) and Bayes tree, and retrieving beliefs for non-Gaussian and multimodal distributions. The library supports integration with various sensors (AprilTags, lidar, sonar, GPS, IMU) through custom factors and middleware (ROS, LCM, ZMQ). Examples demonstrate applications in marine (ASV, AUV, ROV), wheeled (racecar, Victoria Park), tracking (acoustic, radar), and learning (neural network factors) domains. The architecture is modular, with core packages (RoME, IncrementalInference, DistributedFactorGraphs) handling specific aspects of the SLAM pipeline.