The number of functionalities controlled by software on every critical real-time product is on the rise in domains like automotive, avionics and space. To implement these advanced functionalities, software applications increasingly adopt artificial intelligence algorithms that manage massive amounts of data transmitted from various sensors. This translates into unprecedented memory performance requirements in critical systems that the commonly used DRAM memories struggle to provide. High-Bandwidth Memory (HBM) can satisfy these requirements offering high bandwidth, low power and high-integration capacity features. However, it remains unclear whether the predictability and isolation properties of HBM are compatible with the requirements of critical embedded systems. In this work, we perform to our knowledge the first timing analysis of HBM. We show the unique structural and timing characteristics of HBM with respect to DRAM memories and how they can be exploited for better time predictability, with emphasis on increased isolation among tasks and reduced worst-case memory latency. This work has been partially supported by the Spanish Ministry of Science and Innovation under grant PID2019-107255GB-C21/AEI/10.13039/501100011033; the European Union’s Horizon 2020 Framework Programme under grant agreement No. 878752 (MASTECS) and agreement No. 779877 (Mont-Blanc 2020); the European Research Council (ERC) grant agreement No. 772773 (SuPerCom); and the Natural Sciences and Engineering Research Council of Canada (NSERC) Peer Reviewed