We collected a new low-light raw denoising (LRD) dataset for training and benchmarking. In contrast to the SID dataset, which sets a fixed exposure time to capture long and short exposure images, we captured long and short exposure images based on the exposure value (EV). Motivated by multi-exposure image fusion, the exposure value for long exposure images was set to 0, and the exposure value for short exposure was set to the commonly used parameters -1, -2, and -3. The dataset is designed for application to low-light raw image denoising and low-light raw image synthesis. The dataset contains both indoor and outdoor scenes. For each scene instance, we first captured a long-exposure image at ISO 100 to get a noise-free reference image. Then we captured multiple short-exposure images using different ISO levels and EVs, with a 1-2 second interval between subsequent images to wait for the sensor to cool down, thus avoiding unexpected noise introduced by sensor heating.