Rising sea levels pose a potential threat to the densely populated areas along the Indian coastline and the low-lying islands, and cause disastrous impacts to coastal and offshore structures. Large fluctuations in sea surface temperature (SST) in the North Indian Ocean (NIO) is one of the contributing factors in inducing significant changes in sea level along the Indian coastline. Therefore, it is important to quantify the trends in sea level rise (SLR) in association with SST in this region. In this study, the seasonal climatology and variability of sea level anomaly (SLA) and SST is examined in the NIO (65 ◦E–92.5◦E, 4.5 ◦N–25 ◦N). A comparative study is conducted based on two different datasets by using the reconstructed sea surface height anomalies (SSHA) for 58 years from 1952–2009 and Archiving, Validation and Interpretation of Satellite Oceanographic (AVISO) SLA dataset for 27 years from 1993–2019. The spatial correlation maps between SLA and SST reveal that AS exhibits strong positive correlation as compared to BoB throughout the year. In addition, the rate of increase in sea level is examined at twelve locations along the Indian coastline for pre-satellite era (1952–2009) and satellite altimeter era (1993–2019). In recent decades, a higher rate of increase as compared to long term trends (1952–2009) is observed, i.e., even exceeding the global mean SLR trend (3.2 mm yr−1). The highest rate of increase in annual sea level is observed at Mangalore (r = 0.4 cm) and the lowest is observed at Haldia (r = 0.03 cm) during the recent decades. However, during 1952-2009, the maximum rate of annual SLR is found at Okha (r = 0.21 cm) and the minimum at Vishakhapatnam (r = 0.11 cm). The analysis clearly elucidates that the sea level is continuously rising and accelerating and, four Indian coastal cities, namely, Vishakhapatnam, Mangalore, Mumbai and Chennai are the most susceptible of all.