Despite the fact that the channel in a holographic data-storage system is nonlinear, most of the existing approaches use linear equalization for data recovery. We present a novel and simple to implement nonlinear equalization approach based on a minimum mean-square-error criterion. We use a quadratic equalizer whose complexity is comparable to that of a linear equalizer. We also explore the effectiveness of a nonlinear equalization target as compared with the conventional linear target. Bit-error-rate (BER) performance is studied for channels having electronics noise, optical noise, and a different span of intersymbol interference. With a linear target, whereas the linear equalizer exhibits an error floor in the BER performance, the quadratic equalizer significantly improves the performance with no sign of error floor even up to {10}^{-7} . With a nonlinear target, whereas the quadratic equalizer provides an additional performance gain of 1–2\text{\hspace{0.17em} dB} , the error-floor problem of the linear equalizer has been considerably alleviated, thereby significantly improving the latter's performance. A theoretical performance analysis of the nonlinear receiver with non-Gaussian noise is also presented. A simplified approach is developed to compute the underlying probability density functions, optimum detector threshold, and BER using the theoretical analysis. Numerical results show that the theoretical predictions agree well with simulations.