We present a polynomial-time algorithm for online differentially private synthetic data generation. For a data stream within the hypercube [0,1]^d and an infinite time horizon, we develop an online algorithm that generates a differentially private synthetic dataset at each time t. This algorithm achieves a near-optimal accuracy bound in the 1-Wasserstein distance.