Droplet microarray is a platform which was previously proven to be very versatile for chemical synthesis, cell culture or drug screening. In this work, we demonstrated the possibility to expand the scope of DMA setups into a smart, miniaturized, high throughput materials discovery platform. We transitioned from small libraries with known behavior to large chemical spaces including thousands of different, unknown polymeric compositions. The versatility of the platform allowed these adjustments to the experimental workflow to fit a broad scope of different functionalities, enabling the high-throughput synthesis and analysis of various different materials while maintaining a minimal material consumption. The synthesis and screening of the first 918 different compositions with six replicates (for a total of 5508 experiments) was performed in a short time window of one week while consuming only 551 µL of highly diluted monomer stock solutions. For comparison, the validation experiment of four compositions in triplicates consumed roughly 2.5 times the amount of material needed for the whole miniaturized screening, while taking already more time to just swell the larger gel pads than the whole screening pipeline. To perform the whole screening within this scale, the total material consumption would be 574 times higher (316 mL). This shows the advantages of miniaturization and parallelization compared to conventional analysis methods and establishes the DMA once again as a very versatile and applicable platform. The automatic experiment platform for hydrogels can be further combined with Bayesian optimization to further optimize target properties of interest or to explore and expand the space of achievable materials properties. We demonstrated that Bayesian optimization can find hydrogel compositions that increase intensity and lifetime substantially beyond what was found in the initial random screening process.