Jake from TileDB, Inc. here: Depending on the structure of the JSON files you are querying you maybe able to take advantage of columnar compression and massively reduce the dataset size (especially if the json files contain numeric data). Also, repeat queries will not have to re-parse the JSON files. This may speed up queries quite a lot, but it depends on the specifics of your problem.
Stanislav Seltser, Petacube
you are talking comparing structured workload(array-based TileDB) to unstructured one (JSON+Spark). Once you convert your JSON to sparce array structure (one time conversion) TileDB will beat Spark+JSON by several orders of magnitude. Caveat: assuming your spark+json workoad is a some heayy processing not a lightweight one.