aravindkr1

This is covered in https://docs.microsoft.com/azure/cosmos-db/gremlin-support. You can specify a partition key for your graphs for scale out, and access vertices and edges using the partition key + item key ("id") like g.V(['USA', 'Seattle']).

The latency SLAs are within the same Azure region. You can distribute your data across any of the 30+ regions that Azure is available in. Your apps always read from the local/closest region with the homing APIs.

One key difference is the cost difference between running Cosmos DB and Cassandra. We have a TCO paper (https://aka.ms/documentdb-tco-paper) that shows that for a 1M operations/second workload, Cosmos DB is significantly 3x-10x cheaper than other systems.

Cosmos DB guarantees both low latency and that you can achieve your provisioned throughput with SLAs. Latency is guaranteed at p99 regardless of storage size or number of partitions.