I'm evaluating using Cassandra as a binary object store. In my experiments I'm not getting good enough read throughput for single queries to single nodes. Even on a MacBook Pro 15 2018 reading e.g. a 128 MiB blob in 64KiB chunks with the Cassandra C++ driver from a single node on the loopback interface takes about 300ms. I was hoping I could saturate a 10 GiB port on a fast enough server with single requests for large blobs. Are there any C++ driver, Cassandra or Java VM tuning options that could improve read throughput in this scenario?

The blob table has the following schema:

CREATE TABLE blobs.blob (
    id uuid,
    chunk_id int,
    blob_size int,
    creation_time timestamp,
    data blob,
    data_type text,
    hash blob,
    info text,
    update_time timestamp,
    PRIMARY KEY (id, chunk_id)
) WITH CLUSTERING ORDER BY (chunk_id ASC)
    AND bloom_filter_fp_chance = 0.01
    AND caching = {'keys': 'ALL', 'rows_per_partition': 'ALL'}
    AND comment = ''
    AND compaction = {'class': 'org.apache.cassandra.db.compaction.SizeTieredCompactionStrategy', 'max_threshold': '32', 'min_threshold': '4'}
    AND compression = {'enabled': 'false'}
    AND crc_check_chance = 0.0
    AND dclocal_read_repair_chance = 0.1
    AND default_time_to_live = 0
    AND gc_grace_seconds = 864000
    AND max_index_interval = 2048
    AND memtable_flush_period_in_ms = 0
    AND min_index_interval = 128
    AND read_repair_chance = 0.0
    AND speculative_retry = '99PERCENTILE';