List common configuration options that affect RocksDB performance?

• MemTable size: a larger MemTable absorbs more writes before flushing, trading memory usage for fewer, larger flush operations
• Compaction style: leveled versus universal versus FIFO, each shifting the balance between write, read, and space amplification
• Block cache size: a larger cache keeps more hot data in memory, directly improving read latency
• Bloom filter settings: affects how effectively RocksDB can skip SSTables that don't contain a requested key
• Compression settings: trades CPU time for reduced disk space and I/O
• Number of background threads: controls how much parallelism is available for flush and compaction work

Tuning RocksDB well generally means understanding a specific workload's read/write mix and adjusting these options together, rather than treating any single setting in isolation.

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