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To guarantee deduplication-enabled transaction consistency and efficient garbage identification, we design aįlag-based asynchronous consistency scheme We decouple the deduplication metadata shard from read I/O path and replace it with a The placement of data and deduplication metadata is made cluster-wide based on the content fingerprint of chunks. , which promises high-performance deduplication metadata and duplicate fingerprint lookup I/Os without introducing a single point of failure. In particular, GĮliminates duplicate copies across the cluster for high storage space efficiency without jeopardizing performance. , a high-performance inline cluster-wide data deduplication, complying with the design constraints of shared-nothing storage systems. results in rendering inconsistencies in data chunks, deduplication metadata, and garbage data chunks. Further, transaction failures after deduplication integration often render inconsistencies in data chunks, deduplication metadata, and garbage data chunks. Mainly, this is due to ineffective and error-prone deduplication metadata, duplicate lookup I/O redirection, and placement of content fingerprints and data chunks. Likewise, inline deduplication integration poses serious threats to storage system read/write performance, consistency, and scalability. Traditional deduplication research ignores the design specifications of shared-nothing distributed storage systems such as no central metadata bottleneck, scalability, and storage rebalancing. Deduplication has been principally employed in distributed storage systems to improve storage space efficiency.