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With the emergence of byte-addressable persistent memory (PM), a cache line, instead of a page, is expected to be the unit of data transfer between volatile and nonvolatile devices, but the failure-atomicity of write operations is guaranteed in the granularity of 8 bytes rather than cache lines. This granularity mismatch problem has generated interest in redesigning block-based data structures such as B+-trees, and attempts have been made to use in-memory data structures for PM. However, various methods of modifying B+-trees for PM degrade the efficiency of B+-trees due to the additional metadata and high rebalancing overhead caused by logging methods. In this study, we develop Failure-Atomic ShifT (FAST) and Failure-Atomic In-place Rebalance (FAIR) algorithms. FAST and FAIR modify legacy B+-trees in a byte-addressable fashion but solves the granularity mismatch problem. Every 8-byte store instruction used in the FAST and FAIR algorithms transforms a B+-tree into another consistent state or a transient inconsistent state that read operations can tolerate. By making read operations transient inconsistency, we can eliminate expensive copy-on-write, logging, and even the necessity of read latches so that read transactions can be non-blocking. Our experimental results show that legacy B+-trees with FAST and FAIR schemes outperform the state-of-the-art persistent indexing structures by a large margin.