Counting Is All You Need for Instant Tuple Discovery: Enabling Real-Time HTAP in Standalone DBMSs

HTAP systems aim to unify operational and analytical workloads, yet real-time analytics remains constrained by the overhead of extract-transform-load (ETL) operations. Existing solutions often rely on dual-system architectures, incurring substantial resource costs and delays from data reformatting and relocation. We present TracerETL , a progressive ETL framework that enables real-time analytics in standalone DBMSs through instant tuple location discovery during transformation. At its core is Tracer , a counting-based tuple tracking mechanism that constructs a tuple trace vector using per-partition counters. This trace vector deterministically encodes each tuple's future relocation path with arrival order across transformation levels, enabling precise data access at any stage-without auxiliary indexes. We implement TracerETL in PostgreSQL and evaluate it against OLAP- and OLTP-optimized DBMSs. Experimental results show that PostgreSQL with TracerETL accelerates real-time HTAP queries by up to 127×, while efficiently handling progressive data conversion in a standalone DBMS.