Bridging Non-Traditional Backends: Apache Gluten, LLKV, and Dimension-DB

The hottest trend in SQL is bridging non-traditional backends. Apache Gluten is leading the pack as a middle layer that offloads JVM-based SQL engines’ execution to native engines ^[1]. By moving compute from the JVM to native runtimes, Gluten aims to squeeze latency and throughput without rewriting every query engine. It’s pitched as a bridge, not a replacement, for teams wanting JVM-friendly pipelines. Developers can keep their JVM ecosystems intact while gaining native speedups, all without a full rewrite ^[1].

LLKV — Arrow-Native SQL over Key-Value Storage — pushes analytical queries closer to where data lives ^[2]. The project sits on crates.io and signals ongoing work to ship SQL-style access atop KV stores, minimizing data movement ^[2].

Dimension-DB rocks an embeddable, pure‑Java time-series and columnar store built on Berkeley DB Java Edition. It auto-chooses storage formats (RAW, dictionary, run-length) and can act as a read-only SQL accelerator for external systems like PostgreSQL, Oracle, or ClickHouse ^[3]. In benchmarks on NYC Taxi data (78 million rows), it sustains ~55,000 rows/sec ingests and speeds up complex aggregations ^[3]. The package sits alongside related tools like Dimension-UI and Dimension-DI, underscoring a hardware-agnostic path to analytics without dedicated servers ^[3].

Together, these bridges unlock performance gains but raise questions about consistency, tooling, and deployment in mixed environments.

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