SQLite has six layers: SQL parser → query planner → VDBE → B-tree → pager → OS. (https://sqlite.org/arch.html) For key-value workloads you only need the bottom three.

SNKV cuts the top three layers and talks directly to SQLite's B-tree engine. No SQL strings. No query planner. No VM. Just put/get/delete on the same storage core that powers SQLite.

Python:

    pip install snkv

    from snkv import KVStore

    with KVStore("mydb.db") as db:
        db["hello"] = "world"
        print(db["hello"])   # b"world"

C/C++ (single-header, drop-in):

    #define SNKV_IMPLEMENTATION
    #include "snkv.h"

    KVStore *db;
    kvstore_open("mydb.db", &db, KVSTORE_JOURNAL_WAL);
    kvstore_put(db, "key", 3, "value", 5);

Benchmarks vs SQLite WITHOUT ROWID (1M records, identical settings):

  Sequential writes  +57%
  Random reads       +68%
  Sequential scan    +90%
  Random updates     +72%
  Random deletes    +104%
  Exists checks      +75%
  Mixed workload     +84%
  Bulk insert        +10%

Honest tradeoffs: - LMDB beats it on raw reads (memory-mapped) - RocksDB beats it on write-heavy workloads (LSM-tree) - sqlite3 CLI won't open the database (schema layer is bypassed by design)

What you get: ACID, WAL concurrency, column families, crash safety — with less overhead for read-heavy KV workloads.