Don't take our word for it. Measure it.
TPC-H SF1, 22 queries, hot run. Same hardware. No tricks.
Why teams switch to ScramDB
Every query compiles to native code. Every core stays busy. Every byte stays columnar. Zero compromise.
JIT Compilation
SQL queries compile to native machine code - not interpreted, not vectorized. Entire pipeline stages fuse into tight native loops with zero function call overhead.
Morsel-Driven Parallel
Worker threads pinned to CPU cores process data in parallel with linear scaling. NUMA-aware scheduling keeps data local for maximum throughput.
Tundra Columnar Engine
Purpose-built columnar storage engine with zone maps for automatic predicate pushdown, buffer pool caching, and crash recovery via write-ahead logging.
Vector Search
pgvector-compatible vector similarity search with DiskANN-style graph indexes. Query vectors alongside relational data using standard SQL.
GPU JIT
GPU-accelerated query execution for large batch operations. Supports NVIDIA, AMD, and Apple Metal - no CUDA toolkit required at runtime.
Streaming Results
Query results stream directly to the client without full materialization. Backpressure prevents memory overflow on large result sets.
Zero migration. Just connect.
Point your psql, pgAdmin, or any PostgreSQL driver at ScramDB. Same port, same protocol, same SQL. It just works.
Works with everything you already use
If it talks to Postgres, it talks to ScramDB. 90+ integrations out of the box.
ScramDBAdaptive HTAP Database