Databases
should explain
themselves.
One unified self-compressing engine behind PostgreSQL, MySQL, and MongoDB wire protocols. Bit-exact on Cloudflare R2.
Connect Standard Drivers With Zero Code Changes
Storage designed for
extreme efficiency.
Every layer of KOLMOS is engineered to minimize physical byte storage while maintaining 100% bit-exact decode fidelity and full ANSI SQL query capability.
Explanation Ladder
Autonomous MDL formula mining & prototype clustering reduces physical bytes.
Bit-Exact Decode
Invariant #1 guarantees decode(encode(x)) == x across all data types.
WASM Covenant
Sandboxed wasmtime decoders pinned in segment footers ensure perpetual recovery.
Fast Append WAL
Local write-buffer buffers incoming writes before ladder background compaction.
Three Wire Doors
Connect standard PostgreSQL, MySQL, and MongoDB drivers.
Radical Economics
Store data on Cloudflare R2 ($0.015/GB/mo) with zero data egress charges.
Why replace AWS RDS & MongoDB Atlas with KOLMOS?
Traditional databases trap your data on expensive SSD disks and force you to build complex ETL pipelines into separate data warehouses. KOLMOS unifies self-compressing storage directly on Cloudflare R2 at 10×–16× lower storage cost.
Compare Your Monthly Storage Bill
Drag the slider to select your uncompressed database volume:
Requires 500 GB provisioned high-IOPS NVMe disks + egress transfer charges.
Row-based uncompressed tables + IOPS baseline limits and snapshot surcharges.
Direct serverless object storage + $0.00 Egress fees + infinite auto-scale.
Stop Managing 2 Databases & 1 Fragile Pipeline
- ✕2 separate server bills for app transactional DB + analytical cluster
- ✕Data sync delays (dashboards and reports lagged by minutes or hours)
- ✕Heavy engineering overhead to fix broken schema changes in ETL
- Zero ETL: App CRUD and analytical queries execute on the exact same database
- Drop-in: Works out-of-the-box with Prisma, Drizzle, Mongoose, Django, and psql
- R2 Economics: Columnar data lives directly on Cloudflare R2 ($0.015/GB, zero egress)
Direct Capabilities Matrix
Comparing traditional cloud database tiers vs KOLMOS Cloud
| Capability | AWS RDS / Aurora | MongoDB Atlas | KOLMOS Cloud |
|---|---|---|---|
| Storage Cost per GB | $0.115 / GB | $0.250 / GB | $0.015 / GB (10x–16x Cheaper) |
| Data Egress Fees | Up to $0.09 / GB | Cloud dependent | $0.00 (Zero Egress on R2) |
| Storage Format | Row-oriented (B-Tree blocks) | BSON / WiredTiger tables | Columnar KSF1 + Formula Mining (4x–5x smaller) |
| Analytical Queries (`COUNT`, `GROUP BY`) | Slow row scans (reads all columns) | High memory pipelines | 10×–50× Faster (Vectorized SIMD Columnar) |
| Drop-in Compatibility | PostgreSQL / MySQL only | MongoDB MQL only | Multi-Wire (Postgres + Mongo + MySQL in one) |
| Disk Full Risk | Requires manual EBS scaling | Requires cluster tier upgrade | Never (Serverless infinite S3/R2 storage) |
From raw data
to living insight.
KOLMOS doesn't just store your data — it understands it. The Explanation Ladder computes the smallest mathematical program to regenerate exact rows, reducing storage footprint on Cloudflare R2.
- Mathematical formulas surfaced automatically on write
- 1.66× to 2.12× storage reduction over Apache Parquet-zstd
- WASM decoder covenant guarantees perpetual data decodability
- Bit-perfect fidelity verified on every single read
MDL Rule: KOLMOS selected Rung 1 formula replacement because total program + residual bytes were lower than Rung 0 zstd dictionaries.
Every byte written is
recoverable, bit-exact,
forever.
Storage footprint that
redefines efficiency.
Physical benchmark measurements comparing KOLMOS against uncompressed source formats and Parquet-zstd on Cloudflare R2 storage.
Live Database Connector Measurements
MongoDB Connector (Live R2)
Document BSON1,000,000 live BSON documents synced to Cloudflare R2. KOLMOS executes vectorized ANSI SQL aggregations over content-addressed CAS chunks instead of unindexed document scans.
SELECT event_id, AVG(latency_ms) FROM mongo_events WHERE device = 'ios' GROUP BY event_id;TPC-H Lineitem
Standard 16-column analytical benchmark
NYC Taxi Trips
Real-world fare & tip log telemetry
Clickstream Events
Repetitive device & user action logs
Three stages.
End-to-end data lifecycle.
From ~1ms write-buffer client acks to autonomous formula optimization and zero-copy Apache DataFusion SQL execution.
WAL Buffer & Ingest
Ingest from PostgreSQL, MySQL, or MongoDB, or write row DML. Mutations land in the local WAL write-buffer before being partitioned into FastCDC deduplicated chunks on Cloudflare R2.
Explanation Optimization
Background worker pool asynchronously mines affine relations, sequences, and k-medoids prototypes. If Rung 1 or Rung 2 reduces the Minimum Description Length (MDL) cost, an atomic swap is committed.
DataFusion SQL Execution
Execute ANSI SQL queries with Apache DataFusion 54.1. Prunes irrelevant segments via header min/max statistics before streaming zero-copy Arrow memory buffers.
Immutable CAS chunks replicated across Cloudflare R2 global storage.