KOLMOS — Cloud Database Engine
for PostgreSQL, MySQL & MongoDB
KOLMOS is a cloud database engine built for PostgreSQL, MySQL, and MongoDB workloads. It combines self-compressing storage, columnar architecture, and multi-wire compatibility to reduce database storage and cloud infrastructure costs.
Connect Standard Drivers With Zero Code Changes
Reduce Cloud Database
Storage Costs.
Cloud databases can become expensive as storage, replication, I/O, and backups grow. KOLMOS uses a self-compressing storage engine and cloud object storage to reduce the physical footprint of PostgreSQL, MySQL, and MongoDB workloads.
1.66×–2.12× Less Physical Storage
Mathematical MDL formula mining packs data denser than standard Parquet-zstd.
$0.015/GB/mo Object Storage
Direct R2 integration completely eliminates predatory cloud egress and IOPS tax.
Zero Application Rewrites
Native wire protocol compatibility for PostgreSQL, MySQL, and MongoDB drivers.
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.
PostgreSQL, MySQL & MongoDB Compatibility — Three Wire Doors
KOLMOS supports PostgreSQL, MySQL, and MongoDB wire protocols, allowing existing applications and database clients to connect without replacing their familiar tooling.
Self-Compressing Storage — Explanation Ladder
KOLMOS mines minimum description length (MDL) formulas and prototype clusters to reduce physical storage by 1.66×–2.12× compared to Parquet-zstd.
Database Cost Optimization — Radical Economics
KOLMOS is designed to reduce cloud database storage costs through self-compressing storage, columnar data layouts, and efficient object-storage architecture.
100% Lossless Guarantee — Bit-Exact Decode
Invariant #1 cryptographically guarantees decode(encode(x)) == x across all SQL and BSON data types with zero data distortion.
Obsolescence-Proof Recovery — WASM Covenant
Sandboxed wasmtime decoders pinned in segment footers guarantee perpetual data decodability without proprietary database locks.
High-Throughput Ingestion — Fast Append WAL
Memory-mapped write-ahead logging buffers high-concurrency inserts and updates at wire speed before background columnar compaction.
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.
Why replace AWS RDS & MongoDB Atlas with KOLMOS?
Traditional databases lock your data into expensive NVMe disks with exorbitant bandwidth egress taxes. KOLMOS stores directly on Cloudflare R2 with CAS columnar compression at up to 88% lower monthly bills.
Compare Your Monthly Storage & Database Bill
Drag the slider or choose a preset to see actual monthly costs based on our official pricing:
Includes ~250 GB provisioned high-IOPS NVMe disks, RAM overhead, and cloud egress bandwidth taxes.
Includes AWS compute instance, 250 GB gp3 EBS block storage, automated snapshots, and $0.09/GB egress.
Speaks MongoDB, PostgreSQL & MySQL wire natively. Stored on Cloudflare R2 with $0 egress fees.
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 + CAS Compression (3.5x–4x 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) |
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.
Latest Engineering
Research & Guides.
How to Reduce Amazon Aurora Costs in 2026: Taming the I/O and Storage Beast
Amazon Aurora bills escalate rapidly due to hidden I/O charges and row-based storage multiplication. Discover how moving to a drop-in multi-wire columnar engine like KOLMOS slashes storage by 10× and eliminates query I/O via segment-skipping—with zero application rewrites.
How to Reduce Cloud Database Storage Costs in 2026
Cloud database storage costs compound fast on RDS, Aurora, and MongoDB Atlas. Learn 5 proven ways to cut your storage bill in 2026 — with real pricing and an explanation-first compression approach.
How to Slash Cloud Database Storage Bills by 90%: The Complete Engineering Guide
Storage quietly accounts for 70%+ of cloud database invoices above 20TB. Here is how modern database engines use FastCDC chunking, Minimum Description Length (MDL) theory, and Cloudflare R2 to slash monthly costs from $25,000 to $750.
Everything you need
to know about KOLMOS.
Learn how KOLMOS delivers drop-in PostgreSQL, MySQL, and MongoDB wire compatibility with self-compressing columnar storage on Cloudflare R2.