Cached at:
08/14/26, 06:30 PM
# Rayforce — Columnar Analytics and Graph Traversal in One Pipeline
Source: [https://rayforcedb.com/](https://rayforcedb.com/)
Open source · Pure C · Zero dependencies
## Analytics and graphs\. *One fast engine\.*
Rayforce fuses columnar analytics, graph traversal, and recursive queries into one embeddable execution pipeline—built for teams that measure latency in microseconds, not meetings\.
```
; 100,000 deterministic market rows
(select {from: trades
where: (> qty 100)
by: symbol
trades: (count qty)
notional: (sum (* price qty))})
```
Loading 100,000 rows
1. Load100K rows
2. Optimizerewrite DAG
3. Filter60K match
4. Group4 symbols
symboltradesnotional
**NVDA**15,0001,181,242,500
**GOOG**15,0001,191,143,000
**AAPL**15,0001,176,404,200
**MSFT**15,0001,185,774,600
One execution model
## Stop moving data between engines\.
Relational operators and graph traversals belong in the same plan\. Rayforce sees the whole workload, rewrites it together, and keeps the hot path close to the metal\.
[Explore the execution pipeline↗](https://rayforcedb.com/docs/architecture/pipeline/)
01Compose
### Tables \+ graphs \+ rules
Lazy DAG
02Optimize
### Rewrite the whole plan
Multi\-pass
03Bytecode
04Execute
### Stream cache\-sized morsels
Parallel
**16K**lines of focused C
**0**external dependencies
**IPC**client/server transport built in
**MIT**licensed and embeddable
Rayfall language
## Ask complex questions\. Keep the syntax small\.
Use Rayfall interactively, embed the C API, or connect through a growing set of client interfaces\. Every surface reaches the same optimizer and execution core\.
One engine, three surfaces
```
; Aggregate high-value flow, then traverse counterparties
(set flow
(select {from: trades
where: (> Notional 1000000)
by: Counterparty
Volume: (sum Notional)}))
(.graph.var-expand network flow 1 3)
```
EXAMPLE RESULT5 rows · optimized
CounterpartyDepthVolume
LYNX\_02184\.20M
ALPHA\_17261\.08M
NODE\_08244\.71M
FORT\_04327\.19M
EDGE\_12312\.42M
Built as one system
## Small footprint\. Serious machinery\.
Everything you need to move from raw columns to connected answers—without assembling a second platform around it\.
[01### Columnar analytics Vectorized filters, joins, groups, windows, pivots, and time\-series primitives\. *↗*](https://rayforcedb.com/docs/queries/select/)[02### Native graph engine CSR traversal, shortest paths, centrality, communities, WCO joins, and HNSW\. *↗*](https://rayforcedb.com/docs/graph/algorithms/)[03### Recursive Datalog Express reachability and recursive relationships as rules compiled into the same DAG\. *↗*](https://rayforcedb.com/docs/guides/datalog/)[04### Storage that stays open CSV, splayed and partitioned tables, memory maps, IPC, and block offloading\. *↗*](https://rayforcedb.com/docs/guides/storage/)
Rayforce in the wild
## Built for real work, not synthetic demos\.
Rayforce is already part of production systems and open\-source projects spanning trading, market connectivity, investment analytics, and risk\.
Usage confirmed by the Rayforce project\. Consumer names link to their public sites\.
Rayforce Cloud**Coming soon**
## The engine you can embed\. *The platform you won’t have to operate\.*
We’re bringing Rayforce’s unified analytics and graph pipeline to a managed cloud experience—so teams can move from local prototype to production workload without rebuilding the data path\.
RAYFORCE / CLOUD**PREVIEW**
QUERY SERVICE**Preview**
ENGINE**Managed**
Open at the core
## Read every line\. Own every workload\.
One codebase\. One public header\. No external runtime\. Clone Rayforce, compile it, embed it, and keep control of your data path\.
**—**GitHub stars
**—**forks
**Linux · macOS**supported today