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Sekejap

Sekejap is an embedded, graph-first multimodel database engine for workloads that combine graph, time, space, vector, and text.

Built for cases like:

root-cause analysis
hybrid retrieval and graph-aware RAG
memory retrieval around time and place
researcher, article, music, and knowledge graph discovery

Hello World: Root Cause Analysis

Rust:

use sekejap::SekejapDB;
use std::path::Path;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let db = SekejapDB::new(Path::new("./data"), 1_000_000)?;

    let rows = db.query(
        "SELECT id
         FROM cases
         TRAVERSE FORWARD caused_by TO causes HOPS 5
         WHERE id = 'incident_00001'
           AND MATCHING('wet road OR drainage OR education')
         LIMIT 20",
    )?;

    println!("hits = {}", rows.data.len());
    Ok(())
}

Python:

import json
import sekejap

db = sekejap.SekejapDB("./data", capacity=1_000_000)

rows = json.loads(db.query("""
SELECT id
FROM cases
TRAVERSE FORWARD caused_by TO causes HOPS 5
WHERE id = 'incident_00001'
  AND MATCHING('wet road OR drainage OR education')
LIMIT 20
"""))

print(len(rows))

Hello World: Hybrid Retrieval

Rust:

let rows = db.query(
    "SELECT id
     FROM researchers
     TRAVERSE FORWARD collaborates_with TO researchers HOPS 2
     WHERE id = 'researcher_00000'
       AND VECTOR_NEAR(embedding, [0.12, 0.34, 0.56, 0.78], 100)
       AND ST_DWithin(geometry, POINT(144.9631 -37.8136), 40.0)
     LIMIT 20",
)?;

Python:

rows = json.loads(db.query("""
SELECT id
FROM researchers
TRAVERSE FORWARD collaborates_with TO researchers HOPS 2
WHERE id = 'researcher_00000'
  AND VECTOR_NEAR(embedding, [0.12, 0.34, 0.56, 0.78], 100)
  AND ST_DWithin(geometry, POINT(144.9631 -37.8136), 40.0)
LIMIT 20
"""))

Available As

Rust library
Rust CLI
Python library
Python bindings with both SQL and Atomic interfaces

Common-user recommendation:

use SQL first

Lower-level control:

use Atomic / fluent builder when you need it

Installation

Rust

Library:

cargo add sekejap

CLI:

cargo install sekejap-cli

Then run:

sekejap

Python

Library and CLI:

pip install sekejap

Then use either:

sekejap --help

or:

import sekejap

npm

Planned later for CLI distribution.

Quick Usage

Rust main API:

SekejapDB::new(path, capacity)
db.query(input)
db.count(input)
db.explain(input)
db.mutate(input)
db.flush()
db.nodes()
db.edges()
db.schema()

Python main API:

sekejap.SekejapDB(path, capacity=...)
db.query(input)
db.count(input)
db.explain(input)
db.mutate(input)
db.flush()
db.nodes()
db.edges()
db.schema()

Input styles:

SQL
SekejapQL / pipeline text
JSON pipeline and JSON mutation payloads

Recommended usage:

Rust app code: SQL first, Atomic when lower-level control is needed
Python app code: SQL first
CLI: SQL first

Current Status

Rust library is ready for production testing for the core surface:

CREATE COLLECTION
INSERT INTO
SELECT
TRAVERSE
RELATE
RELATE MANY
UPDATE
DELETE FROM
UNRELATE

Collection schemas now persist across reopen, so SQL create/write/query survives process restarts.

Current strongest benchmark areas:

anchored graph traversal
exact-time filtering
vector retrieval
point-centric spatial filtering

Current weakest area:

vague time and vague-time-heavy hybrid planning

Docs

License

MIT

sekejap 0.5.1