EMATIX(R) DATA TERMINAL — ROBCO INDUSTRIES UNIFIED OPERATING SYSTEM
COPYRIGHT 2026 EMATIX SYSTEMS — ALL RIGHTS RESERVED
USER: GUEST   SESSION: 2026-05-21 02:29:57Z   HOST: ematix.dev/terminal
● STATUS: ALPHA — SURFACES STABILIZING. PIN VERSIONS. ●

DECLARATIVE PYTHON DATA PIPELINES.

Rust + Apache Arrow under the hood. Move data between databases, files, and streams with one decorator. Cron schedules, DAG dependencies, watermarks, schema evolution, restart-safe state, at-least-once delivery — built in. No extra scheduler service to deploy.

> pip install ematix-flow
SELECT TERMINAL
// 01

User Guide

Install, connections, pipelines, modes, scheduling, streaming, stream processing, CLI. Each chapter is a copy-paste-runnable example.

▶ ENTER /guide
// 02

Specs & Benchmarks

Why ematix-flow exists, what's shipped, TPC-H numbers (1.75× DuckDB, 2.77× Polars, 13.4× PySpark geomean), and how it stacks up against the field.

▶ ENTER /specs
OPERATOR VIEW
// flow web — pipelines overview
ematix-flow Pipelines view — last-10 execution strip + LIVE STREAMING / next-run indicator per pipeline

Pipelines view ships with flow web — one card per pipeline, last 10 executions as a clickable strip, with a "Next: <UTC>" forecast for batch and an amber LIVE STREAMING pill for streaming. Click any square to drill into that run's task DAG.

▶ MORE SCREENSHOTS
QUICK PEEK
// example: app postgres → warehouse postgres, 5-min cron
from ematix_flow import ematix, ManagedTable, Annotated, BigInt, Text, TimestampTZ, pk

# Where rows are READ FROM (operational app database).
@ematix.connection
class app_db:
    kind = "postgres"
    url = "${APP_DB_URL}"

# Where rows are WRITTEN TO (analytics warehouse).
@ematix.connection
class warehouse:
    kind = "postgres"
    url = "${WAREHOUSE_URL}"

# Target table — typed Python; framework migrates on first run.
class Events(ManagedTable):
    __schema__ = "analytics"
    __tablename__ = "events"

    event_id: Annotated[BigInt, pk()]
    name: Text | None
    received_at: TimestampTZ

# Pipeline: SELECT runs against app_db; rows land in warehouse.analytics.events.
@ematix.pipeline(
    source_connection="app_db",
    target=Events,
    target_connection="warehouse",
    schedule="*/5 * * * *",
    mode="append",
)
def ingest_events(conn):                # conn is the source (app_db)
    return "SELECT event_id, name, received_at FROM public.events"
● Currently ALPHA — on PyPI as ematix-flow. Surfaces are stabilizing; minor APIs may still shift before beta.