Data integration

Neykos exposes your operational data — production orders, OEE, downtime, quality — through a set of read-only ClickHouse views. This page describes everything you need to connect: credentials, endpoints, SSL, the available view and its columns, and end-to-end examples in the most common clients.

TL;DR

You receive a dedicated read-only user, password, and one or more view names. Point any ClickHouse-compatible client at:

Host: 89.167.19.228 (port 8123, no SSL) — or integrations.neykos.net (port 443, SSL enabled)
Database: oee
View: oee.v_<customer>_production_orders (provided to you)

Authenticate with the user and password Neykos shared with you, then SELECT from the view.

Auto-fill

You can pre-fill the examples on this page by adding URL parameters. For instance, ?client=cca replaces the view name with oee.v_cca_production_orders. ?user=, ?password= and ?view= are also accepted as overrides.

1. Overview

Neykos provides read-only access to selected operational datasets through ClickHouse.

Each customer receives:

A dedicated read-only user.
Access only to the views explicitly enabled for that customer.
No access to internal source tables.
No access to other customers' data.

The available view name, username, and password may vary by customer.

2. Connection information

Field	Value
Database type	ClickHouse
Host (direct IP)	`89.167.19.228`
Host (HTTPS)	`integrations.neykos.net`
Port (HTTP)	`8123`
Port (HTTPS)	`443`
Database	`oee`
User	`<provided_user>`
Password	`<provided_password>`
Available view	`<provided_view_name>` (example: `oee.v_customer_production_orders`)
Access mode	read-only

Credentials

The placeholders <provided_user>, <provided_password>, and <provided_view_name> are filled in by Neykos at onboarding. Never commit them to version control — keep them in a secrets manager or environment variables.

3. SSL configuration

Direct IP — no SSLHTTPS domain — SSL enabled

text

Host: 89.167.19.228
Port: 8123
SSL : disabled

text

Host: integrations.neykos.net
Port: 443
SSL : enabled

Use the HTTPS endpoint whenever your client and network allow it.

4. Available production orders view

The production orders view contains customer-specific production order data. The naming pattern is:

sql

oee.v_<customer>_production_orders

The view is already filtered for the corresponding customer — no additional customer / client filter is required from your side.

5. Available columns

text

order_number
order_code
created_at
updated_at
start_time_utc
end_time_utc
start_time_local
end_time_local
start_date_local
end_date_local
duration_seconds
line_name
line_code
product_name
product_code
target_quantity
total_produced
good_quantity
rejected_quantity
rework_quantity
scrap_quantity
units_per_box
boxes_per_pallet
status_name
status_code
is_open

6. Column description

Column	Description
`order_number`	Production order number. Usually the main order identifier.
`order_code`	Internal order code. May be empty if the source PMS does not provide it.
`created_at`	Timestamp when the order was created in the PMS.
`updated_at`	Last update timestamp in the PMS.
`start_time_utc`	Order start timestamp in UTC.
`end_time_utc`	Order end timestamp in UTC. May be empty for open orders.
`start_time_local`	Order start timestamp in local operational time.
`end_time_local`	Order end timestamp in local operational time. May be empty for open orders.
`start_date_local`	Local start date. Recommended for daily operational analysis.
`end_date_local`	Local end date.
`duration_seconds`	Order duration in seconds.
`line_name`	Production line name.
`line_code`	Production line code.
`product_name`	Product name.
`product_code`	Product code.
`target_quantity`	Planned target quantity.
`total_produced`	Total produced quantity recorded by the system.
`good_quantity`	Good quantity recorded by the system.
`rejected_quantity`	Rejected quantity.
`rework_quantity`	Rework quantity.
`scrap_quantity`	Scrap quantity.
`units_per_box`	Units per box.
`boxes_per_pallet`	Boxes per pallet.
`status_name`	Human-readable production order status.
`status_code`	Technical production order status code.
`is_open`	Indicates whether the order is open. `1` = open, `0` = closed.

7. Possible status codes

Status code	Meaning
`PRODUCTION_ORDER_RECEIVED`	Order received / planned, not yet started.
`PRODUCTION_ORDER_RUNNING`	Order currently running.
`PRODUCTION_ORDER_COMPLETED`	Order completed.
`PRODUCTION_ORDER_SENDED`	Order sent / closed, depending on the PMS workflow.
`PRODUCTION_ORDER_DISABLED`	Order disabled.
`PRODUCTION_ORDER_DELETED`	Order deleted.

8. Reference SQL queries

Replace <provided_view_name> with the view provided by Neykos.

Basic test query

sql

SELECT count()
FROM <provided_view_name>

Latest updated orders

sql

SELECT
    order_number,
    line_name,
    product_name,
    target_quantity,
    total_produced,
    status_code,
    is_open,
    updated_at
FROM <provided_view_name>
ORDER BY updated_at DESC
LIMIT 10

Open orders

sql

SELECT
    order_number,
    line_name,
    product_name,
    target_quantity,
    total_produced,
    status_code,
    start_time_local,
    updated_at
FROM <provided_view_name>
WHERE is_open = 1
ORDER BY updated_at DESC

Summary by production line

sql

SELECT
    line_name,
    count()                  AS orders,
    countIf(is_open = 1)     AS open_orders,
    countIf(is_open = 0)     AS closed_orders,
    sum(target_quantity)     AS target_quantity,
    sum(total_produced)      AS total_produced
FROM <provided_view_name>
GROUP BY line_name
ORDER BY orders DESC

Production by local date

sql

SELECT
    start_date_local,
    line_name,
    count()                  AS orders,
    sum(target_quantity)     AS target_quantity,
    sum(total_produced)      AS total_produced
FROM <provided_view_name>
GROUP BY start_date_local, line_name
ORDER BY start_date_local DESC, line_name

9. Ways to connect

Everything below uses the same credentials. Pick the method that matches your stack.

9.1 HTTP API (curl)

ClickHouse exposes an HTTP interface for queries. Send the SQL as the POST body and pick a response format such as JSON, JSONEachRow, CSV, or TSV.

HTTP — direct IPHTTPS — domain

bash

curl 'http://89.167.19.228:8123/?database=oee&user=<provided_user>&password=<provided_password>' \
  --data-binary '
SELECT
    order_number,
    line_name,
    product_name,
    target_quantity,
    total_produced,
    status_code
FROM <provided_view_name>
LIMIT 10
FORMAT JSON
'

bash

curl 'https://integrations.neykos.net/?database=oee&user=<provided_user>&password=<provided_password>' \
  --data-binary '
SELECT
    order_number,
    line_name,
    product_name,
    target_quantity,
    total_produced,
    status_code
FROM <provided_view_name>
LIMIT 10
FORMAT JSON
'

Best practice

Send credentials via HTTP headers instead of query parameters to keep them out of logs:

bash

curl 'https://integrations.neykos.net/?database=oee' \
  -H 'X-ClickHouse-User: <provided_user>' \
  -H 'X-ClickHouse-Key:  <provided_password>' \
  --data-binary 'SELECT count() FROM <provided_view_name> FORMAT JSON'

9.2 Python — `clickhouse-connect` (recommended)

The official Python client supports the HTTP interface and returns native Python types, Pandas DataFrames, and Arrow tables.

bash

pip install clickhouse-connect pandas

python

import os
import clickhouse_connect

client = clickhouse_connect.get_client(
    host='integrations.neykos.net',
    port=443,
    secure=True,
    username=os.environ['NEYKOS_USER'],
    password=os.environ['NEYKOS_PASSWORD'],
    database='oee',
)

# Plain query → list of tuples
result = client.query("SELECT count() FROM v_customer_production_orders")
print(result.result_rows)

# Query as a Pandas DataFrame
df = client.query_df(
    """
    SELECT start_date_local, line_name,
           sum(target_quantity)  AS target,
           sum(total_produced)   AS produced
    FROM v_customer_production_orders
    GROUP BY start_date_local, line_name
    ORDER BY start_date_local DESC
    """
)
print(df.head())

If you must use the direct IP, set host='89.167.19.228', port=8123, secure=False.

9.3 Node.js / TypeScript — `@clickhouse/client`

bash

npm install @clickhouse/client

typescript

import { createClient } from '@clickhouse/client'

const client = createClient({
  url: 'https://integrations.neykos.net',
  username: process.env.NEYKOS_USER!,
  password: process.env.NEYKOS_PASSWORD!,
  database: 'oee',
})

const rs = await client.query({
  query: `
    SELECT order_number, line_name, total_produced, status_code
    FROM v_customer_production_orders
    WHERE is_open = 1
    ORDER BY updated_at DESC
    LIMIT 50
  `,
  format: 'JSONEachRow',
})

const orders = await rs.json<{
  order_number: string
  line_name: string
  total_produced: number
  status_code: string
}>()

console.log(orders)
await client.close()

9.4 JDBC

Use the official ClickHouse JDBC driver — class com.clickhouse.jdbc.ClickHouseDriver.

JDBC — no SSLJDBC — HTTPS

text

jdbc:clickhouse://89.167.19.228:8123/oee

text

jdbc:clickhouse:https://integrations.neykos.net:443/oee

Minimal Java example:

java

String url = "jdbc:clickhouse:https://integrations.neykos.net:443/oee";
Properties props = new Properties();
props.setProperty("user", System.getenv("NEYKOS_USER"));
props.setProperty("password", System.getenv("NEYKOS_PASSWORD"));

try (Connection conn = DriverManager.getConnection(url, props);
     Statement st = conn.createStatement();
     ResultSet rs = st.executeQuery("SELECT count() FROM v_customer_production_orders")) {
    while (rs.next()) System.out.println(rs.getLong(1));
}

9.5 Databricks / Spark

python

jdbc_url     = "jdbc:clickhouse:https://integrations.neykos.net:443/oee"
view_name    = "<provided_view_name>"
user         = dbutils.secrets.get("neykos", "user")       # or os.environ[...]
password     = dbutils.secrets.get("neykos", "password")

df = (
    spark.read
    .format("jdbc")
    .option("url", jdbc_url)
    .option("driver", "com.clickhouse.jdbc.ClickHouseDriver")
    .option("user", user)
    .option("password", password)
    .option("dbtable", view_name)
    .load()
)

display(df)

9.6 BI tools

Metabase

Admin → Databases → Add database → ClickHouse.
Host: integrations.neykos.net, Port: 443, SSL: ✅
Database: oee, User / Password: the ones Neykos provided.
Save. The provided view appears under oee.

Apache Superset

Install clickhouse-connect, then add a database with the SQLAlchemy URI:

text

clickhousedb+connect://<user>:<password>@integrations.neykos.net:443/oee?secure=true

Grafana

Install the Grafana ClickHouse data source plugin and configure:

Server address: integrations.neykos.net
Server port: 443
Protocol: HTTP, Secure connection: ✅
Default database: oee
User / Password from Neykos

Tableau

Use the ClickHouse JDBC connector with the JDBC URL from §9.4.

Power BI

Power BI Desktop ships with a built-in ClickHouse connector (Get Data → ClickHouse). Use integrations.neykos.net, port 443, SSL on, database oee, and the credentials Neykos shared with you. For older versions, install the ClickHouse ODBC driver and connect via ODBC.

9.7 Excel / Power Query (ODBC)

Install the ClickHouse ODBC driver.
Create a System DSN named Neykos pointing at integrations.neykos.net:443, database oee, SSL on.
In Excel: Data → Get Data → From Other Sources → From ODBC → Neykos DSN.

9.8 GUI clients (DBeaver, DataGrip, TablePlus)

Any GUI client that supports ClickHouse works the same way:

Setting	Value
Driver	ClickHouse (HTTP)
Host	`integrations.neykos.net`
Port	`443`
Database	`oee`
SSL / TLS	on
User	`<provided_user>`
Password	`<provided_password>`

DBeaver

Database → New Database Connection → ClickHouse → fill the fields above → Test connection → Finish. The provided view appears under oee → Views.

10. Notes and good practices

Access is read-only.
The provided user can only access the views explicitly enabled by Neykos.
The user does not have access to internal tables or to other customers' data.
The views already apply ClickHouse FINAL internally — you do not need to add FINAL in your queries.
The main production order identifier is usually order_number. order_code may be empty if the source PMS does not provide it.
For operational daily analysis, prefer start_date_local, start_time_local, and end_time_local. UTC timestamps are provided for technical integrations between systems.
Treat the password like any production secret — load it from environment variables or a secrets manager; never check it into a repository.

11. Support

If you don't have credentials yet, or you need a new view enabled, contact your Neykos point of contact. Bug reports and integration questions are welcome at the same address.

Data integration ​

1. Overview ​

2. Connection information ​

3. SSL configuration ​

4. Available production orders view ​

5. Available columns ​

6. Column description ​

7. Possible status codes ​

8. Reference SQL queries ​

Basic test query ​

Latest updated orders ​

Open orders ​

Summary by production line ​

Production by local date ​

9. Ways to connect ​

9.1 HTTP API (curl) ​

9.2 Python — clickhouse-connect (recommended) ​

9.3 Node.js / TypeScript — @clickhouse/client ​

9.4 JDBC ​

9.5 Databricks / Spark ​

9.6 BI tools ​

Metabase ​

Apache Superset ​

Grafana ​

Tableau ​

Power BI ​

9.7 Excel / Power Query (ODBC) ​

9.8 GUI clients (DBeaver, DataGrip, TablePlus) ​

10. Notes and good practices ​

11. Support ​

Data integration

1. Overview

2. Connection information

3. SSL configuration

4. Available production orders view

5. Available columns

6. Column description

7. Possible status codes

8. Reference SQL queries

Basic test query

Latest updated orders

Open orders

Summary by production line

Production by local date

9. Ways to connect

9.1 HTTP API (curl)

9.2 Python — `clickhouse-connect` (recommended)

9.3 Node.js / TypeScript — `@clickhouse/client`

9.4 JDBC

9.5 Databricks / Spark

9.6 BI tools

Metabase

Apache Superset

Grafana

Tableau

Power BI

9.7 Excel / Power Query (ODBC)

9.8 GUI clients (DBeaver, DataGrip, TablePlus)

10. Notes and good practices

11. Support