KNIME · Infrastruttura · YoctoIT tech page

Connettività

Connectors for databases, files, APIs and cloud: the data gets taken where it is — SAP, IBM i and ERPs included.

FOCUS · THE DATA WHERE IT IS300+ connectors without code: from Db2 for i to the SaaS, everything enters the workflow
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YoctoIT material for clients and partners · KNIME and the products mentioned are trademarks of KNIME AG.
01 · What it is

Connettività universale, made clear.

The first half of every analysis is GETTING to the data: KNIME has connectors for (almost) everything — databases via JDBC (Db2 for i included: the IBM i ERP gets queried), SAP, files of every format, REST APIs, cloud storage, scattered Excels. Without code: the node gets configured, the data arrives.

300+
the connectors available: the odd source is already there
JDBC
any database, IBM i included: our world connects
REST
the APIs queried as nodes: even the SaaS without a dedicated connector
Connettività universale
OFFICIAL KNIME BRANDING · CONNECTIVITY
WORKFLOW REALE · CONNETTORI DATABASE · FONTE: KNIME DOCS
REAL WORKFLOW · DATABASE CONNECTORS · SOURCE: KNIME DOCS
02 · How to use it well

The things that make the difference.

The data's roads

The workflow that analyzeswhere everything converges
Databases & SAP
Files & Excel
APIs & cloud
the data's three continents
Governed credentialssecrets out of the workflows
IBM i · Db2 for ithe ERP, finally in analysis
No source left behind

The IBM i ERP inside

Db2 for i via JDBC: the company's core data in the analyses — our specialty meets KNIME.

Credentials out of the flows

Vaults and shared profiles: the passwords never hardwired into the workflows.

Queries pushed to the database

The heavy lifting done by the source (pushdown): the workflow light, the DB exploited.

The Excels tamed

The scattered sheets standardized on entry: data hygiene as the first node.

03 · In depth

400+ connectors: the data wherever it is

KNIME connects to everything: databases (universal JDBC plus the dedicated nodes: Oracle, SQL Server, Postgres, MySQL), warehouses (Snowflake, BigQuery, Redshift, Databricks), files (Excel, CSV, Parquet, JSON, XML), applications (Salesforce, SAP via connectors, SharePoint, Google), object storage (S3, Azure Blob), generic REST APIs; the in-database processing pushes the computation to the database (the SQL generated by the nodes): the terabyte doesn't travel.

  • JDBC universale — any database with a driver: the legacy included
  • In-database — the nodes that generate SQL: the computation goes to the data, not vice versa
  • Warehouse nativi — Snowflake, BigQuery, Databricks: the modern covered
  • SAP & Salesforce — the ERPs as sources: the ERP in the flow
  • REST generico — any API queried as nodes: the everyday integration
  • Parquet/ORC — the columnar formats: big data without a cluster
04 · Numbers and lifecycle

The numbers that matter.

400+
the connectors available
0
external ETL needed: KNIME IS the ETL
SQL
generated by the nodes: the in-database that scales
1
one platform across all the sources
Data integration is half the analytical work: sources, credentials and ETL flows set up by us — the data that arrives on its own.
05 · Use cases

Where it really pays off.

Data from the ERP

IBM i and SAP in the daily analyses.

Heterogeneous sources

ERP + CRM + Excel + APIs: reunited in one flow.

Data migrations

Reading, transformation and loading, visual.

The right data always lives in three inconvenient places: the connectors reach it — we know the roads.