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Scannen Sie die Systeme,
die Sie bereits besitzen.

38 Konnektoren über Datenbanken, Warehouses und Lakehouses, Streaming, Object Storage, Kollaborationstools, Analytics und öffentliche Inhalte — alle speisen einen Beweisstrom.
Katalog durchstöbernBetreiben und einen anbinden
Custom Connector
Sandbox
WordPress
Slack
S3-Compatible Storage
Azure Blob Storage
Google Cloud Storage
PostgreSQL
MySQL
Microsoft SQL Server
Oracle
Apache Hive
Databricks
Snowflake
MongoDB
Neo4j
Power BI
Tableau
Confluence
Jira
Jira Service Management
SQLite
Notion
Email
YouTube
Reddit
Delta Lake
Apache Iceberg
Apache Kafka
Elasticsearch
OpenSearch
Meilisearch
Mounted Folder
Microsoft 365
Google Workspace
Dropbox
Hugging Face
Git Repository
Custom Connector
Sandbox
WordPress
Slack
S3-Compatible Storage
Azure Blob Storage
Google Cloud Storage
PostgreSQL
MySQL
Microsoft SQL Server
Oracle
Apache Hive
Databricks
Snowflake
MongoDB
Neo4j
Power BI
Tableau
Confluence
Jira
Jira Service Management
SQLite
Notion
Email
YouTube
Reddit
Delta Lake
Apache Iceberg
Apache Kafka
Elasticsearch
OpenSearch
Meilisearch
Mounted Folder
Microsoft 365
Google Workspace
Dropbox
Hugging Face
Git Repository
Nach Kategorie

Woher die Beweise kommen

Konnektoren sind gruppiert nach dem, was sie sind, nicht nach Hersteller. Zählungen kommen direkt aus dem Schema — diese Seite kann also nie von dem abweichen, was das Produkt wirklich unterstützt.

  • Warehouse & Lakehouse11

    Analytical compute platforms and catalog-first ingestion.

  • Databases9

    Operational and document stores for row and collection scans.

  • Collaboration9

    Team communication and workspace activity streams.

  • Social Media2

    Social and video platforms with public posts and transcripts.

  • Analytics & BI2

    Dashboards, reports, and business intelligence assets.

  • Graph Databases1

    Graph-native stores with node and relationship traversal.

  • Code Repositories1

    Version-controlled source, configuration, and documentation.

  • Streaming1

    Event streams and message brokers sampled for content.

  • Web & UGC1

    Public-facing websites and user-generated content.

  • Other1

    Sources discovered in schema that have not been categorized yet.

Voller Katalog

Alle 38 Konnektoren

Suchen Sie nach Name, Kategorie oder Fähigkeit. Jeder Eintrag verlinkt auf seine Konfigurationsreferenz in der Doku-Site — Pflichtfelder, Auth und ein durchgearbeitetes Beispiel.

Konfigurationsreferenz
Quellen-Katalog
Konnektor nach Kategorie wählen
38 Treffer

Databases

Operational and document stores for row and collection scans.

9 Quellen
Elasticsearch
Discover Elasticsearch indices and sample documents for detection.
Meilisearch
Discover Meilisearch indexes and sample documents for detection.
Microsoft SQL Server
Scan Microsoft SQL Server tables and views.
MongoDB
Scan MongoDB collections for Atlas or on-prem deployments.
MySQL
Scan MySQL tables with detector-ready row sampling.
OpenSearch
Discover OpenSearch indices and sample documents for detection.
Oracle
Scan Oracle service objects with optional view lineage.
PostgreSQL
Scan PostgreSQL tables with detector-ready row sampling.
SQLite
Scan tables in a local SQLite database file with no server required.

Graph Databases

Graph-native stores with node and relationship traversal.

1 Quellen
Neo4j
Scan Neo4j node labels and relationship structure for graph data.

Warehouse & Lakehouse

Analytical compute platforms and catalog-first ingestion.

11 Quellen
Apache Hive
Scan Hive tables and views across selected databases.
Apache Iceberg
Scan Apache Iceberg tables in S3-compatible storage — schema, snapshots, and row sampling, no Spark required.
Azure Blob Storage
Scan blobs from Azure Storage containers with key, SAS, or managed identity auth.
Databricks
Scan Unity Catalog assets, notebooks, and pipelines.
Delta Lake
Scan Delta Lake tables in S3-compatible storage — schema, versions, and row sampling, no Spark required.
Google Cloud Storage
Scan objects from Google Cloud Storage buckets with ADC or service account credentials.
Hugging Face
Stream files from a Hugging Face dataset, model, or space repository without cloning it.
Mounted Folder
Scan a folder of documents, spreadsheets and images — on this computer, or mounted into the cluster.
S3-Compatible Storage
Scan objects from AWS S3, MinIO, Cloudflare R2, Backblaze B2, and other S3-compatible endpoints.
Sandbox
Upload files directly and scan them through the standard source lifecycle.
Snowflake
Scan Snowflake tables and views with flexible authentication.

Code Repositories

Version-controlled source, configuration, and documentation.

1 Quellen
Git Repository
Scan the source, configuration, and documents on one branch of any Git repository — GitHub, GitLab, Bitbucket, Azure DevOps, or self-hosted.

Streaming

Event streams and message brokers sampled for content.

1 Quellen
Apache Kafka
Discover Kafka topics and sample messages for detection.

Web & UGC

Public-facing websites and user-generated content.

1 Quellen
WordPress
Connect to WordPress to scan posts and pages.

Social Media

Social and video platforms with public posts and transcripts.

2 Quellen
Reddit
Scan subreddits — posts, threaded comments, attached media, and linked video transcripts. Always read-only.
YouTube
Scan YouTube channels and videos, fetching metadata and transcripts for detection.

Collaboration

Team communication and workspace activity streams.

9 Quellen
Confluence
Scan Confluence spaces, pages, comments, and attachments.
Dropbox
Scan documents, spreadsheets, images, and Paper docs stored in a Dropbox account.
Email
Scan IMAP mailboxes (Gmail, Outlook/M365, and more) for messages and attachments.
Google Workspace
Scan Google Drive files, Docs, Sheets, and Slides across My Drive and shared drives.
Jira
Scan Jira issues, comments, links, and attachments.
Jira Service Management
Scan Jira Service Management requests, comments, and attachments.
Microsoft 365
Scan SharePoint sites, OneDrive files, and Teams files via Microsoft Graph API.
Notion
Scan Notion pages, data sources, comments, and file attachments.
Slack
Connect to Slack to scan channel messages.

Analytics & BI

Dashboards, reports, and business intelligence assets.

2 Quellen
Power BI
Scan Power BI workspaces, datasets, reports, and dashboards.
Tableau
Scan Tableau workbooks and datasources.

Other

Sources discovered in schema that have not been categorized yet.

1 Quellen
Custom Connector
Write the connector yourself in a Python notebook, for a system nothing else covers.
Jeder Konnektor

Was alle gemeinsam haben

Das System am anderen Ende wechselt. Was Classifyre mit dem Gelesenen tut, nicht.

  • Assets, nicht nur Zeilen

    Jeder Konnektor liefert Assets mit dranhängenden Quell-Metadaten — Owner, Pfad, Zeitstempel — damit ein Befund immer mitführt, woher er kam.

    Assets & Metadaten →

  • Vor dem Scan testen

    Jede Quelle lässt sich aus der App dry-runnen: Credentials prüfen, sehen, was sie lesen würde, und erst dann einen vollen Scan committen.

    Quellen testen →

  • Sampling, das Kosten deckelt

    Große Tabellen und Dateien werden durch Sampling-Fenster mit Cursor pro Asset gelesen — ein Scan liest also einen begrenzten Ausschnitt statt allem.

    Sampling →

  • Quellenübergreifende Fingerprints

    Derselbe Wert in zwei verschiedenen Systemen wird per Identität verlinkt — wo die meisten echten Ermittlungen tatsächlich beginnen.

    So funktioniert es →

Fehlt der eine, den Sie brauchen?

Konnektoren sind Plugins, und das Projekt ist Open Source — die Antwort ist also entweder ein Pull Request oder ein Gespräch. Enterprise-Kunden bekommen Quellen für die Systeme ihrer Branche, gebaut von unseren Engineers.

Konnektor anfragenMit uns über Enterprise sprechen