Diskover Alternate Ingesters - User Guide Index
Overview
Alternate ingesters redirect Diskover scan output from Elasticsearch to alternative storage systems such as Apache Parquet files, cloud data warehouses, or other data platforms. Unlike index plugins that enrich metadata within Elasticsearch, ingesters completely replace the default storage backend.
This page serves as the central reference for all alternate ingester documentation. Each guide provides installation instructions, configuration details, output format specifications, analytics tool integration examples, and troubleshooting information.
Key Difference from Plugins: Ingesters are selected via the --altingester command-line flag and completely replace Elasticsearch as the data destination. Data stored via ingesters is not accessible through the Diskover Web UI—you'll query this data using analytics tools appropriate for the storage format.
Available Ingesters
📊 Data Lake & Analytics
Ingester | Description | Use Case |
|---|---|---|
Exports scan metadata to Apache Parquet columnar format for integration with data lakes, data warehouses, and analytics platforms. | Feed unstructured data metadata into enterprise data platforms like Snowflake, AWS Athena, Google BigQuery, or Apache Spark for unified analytics. |
Ingesters vs Elasticsearch: When to Use Each
Aspect | Elasticsearch (Default) | Alternate Ingesters |
|---|---|---|
Query Method | REST API / Diskover Web UI | SQL engines, Pandas, Spark, cloud analytics |
Real-time Search | Yes, millisecond latency | No, batch processing |
Diskover Web UI | Full support | Not supported |
Infrastructure | Elasticsearch cluster required | Varies by ingester (local disk, cloud storage, etc.) |
Analytics Integration | Limited | Native integration with data platforms |
Best For | Interactive exploration, file actions, workflows | Historical analysis, data lake integration, compliance archival |
Decision Guide
Use Elasticsearch (default) when:
You need the Diskover Web UI for interactive browsing and file actions
Real-time search and filtering are required
Users need immediate access to scan results
You're leveraging Diskover workflows, automations, and file actions
Use Alternate Ingesters when:
Building a data lake or data warehouse that includes file metadata
Integrating with analytics platforms (Snowflake, BigQuery, Athena, Spark)
Performing historical analysis across multiple scans
Archiving scan data for compliance or long-term retention
Minimizing infrastructure costs for stored scan data
Hybrid Approach: Many organizations use both approaches—Elasticsearch for active, real-time operations and alternate ingesters for archival and analytics. You can run scans with different ingesters for different storage targets.
Quick Reference
Output Formats by Ingester
Ingester | Output Format | Query Tools |
|---|---|---|
Parquet | Apache Parquet files (columnar) | Snowflake, Athena, BigQuery, Spark, Pandas, DuckDB |
License Requirements
All alternate ingesters require the MLT (MultiStream Edition) license tier.
Ingester | License |
|---|---|
Parquet | MLT |
External Dependencies
Ingester | Dependencies |
|---|---|
Parquet | pandas 2.2.3, pyarrow 18.0.0 |
How Ingesters Work
Alternate ingesters are invoked using the --altingester command-line flag:
# Linux python3 /opt/diskover/diskover.py --altingester <ingester_name> /path/to/scan # Windows python "C:\Program Files\Diskover\diskover.py" --altingester <ingester_name> D:\path\to\scan
Key Points:
Configure — Set up the ingester in Diskover Admin > Settings > Alternate Ingesters
Execute — Run a scan with the
--altingesterflagAlternative Output — Scan data goes to the ingester's target instead of Elasticsearch
Query Externally — Use analytics tools appropriate for the output format
Important: The
--altingesterflag completely replaces Elasticsearch output for that scan. No data will be searchable in the Diskover Web UI.
Support & Resources
Diskover Documentation: docs.diskoverdata.com
Support Portal: support.diskoverdata.com
Last Updated: January 2026
Diskover Data, Inc.
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