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DuckDB

Anomstack supports DuckDB as a data source for your metrics. DuckDB is a fast analytical database that can read and write data from various file formats.

Configuration​

Configure DuckDB in your metric batch's config.yaml:

db: "duckdb"
table_key: "metrics"  # Default table to store metrics
metric_batch: "your_metric_batch_name"
ingest_cron_schedule: "*/3 * * * *"  # When to run the ingestion
ingest_sql: >
  select
    current_timestamp() as metric_timestamp,
    'metric_name' as metric_name,
    your_value as metric_value
  from your_table;

Default Configuration​

Many configuration parameters can be set in metrics/defaults/defaults.yaml to apply across all metric batches. Key defaults include:

db: "duckdb"  # Default database type
table_key: "metrics"  # Default table name
ingest_cron_schedule: "*/3 * * * *"  # Default ingestion schedule
model_path: "local://./models"  # Default model storage location
alert_methods: "email,slack"  # Default alert methods

You can override any of these defaults in your metric batch's configuration file.

Features​

DuckDB supports:

  • Local file-based databases
  • MotherDuck cloud integration
  • Reading from various file formats (CSV, Parquet, JSON)
  • SQL queries with Python integration

Examples​

Check out the DuckDB example for a complete working example.

Best Practices​

  • Use appropriate file formats for your data
  • Consider query optimization
  • Implement proper file permissions
  • Use parameterized queries

Limitations​

  • Local storage considerations
  • Memory usage for large datasets
  • Concurrent access limitations