Skip to main content

Ingest and Consume Data

Bulk Load Data from Various Sources​

Recipe to ingest data into ApertureDB:

  • Setup ApertureDB instance in your environment or use our hosted service
  • Configure the database
  • Define metadata schema depending on application use case
  • Generate CSV files for data ingestion
  • Use our CSV data loaders that parallelize load of batches of all object types
  • Setup periodic loading with tools like Airflow
  • For smaller, sporadic additions or updates, use our query language directly through Python scripts or Jupyter notebooks

Monitor the Status of your Database​

Once ingested, you can see it's status on ApertureDB web UI

You can also monitor the resource utilization and logs from our Grafana dashboard.

Various ApertureDB Query Alternatives​

In addition to graphically querying from our web frontend, you can query data from ApertureDB in the following ways:

  • Use the REST API from any client (we provide Python wrappers) to send JSON-based queries
  • Query using the Python object wrapper or using JSON queries from Python in Jupyter notebooks or C++ applications
  • Query from within ML frameworks like PyTorch, Tensorflow using ApertureDB Datasets