Zingg-0.3.3
  • Welcome to Zingg
  • Step By Step Guide
    • Installation
      • Working with Docker Image
    • Hardware Sizing
    • Configuration
    • Creating training data
      • findTrainingData
      • label
      • findAndLabel
      • Using preexisting training data
      • Exporting labeled data as csv
    • Building and saving the model
    • Finding the matches
    • Linking across datasets
  • Data Sources and Sinks
    • Zingg Pipes
    • Snowflake
    • Cassandra
    • MongoDB
    • Neo4j
    • Parquet
  • Running Zingg on Cloud
    • Running on AWS
    • Running on Azure
    • Running on Databricks
  • Zingg Models
    • Pretrained models
  • Improving Accuracy By Defining Own Functions
  • Generating Documentation
  • Output Scores
  • Security And Privacy
  • Updating Labeled Pairs
  • Reporting bugs and contributing
  • Community
  • Frequently Asked Questions
  • Reading Material
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Data Sources and Sinks

PreviousLinking across datasetsNextZingg Pipes

Last updated 2 years ago

Zingg connects, reads and writes to most on-premise and cloud data sources.

Zingg can read and write to Snowflake, Cassandra, S3, Azure, Elastic, major RDBMS and any Spark supported data sources. Zingg also works with all major file formats like Parquet, Avro, JSON, XLSX, CSV, TSV etc. This is done through the Zingg abstraction.

pipe
zinggConnectors