Streambased Documentation
  • Home
  • Overview
    • Key Concepts
  • Streambased Cloud
    • Streambased Cloud UI
      • Create your first Streambased cluster
      • Create your first Streambased API Key
      • Running your first A.S.K Query
      • Exploring your data using S.S.K
    • Iceberg Service for Kafka - I.S.K.
      • Overview
      • Architecture
      • Usage
      • Quick Start
    • Analytics Service for Kafka - A.S.K.
      • Overview
      • Architecture
      • Connecting to Streambased A.S.K.
        • Connect Superset to Streambased A.S.K.
        • Connect Jupyter to Streambased A.S.K.
        • Connect a JDBC Client to Streambased A.S.K.
        • Connect an ODBC client to Streambased A.S.K.
        • Connect a Python Application (SQL Alchemy) to Streambased A.S.K.
    • Storage Service for Kafka - S.S.K.
      • Overview
      • Connecting to Streambased S.S.K.
        • Connecting a S3 compatible client to Streambased S.S.K.
        • Connect a S3manager to Streambased S.S.K.
  • Streambased Platform
    • Overview
    • Requirements
    • Step by Step Installation
    • Configuration
    • Connecting Analytical Applications to Streambased
      • Connect Superset to Streambased
      • Connect Jupyter to Streambased
      • Connect a JDBC Client to Streambased
      • Connect an ODBC client to Streambased
      • Connect a Python Application (SQL Alchemy) to Streambased
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  1. Streambased Cloud
  2. Iceberg Service for Kafka - I.S.K.

Quick Start

Fastest way to try it out is to use the example GitHub repository:

  • Clone the repository

  • Populate streambased.env with environment specific configuration (ISK and SSK regional endpoints and your Streambased API key / secret)

  • Start Spark / Trino through docker compose

  • Query away.

Alternatively you can setup your own Spark or Trino clients - refer to client configuration reference.

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Last updated 12 days ago