Expand Your Data and Analytics Capabilities with TigerGraph Connectors

TigerGraph, the only scalable graph database for the enterprise, delivers broader insight into all the relationships from your data. But, this requires deep integration with both upstream and downstream data sources. To address this need, TigerGraph has built a suite of connectors to complement your existing analytics capabilities by making the power of advanced analytics on connected data available to you better than before.

Data Ingestion Connectors

Built-in Kafka Connect

TigerGraph’s built-in Kafka Connect data ingestion framework means you can get your data into TigerGraph quickly and reliably. Not only does it offer streaming mode, parallel processing, and built-in redundancy and retry, it also leverages the open Kafka Connect ecosystem to support a wide range of data sources and data formats. Sources:
  • Cloud storage: Amazon S3, Google Cloud Storage, Microsoft Azure
  • Data Warehouses like BigQuery (available) and Snowflake (coming soon)
  • External Kafka clusters
  • Databricks DeltaLake (coming soon)
Data formats:
  • CSV
  • JSON
  • Parquet
  • Avro (from an external Kafka cluster)
TigerGraph 3.9.3 Data Loading Architecture

JDBC Connector

TigerGraph’s open-source JDBC driver is a type-4 driver that converts JDBC calls directly into TigerGraph REST API calls. Handling both data loading and queries, this connector can serve a wide variety of needs from a wide range of applications.

For example, use the JDBC connector to ingest DataFrames from Spark.