Kafka’s distributed processing, scalability, and fault tolerance led TigerGraph to make it part of our internal design from day one. Our Kafka data ingestion connector is built-in; nothing to install. Based on the trusted Kafka Connect framework, the TigerGraph Kafka Connector ensures seamless and reliable data integration.
Today’s data lakes — or lakehouses — marry storage capabilities of traditional data lakes with data processing capabilities of Spark. A Spark-based connector is a natural fit for these environments. The TigerGraph Spark connector connects directly to Spark, transforming dataframes into graph data. You can also use it as a high-throughput, bidirectional portal to transport data to and from a wide range of data platforms.
The TigerGraph JDBC Driver is a Type 4 driver, converting JDBC calls directly into TigerGraph database commands. This driver supports TigerGraph builtin queries, loading jobs, compiled queries (i.e., queries which has been installed to the GSQL server) and interpreted queries (i.e., ad hoc queries, without needing to compile and install the queries beforehand). The driver will then talk to TigerGraph’s REST++ server to run queries and get their results.
