The Graph.Build SQL Transformer automates the conversion of relational SQL database data into graph-ready data formats for modern knowledge graph and graph database platforms.
Generate standards-compliant RDF 1.1 (N-QUADS) or Labelled Property Graph CSV outputs with integrated provenance support. Designed for scalability and interoperability, the transformer enables rapid ingestion of enterprise relational data into semantic web, linked data, analytics, and graph AI workflows.
The platform is lightweight, highly scalable, and platform-agnostic, with compatibility across common graph database technologies and graph processing environments.
Highlights
Convert relational SQL database data into RDF or Labelled Property Graph data formats
Built-in provenance support for improved traceability, governance, and data lineage
Compatible with semantic web and graph database workflows including SPARQL and RDF standards
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This contract covers a single pricing dimension: the number of SQL Transformer Hosts you run. You pay based on how many Hosts you deploy. The SQL Transformer connects to SQL sources over JDBC and processes that data into graph model data. Each Host is an independent, scalable processor. To increase capacity, you add more Hosts, so your cost scales with the count you deploy. There are no separate tiers or sizes to choose from — pricing is driven only by the Host quantity.
Top-of-mind questions for buyers
What counts as one Host for billing?
A Host is one running instance of the SQL Transformer processor. Each Transformer deploys as its own container. You count each active container instance as one Host. Adding more Hosts adds more independent, scalable processors handling your SQL-to-graph work.
What does the SQL Transformer Host actually do with my data?
Each Host connects to SQL sources over a JDBC connection, including relational databases. It transforms that data into graph model data using your configured mappings. It also records provenance each time it ingests data, giving you a history of the data state over time.
How does my cost change as data volume or workload grows?
Cost scales with Host count, not data volume directly. One Host may suffice for a proof of concept. As throughput needs grow, you add Hosts to increase processing capacity. Each Host is independent and scalable, so you add capacity by deploying more Hosts.
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Version release notes
Smaller memory footprint during transformations
Increased memory allocation for java heap within the docker container
Improvements to AWS License Manager token checkins during unexpected shutdowns
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