Investor thirst for technology that unites disparate data sources across organizations continues to intensify, as Apollo Graph Inc. today said it closed a new $130 million funding round.

The Series D round brings its total funding to $183 million and valuation to $1.5 billion. Apollo joins a parade of the data and analytics companies that have been showered with investments this year, including Databricks Inc.’s $1 billion round in February, Starburst Data Inc.’s $100 million funding in January, Dataiku Inc.’s $400 million raise early this month and the $325 million investors bestowed on graph database maker Neo4j Inc. in June.

Founded in 2011, Apollo Graph’s “Data Graph Platform,” which is based on the GraphQL query language, is used by application developers to build “data graphs” on top of existing application program interfaces to speed development and response times.

GraphQL was developed by Facebook Inc. and released to open source in 2015. Described as a query language for APIs and a runtime for fulfilling queries with existing data, GraphQL enables developers to specify the results they are seeking more precisely and receive a single response from multiple sources.

Apollo positions GraphQL as a core component of the new technology stacks that organizations are building to unify data and services. It essentially creates a virtual view that can be queried with a single statement. Developers also get a single view of data types, services and usage patterns.

Enterprise endorsement

Apollo said more than 30% of Fortune 500 companies already use its technology, including Walmart Inc., Paypal Holdings Inc., Expedia Inc., Wayfair Inc., New York Times Co. and Audi AG. The company claims to process more than 6 billion queries daily on its platform. Its recurring enterprise revenue grew 274% over the last 12 months, the company said without providing specifics.

Despite the use of the term “graph” in its name, GraphQL is not the same as graph databases, which use a unique data representation system based on relationships between data elements. GraphQL is considered an efficient way to query graph databases and is broadly supported by them but it can also be used to query standard relational data stores. However, because the way it represents data elements is graphlike, it’s considered a good candidate for use cases such as recommendation engines and fraud detection.

Funding was led by Insight Partners Inc. with participation from existing investors including Andreessen Horowitz LLC, Matrix Partners Management Services LP and Trinity Ventures LLC. Other investors included Next47 GmbH and Hatim Shafique, chief customer officer at Databricks.

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