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The startup, which expects to double its workforce of 44 people by next year launched a cloud version of its subscription offering on Tuesday called TigerGraph Cloud. Since launching its first product in 2017, the company says its gross revenue has increased at an annual rate of 300 percent. TigerGraph is on track to generate more than $10 million in revenues in 2019.
At re:Invent yesterday, the company announced it’s making its product available in Database as a Service (DBaaS) form on AWS, as TigerGraph Cloud.
The company says that in addition to the service itself, TigerGraph Cloud includes “out-of-the-box starter kits for quicker application development – for use cases such as Anti-Fraud, Anti-Money Laundering (AML), Customer 360, Enterprise Graph analytics and more.”
The transition of graph databases to the cloud reflects growing demand for public cloud connections to a range of database platforms that has gained momentum over the last two years, beginning with managed NoSQL and relational databases.
Today, TigerGraph, the world’s fastest graph analytics platform for the enterprise, introduced TigerGraph Cloud, the simplest, most robust and cost-effective way to run scalable graph analytics in the cloud.
The release continues, “TigerGraph enables organizations to accelerate their time to value to gain maximum insight from massive amounts of interconnected data at lightning speed. With accelerated scale out capability and TigerGraph’s novel MPP implementation, TigerGraph provides the perfect fit for organizations to quickly adapt to the data needs of the future.
“Organizations already rely on TigerGraph to enable some of the worlds largest and most mission-critical use cases,” said Dr. Yu Xu, CEO and founder, TigerGraph. “This release makes it even easier for enterprises to connect TigerGraph to their existing infrastructure. It’s all part of our commitment of delivering the best graph engine on the market to power the applications that are paving the way of the future.”
TigerGraph wants to be the graph database that companies choose when they are running up against scalability limits, and it will find itself in direct competition with the JanusGraph fork of Titan, which is backed by Google and IBM, and the DataStax fork as well. Neo4j is not going to sit still, either.
The new features include better integration with popular relational and NoSQL engines, support for software containers, one-click availability in Amazon Web Services Inc. and Microsoft Corp. Azure marketplaces and a new graph algorithm library.
TigerGraph has added integration with popular databases and data storage systems including: RDBMS, Kafka, Amazon S3, HDFS, and Spark (coming soon). TigerGraph said a github repository will host open source connectors to TigerGraph as they roll out.
TigerGraph just announced a Neo4j Migration Toolkit, which is largely based on translating Cypher, Neo4j’s query language, to GSQL.