Companies that use Dgraph
Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.
209
companies
List of companies using Dgraph
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"dgraph\"
]
}"Technology
is any of
Dgraph
Employees90Technology, Information and MediaDgraphHigh confidence
Employees28kRevenue$9.6BIT Services and IT ConsultingDgraphHigh confidence
Employees120Revenue$7MDefense and Space ManufacturingDgraphHigh confidence
Employees293kComputer Hardware ManufacturingDgraphHigh confidence
Employees112Defense and Space ManufacturingDgraphHigh confidence
Employees88kRevenue$35BDefense and Space ManufacturingDgraphHigh confidence
Employees1.2kFinancial ServicesDgraphHigh confidence
Employees84Software DevelopmentDgraphHigh confidence
Employees5.2kRevenue$1BSoftware DevelopmentDgraphHigh confidence
Employees43IT Services and IT ConsultingDgraphHigh confidence
We have data on 209 companies and users that use Dgraph. Our Dgraph users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
How to target Dgraph users
- How to customize this list?
You can customize this data to your needs by filtering for geography, industry, company size, revenue, technology usage, job postions and more. You can download the data in Excel or CSV format.
- How to be alerted when companies adopt this technology?
You can get alerts for this data. You can get started by selecting the technology you are interested in and then you will receive alerts in your inbox when there are new companies using that technology.
- How to import this data to my CRM?
You can export this data to an Excel file, which can be imported into your CRM. You can also export the data to an API.
Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
Dgraph is a modern, distributed, native graph database built to leverage the power of graph-based data modeling for real-time applications. It offers a scalable and high-performance solution for managing and querying interconnected data efficiently. Dgraph's architecture is designed to handle complex relationships and interconnected data points with ease, making it a valuable tool for applications requiring complex data structures and relationships.
Graph Databases, the category to which Dgraph belongs, focuses on storing and querying data in graph structures consisting of nodes, edges, and properties. This category enables users to represent and navigate complex relationships between data points effectively, making it ideal for use cases such as social networks, recommendation engines, fraud detection, and network analysis. Dgraph stands out in the graph database category for its focus on distributed and scalable graph processing, enabling users to work with massive datasets in real-time.
Founded in 2015 by Manish Jain, Dgraph was created with the vision of providing a graph database solution that could handle the challenges of modern, highly interconnected data. Motivated by the need for a performant and scalable graph database that could keep up with the demands of real-time applications, Jain set out to develop a system that could provide both speed and scalability while integrating seamlessly with modern application architectures.
Currently, Dgraph holds a promising position in the graph database market with a growing user base and increasing adoption by enterprises looking to harness the power of graph-based data modeling. As the demand for real-time and scalable graph databases continues to rise, Dgraph is poised to expand its market share further. With its focus on distributed processing and high performance, Dgraph is well-positioned to capitalize on the increasing interest in graph databases for powering modern applications, suggesting a positive outlook for its future growth.