使用Dgraph的公司
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.
使用Dgraph的公司列表
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
员工数89Technology, Information and MediaDgraph高置信度
员工数28k收入$9.6BIT Services and IT ConsultingDgraph高置信度
员工数120收入$7MDefense and Space ManufacturingDgraph高置信度
员工数293kComputer Hardware ManufacturingDgraph高置信度
员工数99Defense and Space ManufacturingDgraph高置信度
员工数88k收入$35BDefense and Space ManufacturingDgraph高置信度
员工数1.2kFinancial ServicesDgraph高置信度
员工数84Software DevelopmentDgraph高置信度
员工数5.2k收入$1BSoftware DevelopmentDgraph高置信度
员工数43IT Services and IT ConsultingDgraph高置信度
我们拥有关于209家公司和用户使用Dgraph的数据。我们的Dgraph用户和客户列表可供下载，并附有重要的公司信息，包括行业分类、组织规模、地理位置、融资轮次和收入数据等。
技术使用统计和市场份额
如何定位 Dgraph 用户
- 如何自定义此列表？
您可以根据地理位置、行业、公司规模、收入、技术使用、职位发布等需求自定义此数据。您可以将数据下载为Excel或CSV格式。
- 如何在公司采用此技术时收到通知？
您可以为此数据设置提醒。您可以通过选择您感兴趣的技术开始，当有新公司使用该技术时，您将收到收件箱中的提醒。
- 如何将此数据导入我的CRM？
您可以将此数据导出为Excel文件，然后导入到您的CRM中。您也可以将数据导出到API。
常见问题
我们的数据来源于从数百万家公司收集的职位发布。我们监控公司网站、招聘网站和其他招聘平台上的这些发布。分析职位发布提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。
我们每天刷新数据，以确保您访问的是最新的信息。这一频繁的更新过程保证了我们的洞察和情报反映行业的最新发展和趋势。
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.