使用GraphDb的公司
It is an enterprise ready Semantic Graph Database, compliant with W3C Standards. Semantic graph databases (also called RDF triplestores) provide the core infrastructure for solutions where modelling agility, data integration, relationship exploration and cross-enterprise data publishing and consumption are important.
使用GraphDb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\": [
\"graphdb\"
]
}"Technology
is any of
GraphDb
员工数244kFinancial ServicesGraphDb高置信度
员工数6.9kBroadcast Media Production and DistributionGraphDb高置信度
员工数717收入$58MInformation ServicesGraphDb高置信度
员工数61kFinancial ServicesGraphDb高置信度
员工数740Advertising ServicesGraphDb高置信度
员工数224收入$7.8MIT Services and IT ConsultingGraphDb高置信度
员工数177IT Services and IT ConsultingGraphDb高置信度
员工数14Business Consulting and ServicesGraphDb高置信度
员工数14Software DevelopmentGraphDb高置信度
员工数18Business Consulting and ServicesGraphDb高置信度
我们拥有关于1,483家公司和用户使用GraphDb的数据。我们的GraphDb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 GraphDb 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。
Graph databases, often referred to as GraphDB, are a type of database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. These databases are well-suited for scenarios where relationships between data points are as important as the data points themselves, making them ideal for applications requiring complex querying and deep relationship analysis.
GraphDB falls under the category of databases, specifically graph databases. With a focus on relationships and connections between data points, GraphDB allows for efficient and fast traversal of relationships in various industries such as social networks, fraud detection, recommendation engines, and network and IT operations.
GraphDB emerged in the early 2000s with companies like Neo4j pioneering the space. Founded in 2007 by Emil Eifrem, Neo4j was motivated by the need for a tool that could manage connections and relationships more effectively than traditional relational databases. Since then, GraphDB has seen significant growth in adoption across industries due to its ability to handle complex relationships easily.
Currently, GraphDB holds a notable market share within the database category, with a growing trend expected to continue in the future. As more companies recognize the value of leveraging relationships in data for enhanced insights and decision-making, the demand for GraphDB technologies is forecasted to increase. With an expanding ecosystem and continuous advancements in graph database technology, GraphDB is poised to maintain and potentially grow its market share in the coming years.