Data Asset Companies — Build or Buy Your Data Platform and Data Infrastructure

  • monitoring/metrics/log vertical like DataDog, Dynatrace, Chronosphere, Splunk, SumoLogic
  • gaming vertical like Game Analytics
  • location vertical like SafeGraph, MapBox, Esri
  • crypto vertical like Nansen and Dune Analytics
  1. Cost Scalability
  1. constants, e.g. $/license. It’s like a SaaS model, usually applicable to low data volume areas like metadata and security management, etc. In general should be ok to just swallow them.
  2. usage, e.g. $/sec. This is the most common pricing model in infra areas, e.g. compute service like AWS EC2 charges by $/core*sec (or /instance type), storage service like AWS S3 or GCP Cloud Storage charges by $/ MB or GB stored. It’s likely the cost you pass-on to users.
  3. hidden! This is the worst. Unlike above two, you don’t understand how it’s calculated and have no control. E.g. GCP BigQuery can charge by amount of data scanned. It’s bad in every single way — you can do nothing about it (e.g. barely no optimization can be done), and vendor are not motivated to optimize and reduce the amount of data scanned. If your core business highly depend on BigQuery, give it a second thoughts.
  • How soon do vendors deliver on feature and bug-fix requests?
  • How well do they provide support? e.g. docs, SLAs, response time, oncalls
  • How aligned are your roadmap with their actual roadmap? How much can you impact their roadmap and management chains?




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