
Edge Delta
An analytics startup leveraging federated learning in DevOps and Security.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor | €0.0 | round |
investor investor | €0.0 | round | |
investor investor investor investor | €0.0 | round | |
* | $63.0m | Series B | |
Total Funding | 000k |
USD | 2019 | 2020 | 2021 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | 266 % | 150 % | - |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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Edge Delta is a startup that operates in the tech industry, specifically in the field of data management and analytics. The company provides a comprehensive toolbox for shaping and tiering data, with a focus on observability pipelines, logs, and metrics. Their product is designed to handle the challenges of modern application stacks and microservices architectures, which generate a significantly larger volume of logs, metrics, events, and traces compared to older systems.
Edge Delta's primary clients are businesses that need to manage and analyze large volumes of data. This includes companies with complex IT systems, such as those using modern application stacks and microservices architectures. The company's product is designed to help these businesses stream-process, filter, mask, transform, aggregate, analyze, and route their data to various destinations optimized for specific usage.
Edge Delta's business model revolves around providing a dynamic and scalable architecture that can handle massive amounts of data. The company's product is designed to enable teams to store and search data at any scale, utilizing everything from in-memory to low-cost object storage. This unique architecture allows for lower costs, better performance, and ultimate scalability.
The company makes money by selling its product to businesses. The pricing is likely based on the scale of data that a business needs to manage and analyze, with larger businesses requiring more extensive services and therefore paying more.
Keywords: Data Management, Data Analytics, Observability Pipelines, Logs, Metrics, Modern Application Stacks, Microservices Architectures, Scalable Architecture, In-Memory Storage, Object Storage.