
Quix
Helps developers use live data to build applications, faster.
Date | Investors | Amount | Round |
---|---|---|---|
investor investor investor investor investor investor investor | €0.0 | round | |
* | £11.0m | Series A | |
Total Funding | 000k |
USD | 2021 | 2022 | 2023 |
---|---|---|---|
Revenues | 0000 | 0000 | 0000 |
% growth | - | 67 % | 193 % |
EBITDA | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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Quix.io is a tech startup that provides a platform for developers to simplify the process of creating and deploying event streaming applications. The company operates in the cloud computing market, serving a broad range of clients, including software developers and businesses that require efficient data processing solutions.
Quix.io's platform integrates with Docker, Kafka, and Git, allowing developers to run their applications anywhere, be it on Quix's cloud, their own cloud, or on-premise. This flexibility eliminates the need for developers to manage containers or message brokers, enabling them to focus solely on writing code.
The company's business model revolves around providing a seamless integration with existing Continuous Integration/Continuous Deployment (CI/CD) workflows. This means developers can easily develop, test, and deploy their applications without worrying about setup or maintenance. Quix.io also offers an open-source library, Quix Streams, which allows developers to code in pure Python and transfer batch-processing techniques to streaming applications.
Quix.io generates revenue by charging for its platform usage. The pricing likely depends on the level of resources used, such as data throughput and CPU. The company boasts a reliable tool built by F1 engineers, promising high data velocity and volume handling with minimal downtime.
In summary, Quix.io offers a simple, powerful, and reliable solution for developers to create and deploy event streaming applications, with a focus on streamlining the process and reducing the need for complex setup and maintenance.
Keywords: Cloud Computing, Event Streaming, Application Deployment, Docker Integration, Kafka Integration, Git Integration, CI/CD Workflow, Stream Processing, Python Coding, Batch-Processing Techniques.