In this paper, a new Scalable Speed Stream Processing (SSS) metric that may be used to assess distributed frameworks is introduced. Researchers and practitioners can evaluate the efficacy of stream processing frameworks with the use of the SSS measure. Scalability, flexibility, interoperability, consistency, performance, efficiency, robustness, and integrity are its eight key performance indicators (KPIs). In order to ensure that the framework can manage growing data volumes, adjust to changing requirements, integrate with other systems seamlessly, maintain data accuracy, deliver high throughput, reduce resource consumption, function dependably under pressure, and protect data integrity, these key performance indicators (KPIs) address critical aspects of stream processing. The SSS measure takes use case weighting into account to indicate the relative relevance of various scenarios and is made to adjust to the ever-evolving nature of stream processing technologies. The process for allocating SSS scores to frameworks is elucidated in detail. Our survey explores the literature on stream processing frameworks and builds upon previous research by using a clear selection criterion. We examine security aspects, examining certain framework vulnerabilities and how these security features can be assessed using the recently suggested SSS metric. We also talk about real-world implementation issues such as resource limitations that arise during the deployment of these frameworks. Lastly, we suggest intriguing avenues for further stream processing framework research. For researchers, developers, and practitioners using stream processing in remote systems, this survey is an invaluable resource. It offers a thorough examination of current frameworks, their advantages and disadvantages, and the addition of the innovative SSS measure to help in informed decision-making.