Best Event Stream Processing Software of 2024

Find and compare the best Event Stream Processing software in 2024

Use the comparison tool below to compare the top Event Stream Processing software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Pathway Reviews
    Pathway is a data-processing framework for Python & ML/AI Developers. It allows rapid prototyping in notebooks and containerized deployment at scale. Connect multiple data sources such as Kafka, S3, local and cloud files, and databases. The Pathway engine performs a continuous computation as input data changes. This ensures that your outputs will always be up-to-date. Pathway runs the fastest Rust-based runtime available to run your Python data pipeline. It allows you to integrate seamlessly with Python machine-learning libraries, use LLMs and call into synchronous or asynchronous APIs. Take on diverse tasks such as time series analysis, anomaly detecting with alerting, Graph exploration, and others. All this is done within a flexible, intuitive Python framework. Pathway is an scalable framework that combines in-memory storage and stream data processing with an analytics engine.
  • 2
    Google Cloud Dataflow Reviews
    Unified stream and batch data processing that is serverless, fast, cost-effective, and low-cost. Fully managed data processing service. Automated provisioning of and management of processing resource. Horizontal autoscaling worker resources to maximize resource use Apache Beam SDK is an open-source platform for community-driven innovation. Reliable, consistent processing that works exactly once. Streaming data analytics at lightning speed Dataflow allows for faster, simpler streaming data pipeline development and lower data latency. Dataflow's serverless approach eliminates the operational overhead associated with data engineering workloads. Dataflow allows teams to concentrate on programming and not managing server clusters. Dataflow's serverless approach eliminates operational overhead from data engineering workloads, allowing teams to concentrate on programming and not managing server clusters. Dataflow automates provisioning, management, and utilization of processing resources to minimize latency.
  • 3
    Cloudera DataFlow Reviews
    You can manage your data from the edge to the cloud with a simple, no-code approach to creating sophisticated streaming applications.
  • 4
    Radicalbit Reviews
    Radicalbit Natural Analytics is a DataOps platform that enables Streaming Data Integration as well as Real-time Advanced Analytics. The easiest way to get data to the right people at the right time is the best. RNA offers users the latest technologies in self-service mode. It allows for real-time data processing and takes advantage of Artificial Intelligence solutions to extract value from data. It automates data analysis, which can be laborious. It also helps to communicate important insights and findings in easily understandable formats. You can respond quickly and effectively with real-time situational awareness. You can achieve new levels of efficiency, optimization, and ensure collaboration between siloed groups. You can monitor and manage your models from one central view. Then, deploy your evolving models in seconds. No downtime.
  • 5
    Precisely Connect Reviews
    Integrate legacy systems seamlessly into the next-gen cloud or data platforms with one solution. Connect allows you to take control of your data, from mainframe to cloud. Integrate data via batch and real-time input for advanced analytics, comprehensive machinelearning and seamless data migration. Connect draws on the decades of experience Precisely has gained as a leader in mainframe sorting and IBM i data availability security. This allows the company to be a leader in the field of complex data access and integration. Access to all enterprise data is possible for critical business projects. Connect supports a wide range targets and sources for all your ELT/CDC needs.