Best Streaming Analytics Platforms for Google Cloud Datastream

Compare the Top Streaming Analytics Platforms that integrate with Google Cloud Datastream as of July 2025

This a list of Streaming Analytics platforms that integrate with Google Cloud Datastream. Use the filters on the left to add additional filters for products that have integrations with Google Cloud Datastream. View the products that work with Google Cloud Datastream in the table below.

What are Streaming Analytics Platforms for Google Cloud Datastream?

Streaming analytics platforms are software solutions that enable real-time processing and analysis of data as it is generated or streamed from various sources such as IoT devices, sensors, social media, and transactional systems. These platforms allow businesses to gain immediate insights from continuous data streams, enabling them to make faster decisions, detect anomalies, and optimize operations in real-time. Key features of streaming analytics platforms include data ingestion, real-time event processing, pattern recognition, and advanced analytics like predictive modeling and machine learning integration. They are commonly used in applications such as fraud detection, customer behavior analysis, network monitoring, and supply chain optimization. Compare and read user reviews of the best Streaming Analytics platforms for Google Cloud Datastream currently available using the table below. This list is updated regularly.

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    Google Cloud Dataflow
    Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization.
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