DeltaStream
DeltaStream is a unified serverless stream processing platform that integrates with streaming storage services. Think about it as the compute layer on top of your streaming storage. It provides functionalities of streaming analytics(Stream processing) and streaming databases along with additional features to provide a complete platform to manage, process, secure and share streaming data.
DeltaStream provides a SQL based interface where you can easily create stream processing applications such as streaming pipelines, materialized views, microservices and many more. It has a pluggable processing engine and currently uses Apache Flink as its primary stream processing engine. DeltaStream is more than just a query processing layer on top of Kafka or Kinesis. It brings relational database concepts to the data streaming world, including namespacing and role based access control enabling you to securely access, process and share your streaming data regardless of where they are stored.
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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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Condense
Condense, built by Zeliot, is a real-time data streaming platform that combines fully managed Apache Kafka with everything needed to build and run event-driven applications on top of it. Instead of stitching together Kafka, stream processors, connectors, and observability tools, teams get a single platform: managed Kafka clusters, pre-built and custom transforms, deployment pipelines, and monitoring, all running inside their own cloud account (AWS, Azure, or GCP) so data never leaves their environment.
Condense includes Vapr, an autonomous AI supervisor that coordinates specialist agents for Kafka, Kubernetes, Grafana, and coding tasks, cutting the operational load of running streaming infrastructure. Condense is proven in high-throughput production environments, powering connected vehicle platforms, automotive OEM telematics, EV fleets, logistics operations, Travel & Hospitality, Healthcare, Fintech, etc that process billions of events per day.
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Informatica Data Engineering Streaming
AI-powered Informatica Data Engineering Streaming enables data engineers to ingest, process, and analyze real-time streaming data for actionable insights. Advanced serverless deployment option with integrated metering dashboard cuts admin overhead. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC). Ingest thousands of databases and millions of files, and streaming events. Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics. Find and inventory all data assets throughout your organization. Intelligently discover and prepare trusted data for advanced analytics and AI/ML projects.
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