Best Real-Time Data Streaming Tools for Redis

Find and compare the best Real-Time Data Streaming tools for Redis in 2025

Use the comparison tool below to compare the top Real-Time Data Streaming tools for Redis on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Aiven Reviews

    Aiven

    Aiven

    $200.00 per month
    Aiven manages your open-source data infrastructure in the cloud so that you don't have. Developers can do what is best for them: create applications. We do what we love: manage cloud data infrastructure. All solutions are open-source. You can also freely transfer data between clouds and create multi-cloud environments. You will know exactly what you will be paying and why. We combine storage, networking, and basic support costs. We will keep your Aiven software up and running. We will be there to help you if there is ever an issue. In 10 minutes, you can deploy a service on Aiven. 1. Register now - No credit card information required 2. Select your open-source service and choose the region and cloud to deploy to it 3. Select your plan and get $300 in credit 4. Click "Create service" to configure your data sources
  • 2
    Streamkap Reviews

    Streamkap

    Streamkap

    $600 per month
    Streamkap is a modern streaming ETL platform built on top of Apache Kafka and Flink, designed to replace batch ETL with streaming in minutes. It enables data movement with sub-second latency using change data capture for minimal impact on source databases and real-time updates. The platform offers dozens of pre-built, no-code source connectors, automated schema drift handling, updates, data normalization, and high-performance CDC for efficient and low-impact data movement. Streaming transformations power faster, cheaper, and richer data pipelines, supporting Python and SQL transformations for common use cases like hashing, masking, aggregations, joins, and unnesting JSON. Streamkap allows users to connect data sources and move data to target destinations with an automated, reliable, and scalable data movement platform. It supports a broad range of event and database sources.
  • 3
    TapData Reviews
    CDC-based live-data platform for heterogeneous data replication, real-time integration, or building a data warehouse in real-time. TapData used CDC to sync data from the production line stored in DB2 or Oracle to the modern database. This enabled AI-augmented real time dispatch software to optimize semiconductor production line processes. Real-time data enabled instant decision-making within the RTD software, resulting in faster turnaround times and increased yield. Customer, as one of the largest telcos in the world, has many regional systems to cater to local customers. Customers were able build an order center by syncing data from different sources and locations and aggregating it into a central data store. TapData integrates inventory data across 500+ stores to provide real-time insights on stock levels and customer preferences. This enhances supply chain efficiency.
  • 4
    Arroyo Reviews
    Scale from 0 to millions of events every second. Arroyo is shipped as a single compact binary. Run locally on MacOS, Linux or Kubernetes for development and deploy to production using Docker or Kubernetes. Arroyo is an entirely new stream processing engine that was built from the ground-up to make real time easier than batch. Arroyo has been designed so that anyone with SQL knowledge can build reliable, efficient and correct streaming pipelines. Data scientists and engineers are able to build real-time dashboards, models, and applications from end-to-end without the need for a separate streaming expert team. SQL allows you to transform, filter, aggregate and join data streams with results that are sub-second. Your streaming pipelines should not page someone because Kubernetes rescheduled your pods. Arroyo can run in a modern, elastic cloud environment, from simple container runtimes such as Fargate, to large, distributed deployments using the Kubernetes logo.
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