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Best Data as a Service (DaaS) Software for Apache Kafka

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Compare the Top Data as a Service (DaaS) Software that integrates with Apache Kafka as of September 2025

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This a list of Data as a Service (DaaS) software that integrates with Apache Kafka. Use the filters on the left to add additional filters for products that have integrations with Apache Kafka. View the products that work with Apache Kafka in the table below.

What is Data as a Service (DaaS) Software for Apache Kafka?

Data as a Service (DaaS) software provides businesses with cloud-based access to structured and unstructured data, enabling them to utilize and analyze information without needing to maintain their own data infrastructure. It allows users to retrieve, integrate, and manipulate real-time data from multiple sources, often through APIs, for various applications like analytics, reporting, and decision-making. DaaS platforms ensure data accuracy, quality, and relevance by offering services like data cleansing and enrichment. This on-demand model makes data more accessible and scalable, reducing the cost and complexity of managing in-house data systems. Ultimately, DaaS empowers organizations to leverage data-driven insights efficiently and flexibly. Compare and read user reviews of the best Data as a Service (DaaS) software for Apache Kafka currently available using the table below. This list is updated regularly.

  • 1
    IBM watsonx.data
    Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more.
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  • 2
    TapData

    TapData

    TapData

    CDC-based live data platform for heterogeneous database replication, real-time data integration, or building a real-time data warehouse. By using CDC to sync production line data stored in DB2 and Oracle to the modern database, TapData enabled an AI-augmented real-time dispatch software to optimize the semiconductor production line process. The real-time data made instant decision-making in the RTD software a possibility, leading to faster turnaround times and improved yield. As one of the largest telcos, customer has many regional systems that cater to the local customers. By syncing and aggregating data from various sources and locations into a centralized data store, customers were able to build an order center where the collective orders from many applications can now be aggregated. TapData seamlessly integrates inventory data from 500+ stores, providing real-time insights into stock levels and customer preferences, enhancing supply chain efficiency.
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  • 3
    InformationGrid

    InformationGrid

    InformationGrid

    Most businesses are aware that data can help them to understand their customers better to improve processes and solve problems. We have developed a safe solution for sharing and aggregating data: InformationGrid. Get valuable insights with InformationGrid, a safe solution for sharing and aggregating data. A solution that allows hospitals and general practitioners to share data in order to prescribe better medications. Whether you have a clear idea of your data strategy or need some guidance defining this; we’re here to help you put your data strategy into action. Our SAAS platform enables you to share and aggregate data in a way that’s secure and cost-efficient. To keep time to value as short as possible we can build an application that can handle large amounts of data, and we can build it fast by using cloud-native techniques. This enables you to reap the short-term benefits of the data and get ready to start using AI to advance your business.
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