Best Data Integration Tools for ActiveBatch Workload Automation

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Compare the Top Data Integration Tools that integrate with ActiveBatch Workload Automation as of October 2025

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This a list of Data Integration tools that integrate with ActiveBatch Workload Automation. Use the filters on the left to add additional filters for products that have integrations with ActiveBatch Workload Automation. View the products that work with ActiveBatch Workload Automation in the table below.

What are Data Integration Tools for ActiveBatch Workload Automation?

Data integration tools help organizations combine data from multiple sources into a unified, coherent system for analysis and decision-making. These tools streamline the process of gathering, transforming, and loading data (ETL) from various databases, applications, and cloud services, ensuring consistent data across platforms. They provide features like data cleansing, mapping, and real-time synchronization, ensuring data accuracy and reliability. With automated workflows and connectors, data integration tools reduce manual effort and eliminate data silos, improving operational efficiency. Ultimately, they enable businesses to make better, data-driven decisions by providing a comprehensive view of their information landscape. Compare and read user reviews of the best Data Integration tools for ActiveBatch Workload Automation currently available using the table below. This list is updated regularly.

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    Informatica Cloud Data Integration
    Ingest data with high-performance ETL, mass ingestion, or change data capture. Integrate data on any cloud, with ETL, ELT, Spark, or with a fully managed serverless option. Integrate any application, whether it’s on-premises or SaaS. Process petabytes of data up to 72x faster within your cloud ecosystem. See how you can use Informatica’s Cloud Data Integration to quickly start building high-performance data pipelines to meet any data integration need. Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics. Integrate apps & data in real time with intelligent business processes that span cloud & on-premises sources. Easily integrate message- and event-based systems, queues, and topics with support for top tools. Connect to a wide range of applications (and any API) and integrate in real-time with APIs, messaging, and pub/sub support—no coding required.
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  • 2
    Informatica PowerCenter
    Embrace agility with the market-leading scalable, high-performance enterprise data integration platform. Support the entire data integration lifecycle, from jumpstarting the first project to ensuring successful mission-critical enterprise deployments. PowerCenter, the metadata-driven data integration platform, jumpstarts and accelerates data integration projects in order to deliver data to the business more quickly than manual hand coding. Developers and analysts collaborate, rapidly prototype, iterate, analyze, validate, and deploy projects in days instead of months. PowerCenter serves as the foundation for your data integration investments. Use machine learning to efficiently monitor and manage your PowerCenter deployments across domains and locations.
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  • 3
    IBM DataStage
    Accelerate AI innovation with cloud-native data integration on IBM Cloud Pak for data. AI-powered data integration, anywhere. Your AI and analytics are only as good as the data that fuels them. With a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data delivers that high-quality data. It combines industry-leading data integration with DataOps, governance and analytics on a single data and AI platform. Automation accelerates administrative tasks to help reduce TCO. AI-based design accelerators and out-of-the-box integration with DataOps and data science services speed AI innovation. Parallelism and multicloud integration let you deliver trusted data at scale across hybrid or multicloud environments. Manage the data and analytics lifecycle on the IBM Cloud Pak for Data platform. Services include data science, event messaging, data virtualization and data warehousing. Parallel engine and automated load balancing.
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