Best Data Lake Solutions for ActiveBatch Workload Automation
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Compare the Top Data Lake Solutions that integrate with ActiveBatch Workload Automation as of October 2025
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This a list of Data Lake solutions 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 Lake Solutions for ActiveBatch Workload Automation?
Data lake solutions are platforms designed to store and manage large volumes of structured, semi-structured, and unstructured data in its raw form. Unlike traditional databases, data lakes allow businesses to store data in its native format without the need for preprocessing or schema definition upfront. These solutions provide scalability, flexibility, and high-performance capabilities for handling vast amounts of diverse data, including logs, multimedia, social media posts, sensor data, and more. Data lake solutions typically offer tools for data ingestion, storage, management, analytics, and governance, making them essential for big data analytics, machine learning, and real-time data processing. By consolidating data from various sources, data lakes help organizations gain deeper insights and drive data-driven decision-making. Compare and read user reviews of the best Data Lake solutions for ActiveBatch Workload Automation currently available using the table below. This list is updated regularly.
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Teradata VantageCloud
Teradata
Teradata VantageCloud is a cloud-native platform that combines the scalability of a data lake with the performance of a data warehouse. It enables organizations to ingest, store, and analyze structured and semi-structured data across multi-cloud and hybrid environments. VantageCloud supports open data formats and integrates with modern analytics and AI/ML tools, allowing users to extract insights from raw data without complex migrations. Its unified architecture provides governance, security, and real-time access, making it ideal for enterprises seeking a flexible, intelligent data lake foundation for advanced analytics. -
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Hadoop
Apache Software Foundation
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page. Apache Hadoop 3.3.4 incorporates a number of significant enhancements over the previous major release line (hadoop-3.2).
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