Best Data Modeling Tools for Activeeon ProActive
View:
Compare the Top Data Modeling Tools that integrate with Activeeon ProActive as of October 2025
Sort By:
This a list of Data Modeling tools that integrate with Activeeon ProActive. Use the filters on the left to add additional filters for products that have integrations with Activeeon ProActive. View the products that work with Activeeon ProActive in the table below.
What are Data Modeling Tools for Activeeon ProActive?
Data modeling tools are software tools that help organizations design, visualize, and manage data structures, relationships, and flows within databases and data systems. These tools enable data architects and engineers to create conceptual, logical, and physical data models that ensure data is organized in a way that is efficient, scalable, and aligned with business needs. Data modeling tools also provide features for defining data attributes, establishing relationships between entities, and ensuring data integrity through constraints. By automating aspects of the design and validation process, these tools help prevent errors and inconsistencies in database structures. They are essential for businesses that need to manage complex datasets and maintain data consistency across multiple platforms. Compare and read user reviews of the best Data Modeling tools for Activeeon ProActive currently available using the table below. This list is updated regularly.
-
1
Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
2
A data design solution that enables you to discover, model, relate, standardize and integrate diverse and distributed data assets throughout the enterprise. IBM InfoSphere® Data Architect is a collaborative enterprise data modeling and design solution that can simplify and accelerate integration design for business intelligence, master data management and service-oriented architecture initiatives. InfoSphere Data Architect enables you to work with users at every step of the data design process, from project management to application design to data design. The tool helps to align processes, services, applications and data architectures. Simple warehouse design, dimensional modeling and change management tasks help reduce development time and give you the tools to design and manage warehouses from an enterprise logical model. Time stamped, column-organized tables offer a better understanding of data assets to help increase efficiency and reduce time to market.
- Previous
- You're on page 1
- Next