Best Free Data Modeling Tools

Oracle Analytics is a complete platform for every analytics user role. AI and ML are embedded throughout the platform to accelerate productivity and power better business decisions. Choose either Oracle Analytics Cloud, our cloud native service, or our on-premises solution, Oracle Analytics Server, both of which help you avoid compromising security and governance. Oracle Analytic addresses all needs of business users from data to decision. Oracle Analytics can help you solve your business problems with built in data preparation and enrichment, no-code machine learning and industry leading data visualization.

Connect to your data warehouse, and SSO authenticates your team in seconds. Organize your business intelligence as SQL. Make changes with confidence, automated testing validates every update. Deploy models confidently and travel back in time when things go wrong. Quary connects to your sensitive data store. In order to protect it, Quary is built from the ground up with security in mind. By default, data does not leave your estate, data exchanges happen between your Quary client and your data store. Transform data together, model, test, and deploy as a team. SSO is not an extra, we include it in our base plan and even help set it up. No one should share credentials. Quary builds upon your data store's access management systems and helps you manage it. We are in the process of implementing SOC2 and have security credentials (CISSP) on the team to ensure your data stays secure.

RapidMiner is reinventing enterprise AI so that anyone has the power to positively shape the future. We’re doing this by enabling ‘data loving’ people of all skill levels, across the enterprise, to rapidly create and operate AI solutions to drive immediate business impact. We offer an end-to-end platform that unifies data prep, machine learning, and model operations with a user experience that provides depth for data scientists and simplifies complex tasks for everyone else. Our Center of Excellence methodology and the RapidMiner Academy ensures customers are successful, no matter their experience or resource levels. Simplify operations, no matter how complex models are, or how they were created. Deploy, evaluate, compare, monitor, manage and swap any model. Solve your business issues faster with sharper insights and predictive models, no one understands the business problem like you do.

Count is a fully collaborative and reactive data whiteboard. It brings together all the flexibility and creativity of a whiteboard, with the power of a SQL IDE, and the reactivity of BI notebooks. It makes it easy to break apart complex SQL queries and data models into interconnected cells to better understand the logic. Add sticky notes and visuals to help explain your work to stakeholders. Collaborate with other analysts or stakeholders as you build so you can get feedback faster. Turn any canvas into an interactive report or slideshow presentation.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

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.

Montara enables BI teams and data analysts, using SQL only, to model and transform their data easily and seamlessly and enjoy benefits such as modular code, CI/CD, versioning and automated testing and documentation. With Montara, analysts can quickly understand how changes to models impact analysis, reports and dashboards with report-level lineage and support for 3rd party visualization tools such as Tableau and Looker. Furthermore, BI teams can perform ad-hoc analysis and create reports and dashboards on Montara directly.

ZinkML is a zero-code data science platform designed to address the challenges faced by organizations in leveraging data effectively. By providing a visual and intuitive interface, it eliminates the need for extensive coding expertise, making data science accessible to a broader range of users. ZinkML streamlines the entire data science lifecycle, from data ingestion and preparation to model building, deployment, and monitoring. Users can drag-and-drop components to create complex data pipelines, explore data visually, and build predictive models without writing a single line of code. The platform also offers automated feature engineering, model selection, and hyperparameter tuning, accelerating the model development process. Moreover, ZinkML provides robust collaboration features, enabling teams to work together seamlessly on data science projects. By democratizing data science, we empower companies to extract maximum value from their data and drive better decision-making.