Best Data Management Software for DataRobot

Find and compare the best Data Management software for DataRobot in 2025

Use the comparison tool below to compare the top Data Management software for DataRobot on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Tableau Reviews
    Top Pick
    Tableau, a comprehensive business intelligence (BI/analytics) solution, allows you to generate, analyze, and interpret business data. Tableau allows users to gather data from many sources, including spreadsheets, SQL databases and Salesforce. Tableau offers real-time visual analytics as well as an interactive dashboard that allows users to slice and dice data to make relevant insights and find new opportunities. Tableau allows users to customize the platform for different industry verticals such as communication, banking, and more.
  • 2
    COZYROC SSIS+ Suite Reviews
    COZYROC's SSIS+ suite includes 270+ Data integration adapters, ETL components and tasks for developing ETL solutions with MS SQL Server Integration Services.
  • 3
    Tableau Catalog Reviews

    Tableau Catalog

    Tableau

    $15 per month
    Tableau Catalog is a benefit for everyone. Tableau Catalog provides a complete view of the data and how it connects to the analytics in Tableau. This increases trust and discoverability for IT and business users. Tableau Catalog makes it easy to communicate changes to the data, review dashboards, or search for the right data for analysis. Tableau Catalog automatically ingests all data assets in your Tableau environment into a single central list. There is no need to create an index schedule or connect. You can quickly see all of your files, tables, and databases in one location. Migration of databases, deprecating fields or adding a column to a table can all have potential impacts on your environment. Lineage and impact analysis allows you to see not only the upstream and downstream implications of assets but also who will be affected.
  • 4
    Mona Reviews
    Mona is a flexible and intelligent monitoring platform for AI / ML. Data science teams leverage Mona’s powerful analytical engine to gain granular insights about the behavior of their data and models, and detect issues within specific segments of data, in order to reduce business risk and pinpoint areas that need improvements. Mona enables tracking custom metrics for any AI use case within any industry and easily integrates with existing tech stacks. In 2018, we ventured on a mission to empower data teams to make AI more impactful and reliable, and to raise the collective confidence of business and technology leaders in their ability to make the most out of AI. We have built the leading intelligent monitoring platform to provide data and AI teams with continuous insights to help them reduce risks, optimize their operations, and ultimately build more valuable AI systems. Enterprises in a variety of industries leverage Mona for NLP/NLU, speech, computer vision, and machine learning use cases. Mona was founded by experienced product leaders from Google and McKinsey&Co, is backed by top VCs, and is HQ in Atlanta, Georgia. In 2021, Mona was recognized by Gartner as a Cool Vendor in AI Operationalization and Engineering.
  • 5
    DataOps.live Reviews
    Create a scalable architecture that treats data products as first-class citizens. Automate and repurpose data products. Enable compliance and robust data governance. Control the costs of your data products and pipelines for Snowflake. This global pharmaceutical giant's data product teams can benefit from next-generation analytics using self-service data and analytics infrastructure that includes Snowflake and other tools that use a data mesh approach. The DataOps.live platform allows them to organize and benefit from next generation analytics. DataOps is a unique way for development teams to work together around data in order to achieve rapid results and improve customer service. Data warehousing has never been paired with agility. DataOps is able to change all of this. Governance of data assets is crucial, but it can be a barrier to agility. Dataops enables agility and increases governance. DataOps does not refer to technology; it is a way of thinking.
  • 6
    Lyftrondata Reviews
    Lyftrondata can help you build a governed lake, data warehouse or migrate from your old database to a modern cloud-based data warehouse. Lyftrondata makes it easy to create and manage all your data workloads from one platform. This includes automatically building your warehouse and pipeline. It's easy to share the data with ANSI SQL, BI/ML and analyze it instantly. You can increase the productivity of your data professionals while reducing your time to value. All data sets can be defined, categorized, and found in one place. These data sets can be shared with experts without coding and used to drive data-driven insights. This data sharing capability is ideal for companies who want to store their data once and share it with others. You can define a dataset, apply SQL transformations, or simply migrate your SQL data processing logic into any cloud data warehouse.
  • 7
    CData Python Connectors Reviews
    CData Python Connectors make it easy for Python users to connect to SaaS and Big Data, NoSQL and relational data sources. Our Python Connectors provide simple Python database interfaces to (DB-API), making them easy to connect to popular tools like Jupyter Notebook and SQLAlchemy. CData Python Connectors wrap SQL around APIs and data protocol, making it easier to access data from Python. It also allows Python users to connect more than 150 SaaS and Big Data data sources with advanced Python processing. The CData Python Connectors bridge a critical gap in Python tooling, providing consistent connectivity with data-centric interfaces for hundreds of SaaS/Cloud, NoSQL and Big Data sources. Download a 30-day free trial or learn more at: https://www.cdata.com/python/
  • 8
    TruEra Reviews
    This machine learning monitoring tool allows you to easily monitor and troubleshoot large model volumes. Data scientists can avoid false alarms and dead ends by using an unrivaled explainability accuracy and unique analyses that aren't available anywhere else. This allows them to quickly and effectively address critical problems. So that your business runs at its best, machine learning models are optimized. TruEra's explainability engine is the result of years of dedicated research and development. It is significantly more accurate that current tools. TruEra's enterprise-class AI explainability tech is unrivalled. The core diagnostic engine is built on six years of research by Carnegie Mellon University. It outperforms all competitors. The platform performs sophisticated sensitivity analyses quickly, allowing data scientists, business users, risk and compliance teams to understand how and why a model makes predictions.
  • 9
    SAP Business Data Cloud Reviews
    SAP Business Data Cloud, a fully-managed SaaS solution, unifies and governs SAP data while seamlessly connecting to third-party data. This provides line-of business leaders with the context they need to make informed decisions. It offers mission-critical products that provide access to SAP data in a contextualized and governed way, eliminating the high costs of data extraction and replication. It is a leading data platform that connects all SAP and third party data via a fully managed SaaS in collaboration with Databricks. The platform provides powerful insight applications that facilitate transformational insights in advanced analytics and planning for various lines of businesses. SAP Business Data Cloud offers unparalleled business understanding by harmonizing mission-critical data in an open data ecosystem, and leveraging a robust semantic layer.
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