Best Data Management Software for Dataiku
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Compare the Top Data Management Software that integrates with Dataiku as of September 2025
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This a list of Data Management software that integrates with Dataiku. Use the filters on the left to add additional filters for products that have integrations with Dataiku. View the products that work with Dataiku in the table below.
What is Data Management Software for Dataiku?
Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security. Compare and read user reviews of the best Data Management software for Dataiku currently available using the table below. This list is updated regularly.
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1
UiPath
UiPath
Become a fully automated enterprise™ with the UiPath Platform. A fully automated enterprise is a digitally transformed enterprise. Create business resilience, speed, and agility, and unburden people from mundane work with the automation platform that has it all. Use the data from your business applications (like ERP and CRM) to give you a detailed understanding of complex business processes. You’ll know what to automate and how to do it best—and be able to prove impact, too. UiPath is an innovative Robotic Process Automation (RPA) and process mining enterprise platform that empowers organizations to efficiently automate business processes, helping companies become digital businesses faster and gain a valuable advantage on their path to AI. Scalable, extensible, and sustainable, UiPath lets users design their own workflows visually--no scripting or coding required. The platform also features full auditing capabilities, advanced analytical reporting, and customizable dashboards.Starting Price: $3990.00/year/user -
2
Tableau
Salesforce
Tableau, now enhanced with AI-powered capabilities and integrated with Salesforce, is an advanced analytics platform that helps businesses turn data into actionable insights. With Tableau Next, users can unlock the full potential of their data by accessing trusted AI-driven analytics. Whether deployed in the cloud, on-premises, or natively within Salesforce CRM, Tableau enables seamless data integration, powerful visualizations, and collaboration. The platform is designed to support organizations of all sizes in making data-driven decisions, while fostering a Data Culture through easy-to-use, intuitive tools for analysts, business leaders, IT leaders, and developers alike.Starting Price: $75/user/month -
3
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2 compute/month -
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Apache Hive
Apache Software Foundation
The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API. -
5
Toucan
Toucan
Toucan is a customer-facing analytics platform that empowers organizations to drive engagement with the best end-user experience. From data connections to the distribution of insights anywhere they're needed, Toucan makes it easy. As a result, Toucan analytics are used 3x more than the industry average. Users can connect to any data, cloud-based or other, streaming or stored, with hundreds of connectors. Preparation of data is equally simple with data readiness features that lets business people perform tasks that would ordinarily require an expert. Visualization takes the form of “data storytelling” where every chart is accompanied by context, collaboration, and annotation so that users understand the “why” and not just the “what” of their data. Finally, deployment and management are made easy with one-touch deployment from staging to production, easy embedding, and publishing to any device. -
6
Taipy
Taipy
From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape. Struggle with sluggish performance and excessive memory usage, as every data point demands processing. Large datasets become cumbersome, complicating the user experience and data analysis. Scenarios are made easy with Taipy Studio. A powerful VS Code extension that unlocks a convenient graphical editor. Get your methods invoked at a certain time or intervals. Enjoy a variety of predefined themes or build your own.Starting Price: $360 per month -
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OpenText Analytics Database is a high-performance, scalable analytics platform that enables organizations to analyze massive data sets quickly and cost-effectively. It supports real-time analytics and in-database machine learning to deliver actionable business insights. The platform can be deployed flexibly across hybrid, multi-cloud, and on-premises environments to optimize infrastructure and reduce total cost of ownership. Its massively parallel processing (MPP) architecture handles complex queries efficiently, regardless of data size. OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
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8
DataOps.live
DataOps.live
DataOps.live, the Data Products company, delivers productivity and governance breakthroughs for data developers and teams through environment automation, pipeline orchestration, continuous testing and unified observability. We bring agile DevOps automation and a powerful unified cloud Developer Experience (DX) to modern cloud data platforms like Snowflake. DataOps.live, a global cloud-native company, is used by Global 2000 enterprises including Roche Diagnostics and OneWeb to deliver 1000s of Data Product releases per month with the speed and governance the business demands. -
9
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. -
10
Okera
Okera
Okera, the Universal Data Authorization company, helps modern, data-driven enterprises accelerate innovation, minimize data security risks, and demonstrate regulatory compliance. The Okera Dynamic Access Platform automatically enforces universal fine-grained access control policies. This allows employees, customers, and partners to use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives. Okera began development in 2016 and now dynamically authorizes access to hundreds of petabytes of sensitive data for the world’s most demanding F100 companies and regulatory agencies. The company is headquartered in San Francisco. -
11
HPE Ezmeral
Hewlett Packard Enterprise
Run, manage, control and secure the apps, data and IT that run your business, from edge to cloud. HPE Ezmeral advances digital transformation initiatives by shifting time and resources from IT operations to innovations. Modernize your apps. Simplify your Ops. And harness data to go from insights to impact. Accelerate time-to-value by deploying Kubernetes at scale with integrated persistent data storage for app modernization on bare metal or VMs, in your data center, on any cloud or at the edge. Harness data and get insights faster by operationalizing the end-to-end process to build data pipelines. Bring DevOps agility to the machine learning lifecycle, and deliver a unified data fabric. Boost efficiency and agility in IT Ops with automation and advanced artificial intelligence. And provide security and control to eliminate risk and reduce costs. HPE Ezmeral Container Platform provides an enterprise-grade platform to deploy Kubernetes at scale for a wide range of use cases. -
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Pantomath
Pantomath
Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage.
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