Find and compare the best Artificial Intelligence software for Databricks Data Intelligence Platform in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Databricks Data Intelligence Platform on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Google Cloud Platform
Google
Free ($300 in free credits) 56,320 RatingsThe Google Cloud Platform (GCP) offers a comprehensive collection of Artificial Intelligence (AI) and machine learning resources aimed at simplifying data analysis processes. It features a range of pre-trained models and APIs, including Vision AI, Natural Language, and AutoML, enabling businesses to effortlessly integrate AI into their applications without needing extensive knowledge of the subject. New users are also granted $300 in complimentary credits to experiment with, test, and implement workloads, allowing them to investigate the platform's AI functionalities and develop sophisticated machine learning applications without any upfront investment. GCP’s AI offerings are designed to work harmoniously with other services, facilitating the creation of complete machine learning workflows from data management to model deployment. Moreover, these tools are built for scalability, empowering organizations to explore AI and expand their AI-driven solutions as their requirements evolve. With these capabilities, companies can swiftly adopt AI for a variety of applications, including predictive analysis and automation. -
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Google Cloud BigQuery
Google
Free ($300 in free credits) 1,734 RatingsBigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently. -
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RunMyJobs by Redwood
RunMyJobs by Redwood
238 RatingsRunMyJobs by Redwood is the only SAP endorsed and premium-certified and the most awarded SAP-certified SaaS workload automation platform and only allowing enterprises to achieve end-to-end IT process automation and unify complex across any application, system or environment without limits and with high availability as you scale. We're the #1 job scheduling choice for SAP customers with seamless integration to S/4HANA, BTP, RISE, ECC and more while maintaining a clean core. Empower teams with seamless integration with any present and future tech stack, a low-code editor and a rich library of templates. Monitor processes in real-time with predictive SLA management and get proactive notifications via email or SMS on performance issues or delays in all your processes. Redwood team provides 24/7/365 day global support with the industry’s strongest SLAs and 15-minute response times and a proven approach to migration that secures continuous operations, including team training, on-demand learning and more. -
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Windsurf Editor
Windsurf
Free 137 RatingsWindsurf is a cutting-edge IDE designed for developers to maintain focus and productivity through AI-driven assistance. At the heart of the platform is Cascade, an intelligent agent that not only fixes bugs and errors but also anticipates potential issues before they arise. With built-in features for real-time code previews, automatic linting, and seamless integrations with popular tools like GitHub and Slack, Windsurf streamlines the development process. Developers can also benefit from memory tracking, which helps Cascade recall past work, and smart suggestions that enhance code optimization. Windsurf’s unique capabilities ensure that developers can work faster and smarter, reducing onboarding time and accelerating project delivery. -
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Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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Based on your interests, history, and role, you will receive personalized and recommended results. QuaerisAI provides near-real-time data access for all data. QuaerisAI enhances your data and document workload with AI. To increase knowledge sharing and track performance, teams can share insights and pinboards. Our advanced AI engine transforms your inquiry to a database-ready language within micro-seconds. Data is nothing without context, just like life. Our cognitive AI engine interprets search terms, interests, roles, and past history to provide ranks results that allow further exploration. You can easily add filters to search results to dig into the details and explore relevant questions.
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TensorFlow
TensorFlow
Free 2 RatingsTensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process. -
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Visual Studio Code
Microsoft
26 RatingsVSCode: A revolutionary approach to code editing. It's completely free, open-source, and compatible with all platforms. Experience more than just basic syntax highlighting and autocomplete; with IntelliSense, you gain intelligent suggestions that are based on the types of variables, definitions of functions, and imported modules. You can also debug your code directly within the editor, allowing you to launch or connect to your active applications while utilizing breakpoints, call stacks, and an interactive console for deeper insights. Collaborating with Git and other source control management (SCM) systems is simpler than ever; you can review differences, stage files, and commit changes right from within the editor itself. Easily push and pull changes from any hosted SCM service without hassle. Looking for additional capabilities? You can enhance your experience by installing extensions that introduce new languages, themes, debuggers, and connections to various services. These extensions operate in their own processes, ensuring they won't hinder your editor's performance. Discover the endless possibilities with extensions. Furthermore, with Microsoft Azure, you can efficiently deploy and host a variety of sites built with React, Angular, Vue, Node, Python, and more, while also being able to store and query both relational and document-based data, and scale effortlessly using serverless computing solutions. This powerful integration streamlines your development workflow and enhances productivity. -
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Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.
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Around 25 million engineers work across dozens of distinct functions. Engineers are using New Relic as every company is becoming a software company to gather real-time insight and trending data on the performance of their software. This allows them to be more resilient and provide exceptional customer experiences. New Relic is the only platform that offers an all-in one solution. New Relic offers customers a secure cloud for all metrics and events, powerful full-stack analytics tools, and simple, transparent pricing based on usage. New Relic also has curated the largest open source ecosystem in the industry, making it simple for engineers to get started using observability.
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Keras is an API tailored for human users rather than machines. It adheres to optimal practices for alleviating cognitive strain by providing consistent and straightforward APIs, reducing the number of necessary actions for typical tasks, and delivering clear and actionable error messages. Additionally, it boasts comprehensive documentation alongside developer guides. Keras is recognized as the most utilized deep learning framework among the top five winning teams on Kaggle, showcasing its popularity and effectiveness. By simplifying the process of conducting new experiments, Keras enables users to implement more innovative ideas at a quicker pace than their competitors, which is a crucial advantage for success. Built upon TensorFlow 2.0, Keras serves as a robust framework capable of scaling across large GPU clusters or entire TPU pods with ease. Utilizing the full deployment potential of the TensorFlow platform is not just feasible; it is remarkably straightforward. You have the ability to export Keras models to JavaScript for direct browser execution, transform them to TF Lite for use on iOS, Android, and embedded devices, and seamlessly serve Keras models through a web API. This versatility makes Keras an invaluable tool for developers looking to maximize their machine learning capabilities.
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Alation stands out as the pioneering company to introduce a data catalog to the market, significantly enhancing the ways individuals discover, comprehend, trust, utilize, and repurpose data. By leading the charge in active, non-invasive data governance, Alation effectively facilitates data democratization while ensuring compliance on a large scale, providing users with the necessary data along with clear guidance on its appropriate usage. The company addresses some of the most pressing data challenges today by merging human insights with advanced AI and machine learning technologies. Currently, over 350 enterprises rely on Alation to empower their decision-making with confidence based on data. Notable clients include American Family Insurance, Exelon, Munich Re, and Pfizer, all of whom benefit from Alation’s innovative solutions. This widespread adoption underscores the company's impact on fostering a data-driven culture across various industries.
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LangChain provides a comprehensive framework that empowers developers to build and scale intelligent applications using large language models (LLMs). By integrating data and APIs, LangChain enables context-aware applications that can perform reasoning tasks. The suite includes LangGraph, a tool for orchestrating complex workflows, and LangSmith, a platform for monitoring and optimizing LLM-driven agents. LangChain supports the full lifecycle of LLM applications, offering tools to handle everything from initial design and deployment to post-launch performance management. Its flexibility makes it an ideal solution for businesses looking to enhance their applications with AI-powered reasoning and automation.
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Ray
Anyscale
FreeYou can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution. -
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Dagster
Dagster Labs
$0Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. -
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LangGraph
LangChain
FreeAchieve enhanced precision and control through LangGraph, enabling the creation of agents capable of efficiently managing intricate tasks. The LangGraph Platform facilitates the development and scaling of agent-driven applications. With its adaptable framework, LangGraph accommodates various control mechanisms, including single-agent, multi-agent, hierarchical, and sequential flows, effectively addressing intricate real-world challenges. Reliability is guaranteed by the straightforward integration of moderation and quality loops, which ensure agents remain focused on their objectives. Additionally, LangGraph Platform allows you to create templates for your cognitive architecture, making it simple to configure tools, prompts, and models using LangGraph Platform Assistants. Featuring inherent statefulness, LangGraph agents work in tandem with humans by drafting work for review and awaiting approval prior to executing actions. Users can easily monitor the agent’s decisions, and the "time-travel" feature enables rolling back to revisit and amend previous actions for a more accurate outcome. This flexibility ensures that the agents not only perform tasks effectively but also adapt to changing requirements and feedback. -
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Immuta
Immuta
Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals. -
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Toucan
Toucan
Toucan, a customer-facing platform for analytics, empowers organizations to drive engagement and provide the best possible end-user experience. Toucan makes it simple, from data connections to the distribution and sharing of insights wherever they are needed. Toucan analytics are 3x more popular than the industry average. With hundreds of connectors, users can connect to any cloud-based or stored data. Data readiness features make data preparation easy for business people. They can perform tasks that would normally require an expert. Visualization can be described as "data storytelling", where every chart is accompanied with context, collaboration and annotation to help users understand the "why" behind their data. Finally, deployment and management are easy with one-touch deployment, from staging to production, easy embedding and publishing to any device. -
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Skypoint AI Platform
SkyPoint Cloud
$24,995/month The Skypoint AI Platform serves as a robust data and artificial intelligence solution tailored for sectors that are heavily regulated, such as healthcare, finance, and government, facilitating smooth data integration alongside sophisticated AI-driven automation. Constructed on a flexible data lakehouse architecture, this platform merges both structured and unstructured data into a unified source of truth while prioritizing governance, security, and compliance measures. With comprehensive AI capabilities, it encompasses business intelligence, AI agents, and collaborative tools, empowering organizations to optimize their operations and enhance decision-making processes. By utilizing compound AI systems that incorporate specialized language models, retrieval mechanisms, and external resources, Skypoint provides customized, intelligent solutions aimed at addressing specific industry challenges. Furthermore, its innovative approach ensures that organizations can adapt to evolving regulatory requirements while maximizing efficiency and insights. -
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Prophecy
Prophecy
$299 per monthProphecy expands accessibility for a wider range of users, including visual ETL developers and data analysts, by allowing them to easily create pipelines through a user-friendly point-and-click interface combined with a few SQL expressions. While utilizing the Low-Code designer to construct workflows, you simultaneously generate high-quality, easily readable code for Spark and Airflow, which is then seamlessly integrated into your Git repository. The platform comes equipped with a gem builder, enabling rapid development and deployment of custom frameworks, such as those for data quality, encryption, and additional sources and targets that enhance the existing capabilities. Furthermore, Prophecy ensures that best practices and essential infrastructure are offered as managed services, simplifying your daily operations and overall experience. With Prophecy, you can achieve high-performance workflows that leverage the cloud's scalability and performance capabilities, ensuring that your projects run efficiently and effectively. This powerful combination of features makes it an invaluable tool for modern data workflows. -
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Flyte
Union.ai
FreeFlyte is a robust platform designed for automating intricate, mission-critical data and machine learning workflows at scale. It simplifies the creation of concurrent, scalable, and maintainable workflows, making it an essential tool for data processing and machine learning applications. Companies like Lyft, Spotify, and Freenome have adopted Flyte for their production needs. At Lyft, Flyte has been a cornerstone for model training and data processes for more than four years, establishing itself as the go-to platform for various teams including pricing, locations, ETA, mapping, and autonomous vehicles. Notably, Flyte oversees more than 10,000 unique workflows at Lyft alone, culminating in over 1,000,000 executions each month, along with 20 million tasks and 40 million container instances. Its reliability has been proven in high-demand environments such as those at Lyft and Spotify, among others. As an entirely open-source initiative licensed under Apache 2.0 and backed by the Linux Foundation, it is governed by a committee representing multiple industries. Although YAML configurations can introduce complexity and potential errors in machine learning and data workflows, Flyte aims to alleviate these challenges effectively. This makes Flyte not only a powerful tool but also a user-friendly option for teams looking to streamline their data operations. -
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Spark NLP
John Snow Labs
FreeDiscover the transformative capabilities of large language models as they redefine Natural Language Processing (NLP) through Spark NLP, an open-source library that empowers users with scalable LLMs. The complete codebase is accessible under the Apache 2.0 license, featuring pre-trained models and comprehensive pipelines. As the sole NLP library designed specifically for Apache Spark, it stands out as the most widely adopted solution in enterprise settings. Spark ML encompasses a variety of machine learning applications that leverage two primary components: estimators and transformers. Estimators possess a method that ensures data is secured and trained for specific applications, while transformers typically result from the fitting process, enabling modifications to the target dataset. These essential components are intricately integrated within Spark NLP, facilitating seamless functionality. Pipelines serve as a powerful mechanism that unites multiple estimators and transformers into a cohesive workflow, enabling a series of interconnected transformations throughout the machine-learning process. This integration not only enhances the efficiency of NLP tasks but also simplifies the overall development experience. -
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scikit-learn
scikit-learn
FreeScikit-learn offers a user-friendly and effective suite of tools for predictive data analysis, making it an indispensable resource for those in the field. This powerful, open-source machine learning library is built for the Python programming language and aims to simplify the process of data analysis and modeling. Drawing from established scientific libraries like NumPy, SciPy, and Matplotlib, Scikit-learn presents a diverse array of both supervised and unsupervised learning algorithms, positioning itself as a crucial asset for data scientists, machine learning developers, and researchers alike. Its structure is designed to be both consistent and adaptable, allowing users to mix and match different components to meet their unique requirements. This modularity empowers users to create intricate workflows, streamline repetitive processes, and effectively incorporate Scikit-learn into expansive machine learning projects. Furthermore, the library prioritizes interoperability, ensuring seamless compatibility with other Python libraries, which greatly enhances data processing capabilities and overall efficiency. As a result, Scikit-learn stands out as a go-to toolkit for anyone looking to delve into the world of machine learning. -
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Taipy
Taipy
$360 per monthTransforming basic prototypes into fully functional web applications is now a swift process. You no longer need to make sacrifices regarding performance, customization, or scalability. Taipy boosts performance through effective caching of graphical events, ensuring that graphical components are rendered only when necessary, based on user interactions. With Taipy's integrated decimator for charts, managing extensive datasets becomes a breeze, as it smartly minimizes data points to conserve time and memory while preserving the fundamental structure of your data. This alleviates the challenges associated with sluggish performance and high memory demands that arise from processing every single data point. When dealing with large datasets, the user experience and data analysis can become overly complex. Taipy Studio simplifies these situations with its robust VS Code extension, offering a user-friendly graphical editor. It allows you to schedule method invocations at specific intervals, providing flexibility in your workflows. Additionally, you can choose from a variety of pre-defined themes or craft your own, making customization both simple and enjoyable. -
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Arize Phoenix
Arize AI
FreePhoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.