Best Artificial Intelligence Software for Apache Superset
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Compare the Top Artificial Intelligence Software that integrates with Apache Superset as of September 2025
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This a list of Artificial Intelligence software that integrates with Apache Superset. Use the filters on the left to add additional filters for products that have integrations with Apache Superset. View the products that work with Apache Superset in the table below.
What is Artificial Intelligence Software for Apache Superset?
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics. Compare and read user reviews of the best Artificial Intelligence software for Apache Superset currently available using the table below. This list is updated regularly.
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1
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.Starting Price: Free ($300 in free credits) -
2
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 -
3
PostgresML
PostgresML
PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. Return results and detect fraud faster with ML at the database layer. PostgresML abstracts the data management overhead from the ML/AI lifecycle by enabling users to run ML/LLM models directly on a Postgres database.Starting Price: $.60 per hour -
4
DataHub
DataHub
DataHub is an open source metadata platform designed to streamline data discovery, observability, and governance across diverse data ecosystems. It enables organizations to effortlessly discover trustworthy data, with experiences tailored for each person and eliminates breaking changes with detailed cross-platform and column-level lineage. DataHub builds confidence in your data by providing a comprehensive view of business, operational, and technical context, all in one place. The platform offers automated data quality checks and AI-driven anomaly detection, notifying teams when issues arise and centralizing incident tracking. With detailed lineage, documentation, and ownership information, DataHub facilitates swift issue resolution. It also automates governance programs by classifying assets as they evolve, minimizing manual work through GenAI documentation, AI-driven classification, and smart propagation. DataHub's extensible architecture supports over 70 native integrations.Starting Price: Free -
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AWS Marketplace
Amazon
AWS Marketplace is a curated digital catalog that enables customers to discover, purchase, deploy, and manage third-party software, data products, AI agents, and services directly within the AWS ecosystem. It provides access to thousands of listings across categories like security, machine learning, business applications, and DevOps tools. With flexible pricing models such as pay-as-you-go, annual subscriptions, and free trials, AWS Marketplace simplifies procurement and billing by integrating costs into a single AWS invoice. It also supports rapid deployment with pre-configured software that can be launched on AWS infrastructure. This streamlined approach allows businesses to accelerate innovation, reduce time-to-market, and maintain better control over software usage and costs. -
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Acryl Data
Acryl Data
No more data catalog ghost towns. Acryl Cloud drives fast time-to-value via Shift Left practices for data producers and an intuitive UI for data consumers. Continuously detect data quality incidents in real-time, automate anomaly detection to prevent breakages, and drive fast resolution when they do occur. Acryl Cloud supports both push-based and pull-based metadata ingestion for easy maintenance, ensuring information is trustworthy, up-to-date, and definitive. Data should be operational. Go beyond simple visibility and use automated Metadata Tests to continuously expose data insights and surface new areas for improvement. Reduce confusion and accelerate resolution with clear asset ownership, automatic detection, streamlined alerts, and time-based lineage for tracing root causes. -
7
Cake AI
Cake AI
Cake AI is a comprehensive AI infrastructure platform that enables teams to build and deploy AI applications using hundreds of pre-integrated open source components, offering complete visibility and control. It provides a curated, end-to-end selection of fully managed, best-in-class commercial and open source AI tools, with pre-built integrations across the full breadth of components needed to move an AI application into production. Cake supports dynamic autoscaling, comprehensive security measures including role-based access control and encryption, advanced monitoring, and infrastructure flexibility across various environments, including Kubernetes clusters and cloud services such as AWS. Its data layer equips teams with tools for data ingestion, transformation, and analytics, leveraging tools like Airflow, DBT, Prefect, Metabase, and Superset. For AI operations, Cake integrates with model catalogs like Hugging Face and supports modular workflows using LangChain, LlamaIndex, and more.
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