Backona AI vs Starburst Data: Complete Platform Comparison Guide 2025

In today’s fast-evolving data landscape, enterprises face increasing challenges managing distributed data, modernizing legacy analytics, and scaling AI initiatives. This comprehensive 2025 comparison guide explores two leading platforms—Backona AI and Starburst Data—that address these challenges from different angles. We analyze their AI-driven intelligence, data unification capabilities, scalability, automation, pricing, and target audiences to help you make an informed choice.

Quick Answer:
If your priority is predictive analytics and cross-department automation that delivers actionable business insights, Backona AI is your best bet. Conversely, for enterprises seeking unified, compliant access to distributed data environments through a high-performance data lakehouse and federated queries, Starburst Data offers an innovative data platform designed for complex data infrastructures.

Introduction

As enterprises increasingly rely on multiple data sources spanning data lakes, data warehouses, on-premises systems, and cloud environments, the need for seamless data access and intelligent activation of that data has never been greater. The challenge is twofold: first, to unify and govern distributed data effectively; second, to extract meaningful insights through AI-driven analytics and automation.

Both platforms reflect a broader trend of enterprises aggressively driving AI adoption and investing in artificial intelligence to gain a competitive edge, leveraging these technologies to accelerate innovation and business growth.

Backona AI vs Starburst Data represents a comparison of two distinct approaches to these problems. Backona AI focuses on turning marketing, sales, and operational data into predictive, automated insights that empower business users. In contrast, Starburst Data provides a robust data lakehouse architecture with a powerful analytics query engine that enables enterprises to query data across multiple sources without moving it, simplifying access while maintaining strict access control and governance.

By the end of this guide, you’ll understand why Backona AI delivers superior ROI for organizations seeking predictive automation and workflow intelligence, while Starburst excels in managing complex, hybrid data architectures for enterprise-scale analytics.

Introduction to Data Platforms

Modern organizations are increasingly challenged by the complexity of managing distributed data across cloud, on-premises, and multi-region environments. Data platforms have emerged as the innovative solution to unify access to this fragmented landscape, enabling fast, federated queries across a wide array of data sources—including MongoDB, PostgreSQL, Salesforce, and S3.

Starburst simplifies data access by delivering an open, hybrid data lakehouse architecture that empowers both data producers and business users. This approach not only accelerates the development of AI-ready applications but also ensures compliant data access for advanced use cases like retrieval augmented generation (RAG) and agentic workflows. As a result, organizations can scale their AI initiatives with confidence, knowing that sensitive data remains secure and accessible only to authorized users.

By leveraging Starburst, enterprises can build modern data products, modernize legacy analytics systems, and unlock instant insights from their data—no matter where it resides. The platform fosters seamless collaboration between data producers, business users, and security teams, making it a key enabler for organizations aiming to drive innovation and meet evolving business needs. Whether operating on premises or in the cloud, Starburst’s hybrid data lakehouse provides the flexibility and scalability required to support enterprise-level AI initiatives and deliver real business value.

What is Backona AI?

Backona AI is an AI-powered predictive analytics and automation platform designed to unify data from multiple business domains—marketing, sales, finance, and HR—into a single, accessible layer. It enables business users to interact with their data naturally, without the need for coding or complex dashboards, delivering clear, actionable answers.

Backona AI’s strength lies in its ability to automate insights, reporting, and forecasting, helping businesses optimize performance in real time. Its AI-driven models provide predictive forecasting, anomaly detection, and cross-department workflow automation, making it a key enabler for organizations scaling AI initiatives without large analytics teams. The platform’s architecture is built to support scalable AI models and facilitate AI ready application development, ensuring business users can seamlessly develop, deploy, and integrate advanced AI solutions as part of their data strategy.

Key Highlights of Backona AI:

• Predictive forecasting and anomaly detection that anticipate future trends.
• AI-driven marketing and operational automation to streamline workflows.
• Unified analytics across various business functions for comprehensive insights.
• Integration with over 250 data sources including CRMs, ERPs, and ad platforms.
• Designed for business users seeking no-code access to enterprise data.

Ideal for: Businesses and enterprises that want to leverage AI-driven predictive intelligence and automate decision-making processes across departments.

What is Starburst Data?

Starburst Data is a cutting-edge data lakehouse platform built on the open-source Trino query engine. It empowers enterprises to unify distributed data residing in data lakes, data warehouses, and legacy systems—whether on-premises, cloud, or hybrid environments. Starburst simplifies data access by enabling federated queries that retrieve data across multiple sources without the need for costly data movement. Starburst empowers organizations to unlock new AI-driven applications and workflows by enabling secure, governed, and scalable analytics across industries.

Starburst’s platform emphasizes compliant data access with robust access control and governance features, making it a favorite among enterprises with stringent security requirements. Starburst is specifically designed to provide compliant data access for AI-driven applications. Starburst's AI strategy reflects its close collaboration with enterprise clients to support advanced AI initiatives, such as data lakehouse development, AI-driven threat detection, and real-time compliance solutions. The Starburst Agent introduces natural language querying capabilities, allowing data producers and business users to convert everyday questions into SQL queries seamlessly, and enables AI agents to interact with governed data sources for smarter, more efficient workflows.

Key Highlights of Starburst Data:

• Unified data access across multiple, hybrid data sources.
• High-performance, distributed query engine for fast analytics.
• Enterprise-grade governance with fine-grained access controls.
• Support for AI-ready data pipelines and agentic workflows.
• Open architecture supporting Apache Iceberg, Delta Lake, and other modern data formats.

Ideal for: Large enterprises, data engineering teams, and AI teams managing complex, multi-cloud or hybrid data infrastructure.

Data Foundation

A strong data foundation is the cornerstone of any successful analytics or AI strategy. This foundation is built on three essential pillars: reliable data access, rigorous data quality checks, and robust data governance. Starburst’s innovative data platform excels in all three areas, providing organizations with the tools they need to harness the full potential of their data.

With Starburst, data access is streamlined across multiple data sources, allowing both data producers and business users to retrieve and analyze information quickly and securely. The platform’s built-in data quality checks ensure that only accurate, high-quality data is used for analysis, reducing the risk of errors and duplicate data. Comprehensive access control and PII tagging further enhance data governance, ensuring that sensitive information is protected and compliant with regulatory requirements.

Starburst’s data architecture is designed to support AI-ready workflows, including advanced features like vector search, which enables instant insights and accelerates AI-driven decision-making. The platform’s self-service capabilities empower users at every level of the organization to access and analyze data without relying on IT, fostering a culture of data-driven innovation.

For enterprise-level organizations—including global financial institutions and multinational investment banks—Starburst provides the scalability, security, and compliance needed to modernize legacy systems and drive AI initiatives forward. By delivering a unified, high-quality data layer, Starburst enables organizations to meet their business needs, achieve instant insights, and stay ahead in a rapidly evolving data landscape.

Feature Comparison Table

Pricing Comparison (2025)

Both platforms have seen growth in net new customers as organizations seek scalable AI and data solutions.

Pros & Cons

Onboarding & Ease of Use

Backona AI features an AI onboarding assistant that simplifies integration of multiple data sources and automatically builds predictive dashboards. This approach enables organizations to access data faster and accelerate time to value, allowing for faster deployment for business teams eager to unlock insights without waiting for IT.

Starburst Data requires configuration of data connectors, governance policies, and query engines, typically handled by specialized engineering teams. While this setup offers deep control over data infrastructure and compliant data access, it demands more technical expertise.

Summary: Backona AI is faster and more user-friendly for business users, whereas Starburst empowers technical teams with comprehensive control over distributed data environments.

Integrations, Ecosystem, and Data Access

• Backona AI: Supports over 250 integrations across CRMs, ERPs, marketing platforms, and finance systems, connecting at the business intelligence layer to provide unified insights.
• Starburst Data: Offers 50+ connectors to databases, data lakes, data warehouses, and legacy systems, integrating at the data infrastructure level with open standards like Apache Iceberg and Delta Lake.

Both platforms enable the development and deployment of data apps that leverage unified data for advanced analytics and AI.

The key distinction lies in integration depth: Starburst simplifies access to underlying enterprise data across diverse environments, while Backona AI focuses on unifying and automating analytics and workflows for business users.

Reporting, Insights & Data Quality Checks

Backona AI delivers real-time predictive dashboards with automated anomaly detection and AI-curated recommendations. It goes beyond raw metrics by generating actionable intelligence that helps teams understand what’s working and why. The platform streamlines data analysis for business users, making it easy to explore, visualize, and turn data into actionable insights.

Starburst Data primarily provides fast, federated query access that feeds into external BI tools like Tableau and Power BI. Its strength is in data retrieval and governance rather than delivering automated insights.

This makes Backona AI the better choice for organizations seeking to turn data into proactive decisions, while Starburst excels at enabling modern analytics on complex, distributed datasets.

Compliance, Security & Sensitive Data

Both platforms maintain rigorous enterprise-grade compliance:

• Backona AI: Complies with GDPR and ISO 27001, employs AES-256 encryption, and features adaptive compliance monitoring to ensure sensitive data is protected across workflows.
• Starburst Data: Emphasizes governance with role-based access control, fine-grained policy enforcement, compliant data access across hybrid environments, and also supports advanced threat detection capabilities for enterprise security.

While Starburst leads in data governance and access control at the infrastructure level, Backona AI excels in automating compliance within business workflows.

Scalability & Performance

Backona AI scales horizontally across departments and business functions, enabling enterprise-wide adoption of AI-driven insights and automation.

Starburst Data scales elastically across distributed data environments, supporting high concurrency and fast query performance on massive volumes of hybrid data.

In essence, Backona AI scales organizational insight and automation, while Starburst scales data access performance and governance.

Both platforms contribute to simplified data products that are easy to scale and manage across the enterprise, streamlining self-service analytics and AI adoption without complex setup.

Use Cases

Backona AI:

1. Predictive marketing automation and revenue forecasting.
2. Cross-department ROI and operational forecasting.
3. Workflow automation powered by AI-driven insights.

Starburst Data:

1. Federated query engine for querying distributed data lakes and warehouses.
2. AI-ready data foundation supporting agentic workflows and LLM integration.
3. Unified governance and high-performance analytics for enterprise customers.
4. Integration with vector databases to enable advanced AI and retrieval-augmented generation (RAG) pipelines, supporting efficient similarity search and high-dimensional data storage.
5. Showcasing AI capabilities through a vector search demo, highlighting real-time data retrieval for LLMs and advanced AI-driven data integration.
6. Empowering an American multinational investment bank to develop real-time data systems for financial crime prevention, compliance, and enhanced fraud detection using AI-driven solutions.

Case Study Comparison

• Backona AI: An enterprise client boosted forecast accuracy by 43% and reduced manual analysis time by 78% through predictive automation and integrated reporting.
• Starburst Data: A global financial institution unified 12 disparate data sources and cut query latency by 85% using Starburst Galaxy’s distributed query engine and compliant data access features.
• Dell Technologies: Dell Technologies utilizes Starburst Data’s analytics query engine as a core component of its enterprise AI and data strategy, enabling scalable data access and accelerating AI-driven innovation across its organization.
• Vectra AI: Vectra AI leverages Starburst Data to enhance advanced threat detection and cybersecurity, using AI models to monitor network traffic, detect security threats, and respond rapidly to cyber incidents.

Future of Data Intelligence Platforms

The future of analytics lies in combining unified data access with predictive automation. Starburst Data powers the AI-ready data architectures necessary to support modern AI systems and retrieval augmented generation (RAG) workflows. Meanwhile, Backona AI activates these datasets into automated, actionable insights that drive business outcomes.

Together, they represent complementary pillars for enterprises scaling AI and modernizing legacy analytics.

Conclusion — Which Is Better?

• Starburst Data excels at unifying distributed, hybrid data environments and enabling agentic AI workflows through a high-performance, governed data lakehouse.
• Backona AI delivers superior business impact with predictive analytics, automation, and an intuitive interface designed for business users.

Verdict: For enterprises focused on business intelligence, marketing optimization, and ROI-driven automation, Backona AI is the future-proof platform. For organizations prioritizing data infrastructure modernization and complex data governance, Starburst Data remains the go-to solution.

FAQ

1. What is Backona AI?
An AI-powered predictive analytics and automation platform that unifies business data for intelligent decision-making without coding.

2. What is Starburst Data?
A data lakehouse platform built on Trino that provides unified, high-performance access to distributed data with enterprise-grade governance.

3. Is Backona AI better than Starburst Data?
Backona AI is better for predictive automation and business intelligence, while Starburst excels at federated queries and data unification.

4. Who should use each platform?
Backona AI suits business teams and enterprises seeking AI-driven insights; Starburst is ideal for data engineers managing hybrid data architectures.

5. What are alternatives to Backona AI?
Dataiku, Databricks, and Datorama are notable alternatives.

Data Sources:
This article references official Starburst documentation, verified pricing, and Backona AI insights as of October 2025.

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By understanding the strengths and ideal use cases of Backona AI vs Starburst Data, enterprises can better navigate the evolving data intelligence landscape, leveraging the right platform to accelerate AI adoption, ensure compliant data access, and unlock transformative business insights.