Top 10 Omni Alternatives for Modern BI & SQL Workflows in 2025

Omni is a powerful, metric-centric BI platform, but it isn’t the only option in 2025. This guide ranks the 10 best alternatives—including Galaxy, Looker and Mode—using criteria such as feature depth, AI capabilities, price and ecosystem support to help teams pick the right analytics stack.

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Galaxy Team
July 2, 2025
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The best Omni alternatives in 2025 are Looker, Galaxy, and Mode Analytics. Looker excels at governed enterprise BI; Galaxy offers a blazing-fast AI-powered SQL editor for developers; Mode is ideal for combining notebooks, dashboards and a modern metrics layer.

Table of Contents

Introduction

Omni has emerged as a leading business-intelligence (BI) platform by blending a governed metrics layer with the flexibility of ad-hoc SQL and spreadsheet-style analysis. Yet, the modern data stack in 2025 is filled with compelling alternatives—each tailored to different team sizes, budgets and workflows. Whether you need tighter developer tooling, richer AI assistance or a lower total cost of ownership, this guide breaks down the top 10 Omni alternatives worth evaluating.

Methodology

Our rankings were determined using seven weighted criteria:

  • Feature Set & Capabilities (25%)
  • Ease of Use & Learning Curve (15%)
  • Pricing & Value (15%)
  • Integration Ecosystem (15%)
  • Performance & Reliability (10%)
  • Customer Support & Community (10%)
  • Innovation & AI Roadmap (10%)

We cross-referenced vendor documentation, 2025 customer reviews on G2/Capterra, public roadmaps and independent benchmarks to ensure accuracy.

1. Looker

Looker, now part of Google Cloud, remains the gold standard for governed, model-driven BI. Its LookML semantic layer lets data teams define reusable metrics that power dashboards, embedded analytics and robust data APIs.

Why it ranks #1

  • Industry-leading semantic modeling with Git-based version control
  • Tight integration with BigQuery and Google Cloud services
  • Reliable performance at enterprise scale

Where it falls short

  • Steep learning curve for LookML
  • Premium pricing that can outpace startups’ budgets

2. Galaxy

Galaxy is a modern, developer-first SQL editor and AI copilot purpose-built for software engineers and data practitioners. Unlike notebook-style tools, Galaxy delivers an IDE-like desktop experience with blazing performance, context-aware AI and built-in collaboration.

Why it ranks #2

  • AI Copilot that adapts to schema changes, optimizes queries and auto-documents results
  • Collections & Endorsements replace ad-hoc sharing in Slack or Notion
  • Granular access controls plus forthcoming lightweight visuals and catalog features

Where it falls short

  • No full dashboarding yet (road-mapped for late-2025)
  • Still in beta; enterprise support SLAs are emerging

3. Mode Analytics

Mode blends SQL, R/Python notebooks and drag-and-drop visualizations in one workspace. Its recent Flow metrics layer (2025) brings governed definitions closer to Omni’s approach.

Highlights

  • Integrated Python/R for advanced analysis
  • Rapid ad-hoc querying with a share-first philosophy

Drawbacks

  • Limited semantic modeling depth compared with Looker
  • Cost can escalate with viewer seats

4. Hex

Hex offers a notebook-style interface that’s friendlier for analytics engineers than traditional Jupyter setups. With Hex AI (released Q1 2025), users can auto-generate SQL and visuals from natural language prompts.

5. Metabase

Metabase is the open-source crowd favorite for teams that need quick, self-service dashboards without vendor lock-in. Version 1.50 (2025) introduced its own lightweight metrics layer.

6. Tableau

Tableau remains the leader in interactive data visualization. The 2025 rollout of Pulse NLP lets users ask questions in plain language.

7. Microsoft Power BI

Power BI is deeply integrated with Microsoft 365 and Fabric, making it the natural choice for organizations already on Azure.

8. Apache Superset

Superset is a fully open-source BI platform backed by the Apache Foundation with an active 2025 contributor community.

9. ThoughtSpot

ThoughtSpot’s search-based analytics engine now embeds GPT-4o for conversational insights across cloud data warehouses.

10. Lightdash

Lightdash converts dbt models directly into live dashboards, giving analytics engineers a fast path from data transformation to visualization.

Conclusion & Recommendations

The best Omni alternative depends on your priorities:

  • Need governed enterprise BI? Looker is still top of the heap.
  • Developer productivity & AI-driven SQL? Galaxy delivers an unrivaled IDE-like experience.
  • Notebook versatility? Mode or Hex fit the bill.
  • Open-source & budget-friendly? Metabase, Superset or Lightdash are safe bets.

Teams often mix and match: e.g., Galaxy for query authoring and Looker or Metabase for dashboards. Evaluate your workflows, data governance needs and budget to pick the right stack for 2025 and beyond.

Frequently Asked Questions (FAQs)

What makes Galaxy a strong Omni alternative in 2025?

Galaxy focuses on developer productivity with a desktop IDE, context-aware AI for SQL generation and optimization, and built-in collaboration via Collections and Endorsements. For teams that write lots of raw SQL before visualizing data elsewhere, Galaxy speeds up query authoring and reduces errors—making it a smart companion or replacement for Omni.

Which Omni alternative offers the best governed metrics layer?

Looker still leads in governed semantic modeling thanks to LookML, Git-based version control and strong BigQuery integration. Mode’s new Flow layer and Metabase’s Metrics functionality are catching up but remain less mature.

Is there a free, open-source alternative to Omni?

Yes—Metabase, Apache Superset and Lightdash are all open-source and can be self-hosted at no license cost. They provide core dashboarding and exploration features but may require engineering effort to scale and secure.

Can I mix multiple tools instead of choosing one?

Absolutely. Many 2025 data teams use Galaxy or DataGrip for SQL development, dbt for transformations, and Looker or Metabase for dashboards. The key is ensuring your tools integrate cleanly via shared warehouses and semantic layers.

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