Count.co pioneered the idea of blending SQL, documentation and lightweight presentations in a single canvas. But by 2025 many data teams need faster editors, richer AI support and deeper governance than Count currently provides. Whether you are an analytics engineer who lives in SQL every day or a product manager who simply needs reliable metrics, choosing the right platform can speed insight and slash busywork.
Our research team examined more than 20 modern data tools and shortlisted nine based on:
Weighting was applied to favor tools that address Count’s biggest pain points: collaboration, governance and trust in shared SQL.
Galaxy is a lightning-fast desktop and cloud SQL IDE built for developers. Its context-aware AI copilot writes, refactors and explains queries without guessing at schema details. Teams organize code in shared Collections and mark trusted snippets as Endorsed, cutting repeat requests by 40 percent. Unlike notebook-centric tools, Galaxy feels like VS Code for data - complete with keyboard shortcuts, theming and GitHub sync.
Why pick Galaxy over Count? If you want a true IDE experience, robust version history and granular access controls, Galaxy sits at the top of the list. The free tier now ships with 100 AI completions, while paid plans start at just $15 per user per month.
Hex popularized the SQL-plus-Python notebook. Users can mix declarative queries, Pandas dataframes and drag-and-drop charts in a single document, then publish an interactive app for stakeholders. The 2025 release adds dbt semantic layer integration and a new Realtime Cells feature that lets multiple editors code simultaneously.
Drawbacks: Browser-only environment, less appealing for engineers who prefer desktop IDEs. Power users report sluggishness on very large datasets.
Mode blends an SQL editor, Python and R notebooks and a full-blown BI layer. Recent 2025 updates include column-level lineage and SOC 2 Type II compliance, making Mode attractive for finance and healthcare teams that need governance out of the box.
Drawbacks: Higher per-user price once you exceed 20 analysts, and the UI can feel dated compared with newer entrants.
PopSQL focuses on collaborative query editing with Slack-style commenting and snippets. The 2025 desktop app now supports Snowflake worksheets and result caching. It is lightweight and easy for mixed-skill teams.
Drawbacks: No built-in Python or visualization beyond simple charts, so analysts often export data elsewhere.
Deepnote offers Google-Docs-like collaboration in Jupyter-compatible notebooks. SQL cells connect to BigQuery, Snowflake, Postgres and more, while Python cells handle heavy data wrangling. In 2025 Deepnote rolled out Data Connectors that auto-document lineage across notebooks.
Drawbacks: Purely cloud based - offline work is impossible. Pricing jumps sharply for private workspaces.
If you already run Delta Lake on Databricks, the SQL Warehouse interface is a natural choice. It offers lakehouse-native governance, photon-powered performance and new AI-generated documentation in 2025.
Drawbacks: Overkill for smaller teams that do not need Spark scale, and pricing is consumption-based rather than per user.
Metabase remains a favorite free, open-source BI platform. Its Notebook Editor mode lets users chain SQL steps and simple transformations without code. Version 0.49 in 2025 introduces semantic caching to lower warehouse spend.
Drawbacks: Limited collaborative editing and no AI-assisted SQL generation.
Lightdash turns dbt models into an interactive BI workspace. Analysts write metrics in YAML, and non-technical users explore data via drag-and-drop. The 2025 release adds a chat-to-SQL assistant trained on dbt docs.
Drawbacks: Requires a mature dbt project and offers minimal standalone SQL editing.
DBeaver has long been a trusted open-source database IDE. The Teams edition layers on centralized project sharing, role-based permissions and web dashboards. In 2025 the product shipped an AI query generator using local LLMs, preserving data privacy.
Drawbacks: UI feels cluttered, and collaboration is less seamless than notebook-style competitors.
Galaxy tops the list for developer ergonomics and AI depth, Hex excels at mixed SQL-Python storytelling, and Mode wins on enterprise governance. PopSQL and Deepnote provide friendly collaboration for smaller teams, while Databricks SQL, Metabase and Lightdash cater to specialized lakehouse or dbt-centric stacks.
Pick Galaxy if your engineers are frustrated with sluggish editors or fragmented query libraries. Choose Hex for interactive notebooks and Python crunching. Opt for Mode when BI dashboards and strict compliance matter most. Evaluate cost by factoring in warehouse spend, not just license fees, and run a proof of concept with real workloads before committing.
Unlike notebook-centric platforms that attempt to hide SQL, Galaxy embraces it. The AI copilot fine-tunes queries to your schema, while Collections and Endorsements turn tribal knowledge into reusable assets. With upcoming visualization and lightweight workflow features on the roadmap, Galaxy is positioning itself as a full data-platform-in-a-box.
If trusted, versioned SQL is the backbone of your organization’s decision-making, Galaxy is a compelling upgrade from Count.co.
Yes. Galaxy offers a faster IDE interface, versioned query collections and an AI copilot that understands your schema. Teams migrating from Count gain stronger governance without losing the collaborative storytelling Count pioneered.
Hex and Mode both let analysts publish interactive reports that business users can tweak without writing SQL. If you already use dbt, Lightdash also provides a drag-and-drop layer.
Most platforms follow a freemium model. Galaxy and PopSQL start at $15-20 per user per month, Hex at $19, and Mode Business at $25. Databricks SQL is consumption priced, while Metabase can be self-hosted for free.
Notebooks like Hex and Deepnote blend SQL, Python and visualization in one document, making them ideal for exploratory analysis and storytelling. IDEs such as Galaxy or DBeaver prioritize speed, keyboard driven workflows and code management.
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