Hex vs Power Query
Side-by-side comparison to help you choose.
| Feature | Hex | Power Query |
|---|---|---|
| Type | Web App | Product |
| UnfragileRank | 38/100 | 32/100 |
| Adoption | 1 | 0 |
| Quality | 0 | 1 |
| Ecosystem | 0 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Paid |
| Capabilities | 16 decomposed | 18 decomposed |
| Times Matched | 0 | 0 |
Executes SQL, Python, and no-code cells in a cloud-hosted reactive compute environment where cell dependencies are automatically tracked and re-executed only when upstream cells change. Uses a dataflow execution model similar to spreadsheet recalculation, maintaining stateful session context across cell runs and supporting query pushdown to connected data warehouses to avoid materializing large datasets locally.
Unique: Implements spreadsheet-like reactive execution (only re-run changed cells and dependents) for SQL/Python notebooks with automatic query pushdown to warehouses, avoiding local materialization of large datasets. Most notebooks (Jupyter, Colab) require manual cell re-execution; Hex's dataflow model is closer to Databricks notebooks but with tighter warehouse integration.
vs alternatives: Faster iteration than Jupyter for warehouse-backed analysis because reactive execution eliminates manual re-running, and query pushdown prevents local memory bottlenecks on large datasets.
Natural language agent that generates, modifies, debugs, and documents SQL/Python code cells based on user prompts. The agent receives context from the current notebook state (cell values, data schemas), connected data sources, and optional semantic models (dbt-based metric definitions), then generates or edits code that executes in the reactive environment. Supports unlimited quick edits on Professional+ plans and trial access on free tier.
Unique: Agent receives notebook execution context (cell values, data schemas) and optional semantic models (dbt) to generate contextually-aware code. Unlike generic code assistants (Copilot), the agent understands the current analysis state and can reference standardized metrics, reducing hallucination and improving relevance for data work.
vs alternatives: More accurate than GitHub Copilot for data analysis because it has access to live data schemas and semantic models, reducing the need for manual prompt engineering or code review.
Manages connections to multiple data sources (Snowflake, Redshift, BigQuery, S3, generic SQL via SSH) with support for OAuth, SSH keys, and standard database credentials. Connections are workspace-level and can be shared across notebooks. Supports connection testing and credential rotation. Enterprise plan includes OIDC SSO for database connections.
Unique: Centralizes data source connections at the workspace level with support for multiple authentication methods (OAuth, SSH, standard credentials). Unlike Jupyter (which requires manual credential management in notebooks), Hex abstracts credentials and enables sharing without exposing secrets.
vs alternatives: More secure than Jupyter because credentials are managed centrally and not stored in notebooks; more flexible than Tableau because it supports SSH and generic SQL connections.
Maintains version history of notebooks with snapshots at each execution or manual save. Users can view, compare, and rollback to previous versions. Version retention depends on plan: 7 days (free), 30 days (Professional), unlimited (Team+). Snapshots include cell code, execution results, and metadata (timestamp, author).
Unique: Built-in version history with automatic snapshots on execution, eliminating the need for manual Git commits. Unlike Jupyter (which requires external Git), Hex tracks versions automatically and provides UI-based comparison and rollback.
vs alternatives: More convenient than Git for non-technical users because versioning is automatic and rollback is UI-based, not requiring command-line Git operations.
Provides read-only access to published apps and dashboards with ability to filter, drill-down, and interact with visualizations without viewing or editing underlying code. Explorer users cannot see SQL/Python cells, only the published results. Enables sharing insights with business stakeholders without exposing data warehouse queries or business logic.
Unique: Explorer role separates code access from result access, allowing non-technical users to interact with dashboards without seeing underlying queries. Unlike Tableau (which requires separate data modeling), Hex Explorer role is built on top of existing notebooks, reducing duplication.
vs alternatives: More flexible than Tableau for code-first teams because it allows sharing results without exposing queries, while keeping code and dashboards in the same tool.
Offers tiered compute profiles (Small through 4XL) with optional GPU acceleration (A10G, L4) for machine learning and heavy computation. Compute is billed per-minute for Large+ profiles; Medium compute is included on paid plans. Users can select compute profile per notebook run. GPU profiles enable faster model training and inference.
Unique: Offers GPU acceleration for machine learning workloads with per-minute billing, allowing teams to scale compute on-demand without managing infrastructure. Unlike Jupyter (which requires local GPU or cloud setup), Hex provides GPU as a built-in option with simple profile selection.
vs alternatives: More convenient than AWS SageMaker for exploratory ML because GPU is available on-demand without provisioning instances or managing infrastructure.
Provides observability APIs for monitoring notebook execution, tracking usage metrics, and auditing user actions in enterprise deployments. Enables integration with external monitoring tools (Datadog, New Relic, etc.). Includes audit logging for compliance and governance. Available on Enterprise plan only.
Unique: Provides observability APIs for enterprise deployments, enabling integration with external monitoring and compliance tools. Unlike most notebooks (which lack observability), Hex offers built-in audit logging and monitoring for governance-heavy organizations.
vs alternatives: More compliant than Jupyter for enterprise because it provides native audit logging and observability APIs without requiring custom instrumentation.
Enterprise plan option for deploying Hex in a single-tenant environment with HIPAA compliance, custom branding (white-label), and dedicated support. Enables embedding Hex analytics in customer-facing applications without Hex branding. Requires custom contract and pricing.
Unique: Offers single-tenant deployment with white-label branding and HIPAA compliance, enabling SaaS companies to embed Hex as a white-label analytics solution. Unlike most notebooks (which are multi-tenant only), Hex provides enterprise deployment options for customer-facing products.
vs alternatives: More suitable for SaaS embedding than Tableau because it's designed for code-first analytics and can be white-labeled without separate data modeling.
+8 more capabilities
Construct data transformations through a visual, step-by-step interface without writing code. Users click through operations like filtering, sorting, and reshaping data, with each step automatically generating M language code in the background.
Automatically detect and assign appropriate data types (text, number, date, boolean) to columns based on content analysis. Reduces manual type-setting and catches data quality issues early.
Stack multiple datasets vertically to combine rows from different sources. Automatically aligns columns by name and handles mismatched schemas.
Split a single column into multiple columns based on delimiters, fixed widths, or patterns. Extracts structured data from unstructured text fields.
Convert data between wide and long formats. Pivot transforms rows into columns (aggregating values), while unpivot transforms columns into rows.
Identify and remove duplicate rows based on all columns or specific key columns. Keeps first or last occurrence based on user preference.
Detect, replace, and manage null or missing values in datasets. Options include removing rows, filling with defaults, or using formulas to impute values.
Hex scores higher at 38/100 vs Power Query at 32/100. Hex leads on adoption, while Power Query is stronger on quality and ecosystem. Hex also has a free tier, making it more accessible.
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Apply text operations like case conversion (upper, lower, proper), trimming whitespace, and text replacement. Standardizes text data for consistent analysis.
+10 more capabilities