Alteryx to SQL Matrix is a practical reference tool teams migrating from Alteryx to Snowflake. We mapped Alteryx tools to equivalent SQL functions, Snowpark Python scripts, or user-defined functions (UDFs). As more organizations shift from low-code platforms to cloud-first data stacks, this guide bridges the gap between Alteryx workflows and modern ELT practices in Snowflake.
Why was this created?
Many data teams are moving from low-code/no-code platforms like Alteryx to modern cloud-based analytics platforms like Snowflake, due to reasons like:
- Scalability and cost optimization
- Centralized governance of code-based transformations
- Shift from decentralized self service ETL to centralized ELT
- Operationalizing machine learning pipelines in the cloud
- Avoiding licensing lock-in for basic prep and modeling tasks
Who is this for?
- Data Engineers rewriting Alteryx workflows in SQL or Python
- Analytics leads planning Alteryx retirement or Snowflake-first data strategies
- Consultants and solution architects leading migration or modernization projects
- Alteryx users learning to translate their skills to SQL.
Need help translating Alteryx to Snowflake?
Article: Alteryx to Snowflake Guide
How self service with Alteryx can create data chaos
DataTools Spotlight: Datameer is our Snowflake Tool of Choice
Alteryx to Snowflake SQL Matrix
| Category | Alteryx Tool | Snowflake SQL Low Code |
|---|---|---|
| Preparation | Browse | PREVIEW DATA |
| Preparation | Data Cleansing | CASE, COALESCE, IFF |
| Preparation | DateTime | DATEADD, DATEDIFF, TO_DATE |
| Preparation | Filter | WHERE |
| Preparation | Formula | CASE, COALESCE, IFF, SQL Functions |
| Preparation | Generate Rows | SEQUENCE |
| Preparation | Imputation | CASE, COALESCE, IFF |
| Preparation | Multi-Field Binning | CASE |
| Preparation | Multi-Field Formula | CASE |
| Preparation | Multi-Row Formula | LAG, LEAD |
| Preparation | Random % Sample | SAMPLE |
| Preparation | Record ID | ROW_NUMBER |
| Preparation | Sample | SAMPLE |
| Preparation | Select | SELECT |
| Preparation | Select Records | WHERE |
| Preparation | Sort | ORDER BY |
| Preparation | Unique | DISTINCT |
| Parse | Find Replace | JOIN |
| Parse | JSON Parse | PARSE_JSON, FLATTEN |
| Parse | RegEx | REGEXP |
| Parse | Text to Columns | SPLIT, FLATTEN |
| Parse | XML Parse | XMLPARSE |
| Parse | Address | — Custom Implementation Needed |
| Transform | Summarize | GROUP BY |
| Transform | Append Fields | JOIN |
| Transform | Cross Tab | PIVOT |
| Parse | Create Points | ST_GEOGPOINT |
| Transform | Principal Components Analysis | ST_UNION_AGG, GROUP BY |
| Transform | Spatial Info | ARRAY, GROUP BY |
| Transform | Moving Summarize | ARRAY, GROUP BY |
| Transform | Pairwise Distance | Snowpark Python |
| Transform | Polynomial Regression | UDF – PACKAGES = (‘numpy’, ‘scikit-learn’) |
| Transform | Density-Based Spatial Clustering | Snowpark Python |
| Transform | K-Centroid Cluster Analysis | Snowpark Python (Pandas – kmeans = KMeans(n_clusters=3, random_state=0) |
| Transform | Make Columns | PIVOT |
| Transform | Arrive/Depart | DATEDIFF |
| Transform | Tile | Snowpark (pandas.qcut) |
| Transform | Transpose | UNPIVOT |
| Reporting | Charting | EMAIL PACKAGE |
| Reporting | IMAGE PACKAGE | |
| Reporting | Image | N/A |
| Reporting | Layout | N/A |
| Reporting | Map | ST_GEOGPOINT |
| Reporting | Report Map | ST_DISTANCE |
| Reporting | Report Text | ST_NEAREST_POINTS |
| Reporting | Table | ST_SIMPLIFY |
| Spatial | Buffer | ST_GEOGFROMWKT |
| Spatial | Create Points | ST_GEOGFROMTEXT |
| Spatial | Distance | ST_GEOGFROMGEOJSON |
| Spatial | Find Nearest | ST_GEOGFROMKML |
| Spatial | Generalize | ST_UNION_AGG, GROUP BY |
| Spatial | Poly-Build | BOOLEAN, CASE |
| Spatial | Poly-Split | BOOLEAN, CASE |
| Spatial | Poly-Spline | PARAMETERIZED QUERIES |
| Spatial | Spatial Info | — Custom Implementation Needed |
| Spatial | Spatial Match | ERROR HANDLING |
| Spatial | Trade Area | ST_BUFFER (basic radius trade areas) |
| Documentation | Comment | Supported |
| Documentation | Container | N/A |
| Documentation | Tool Container | N/A |
| Connectors | SharePoint | Not supported |
| Connectors | Amazon S3 | Natively Supported |
| Connectors | Google Analytics | — Custom Implementation Needed |
| Connectors | Salesforce Input | Native Supported Salesforce Data Cloud |
| Connectors | Salesforce Output | Native Supported Salesforce Data Cloud |
| Connectors | Tableau | N/A |
| Connectors | Adobe Analytics | Native Supported Zero Copy (Adobe Real-Time Customer Data Platform (CDP) and Adobe Journey Optimizer) |
| Predictive | A/B Testing | Snowpark Python (scipy.stats.ttest_ind) |
| Predictive | AB Controls Testing | Snowpark Python (scipy.stats.ttest_ind, stratified grouping) |
| Predictive | Apriori | Snowpark Python (mlxtend.frequent_patterns.apriori) |
| Predictive | Create Samples | TABLESAMPLE, RANDOM(), or UNIFORM() in SQL |
| Predictive | Decision Tree | snowflake.ml.modeling.tree.DecisionTreeClassifier (Snowpark ML) |
| Predictive | Forest Model | Snowpark Python (sklearn.ensemble.RandomForestClassifier) |
| Predictive | Lift Chart | Snowpark Python (sklearn.metrics.roc_curve, matplotlib) |
| Predictive | Linear Regression | snowflake.ml.modeling.linear_model.LinearRegression (Snowpark ML) |
| Predictive | Logistic Regression | snowflake.ml.modeling.linear_model.LogisticRegression or Snowpark Python (sklearn) |
| Predictive | Naive Bayes | snowflake.ml.modeling.naive_bayes.ComplementNB |
| Predictive | Nested Test | Snowpark Python (statsmodels.stats.anova_lm) |
| Predictive | Principal Components | Snowpark Python (sklearn.decomposition.PCA) |
| Predictive | Random Forest | Snowpark Python (sklearn.ensemble.RandomForestClassifier) |
| Predictive | Score | UDF or Snowpark batch scoring |
| Predictive | Support Vector Machine | Snowpark Python (sklearn.svm.SVC) |
| Predictive | Test | Snowflake SQL assertions or Snowpark Python validation |
| Data Investigation | Association Analysis | Snowpark Python (mlxtend.association_rules) |
| Data Investigation | Contingency Table | PIVOT + GROUP BY |
| Data Investigation | Frequency Table | GROUP BY + COUNT() |
| Data Investigation | Pearson Correlation | CORR(col1, col2) |
| Data Investigation | Spearman Correlation | Snowpark Python (scipy.stats.spearmanr) |
| Data Investigation | Summary Statistics | MIN, MAX, AVG, STDDEV, VAR_POP |
| Time Series | ARIMA | Snowpark Python (pmdarima.auto_arima) |
| Time Series | ETS | Snowpark Python (statsmodels.tsa.holtwinters) |
| Time Series | TS Covariance | COVAR_POP / Snowpark Python (pandas.cov()) |
| Time Series | TS Filler | Snowpark Python (pandas.interpolate()) |
| Time Series | TS Forecast | Snowflake Cortex Forecast / Snowpark Python (prophet, pmdarima) |
| Time Series | TS Model Factory | Snowpark Python (Grouped forecasting by key) |
| Time Series | TS Plot | Snowpark Notebook (matplotlib, seaborn, statsmodels.plot) |
| Time Series | TS Regression | Snowpark Python (statsmodels.OLS) |
| Demographic Analysis | Allocate Append | External enrichment service (no native equivalent) |
| Demographic Analysis | Allocate Input | External enrichment service (no native equivalent) |
| Demographic Analysis | Allocate Reports | External service or reporting layer |
| Demographic Analysis | Allocate Trade Area | External GIS system (e.g., Alteryx, PostGIS, Mapbox) |
| Demographic Analysis | Allocate Calculate | External enrichment tool |
| Demographic Analysis | Allocate Concentric | Snowpark Python + GIS integration (PostGIS buffer logic) |
| Demographic Analysis | Allocate Spatial Match | ST_WITHIN, ST_INTERSECTS |
| Demographic Analysis | Allocate Summarize | GROUP BY + spatial aggregation |
| Predictive Grouping | Append Cluster | Snowpark Python (sklearn.cluster.KMeans, cluster label JOIN) |
| Predictive Grouping | K-Centroids Analysis | Snowpark Python (sklearn.cluster.KMeans) |
| Predictive Grouping | K-Centroids Diagnostics | Snowpark Python (inertia, silhouette score from sklearn) |
| Predictive Grouping | MB Affinity | Snowpark Python (cosine_similarity, pandas.crosstab()) |
| Predictive Grouping | MB Inspect | Snowpark Python (manual matrix inspection & statistics) |