5X vs Snowflake: Beyond Data Warehousing

The most crucial metric for data teams isn't the volume of data collected, query execution speed, or pipeline uptime. It's data readiness.

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Data readiness ensures your clean, structured, and centrally modeled data is readily available for a number of use cases: traditional BI, advanced analytics, data activation, and increasingly, AI. It's the foundation for AI and Large Language Models (LLMs) – after all, your AI is only as good as the data it learns from.

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Snowflake is a warehousing powerhouse. It excels at storing and managing large amounts of data, and is making strides with new initiatives. But is it a complete data readiness platform? 

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This article compares 5X with Snowflake from a data readiness perspective and explores how you can get the best of both worlds.

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The five layers of a data-ready system are:

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1. Ingestion

2. Warehouse

3. Modeling 

4. Orchestration

5. Business Intelligence

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So how do 5X and Snowflake stack up on these? Let’s find out!

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Snowflake

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Ingestion

• Offers some native ingestion tools (COPY INTO, Snowpipe, Kafka Connector) that work with sources like Google Analytics.
• Requires additional configuration and custom scripting for complex data sources with non-standard formats or APIs.
• Integrates with third-party data transfer services for broader source coverage.

Warehouse

• Excellent storage and compute capabilities, ideal for handling large, complex datasets.
• Offers various storage options (e.g., micro-partitions, clustering) to optimize performance and cost for diverse workloads.

Modeling

• Limited native modeling capabilities.
• Does not offer dbt for SQL-based modeling.
• Relies on Snowpark (to query, process, and transform data using Python) for advanced data transformations.
• Offers connector for Apache Spark.
• Direct integration of advanced analytics (forecasting, anomaly detection) into data models via Snowflake Cortex.

Orchestration

• Basic built in scheduling capabilities with Snowflake Tasks.
• Requires vendor ecosystem for complex scheduling capabilities.

Business intelligence

• Offers basic charts for visualization.
• Lacks native BI tools for data visualization and exploration.
• Integrates with external BI tools like Looker, Tableau, Power BI.

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How 5X complements Snowflake’s warehousing capabilities

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Ingestion

• Offers 500+ pre-built connectors from all of the most used data sources.
• Hours, day implementations for custom connector development for the long tail of connectors.
• Support for Apache Iceberg Tables in S3 or other flat storage.

Warehouse

• Works on top of Snowflake
• Also works with multiple other warehouses, including GBQ, Redshift, and Databricks.

Modeling

• Integrates with dbt for enterprise-grade data modeling.
• Offers features like lineage tracking, version control, and modular transformations.
• Also supports SQL, Python, and notebooks for transformation flexibility.

Orchestration

• Offers Dagster to ship pipelines quickly with 1-click scheduling.
• Enterprise grade scheduling and DAGS with easy to use UI.
• Prebuilt templates to accelerate dev time.

Business intelligence

• Compatible with any BI tool.
• Provides Superset as an inbuilt option in the platform.
• Deep integrations and provisioning Power BI, Looker, Sigma and Tableau from 5X.

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Snowflake vs 5X: A comparison on data readiness level

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Other considerations

Total cost of ownership (TCO)

Building data pipelines in Snowflake often requires multiple services for different ingestion methods (Snowpipe, Kafka Integration, etc.), leading to unexpected charges. Plus, separate tools for modeling (dbt, Snowpark) and orchestration (Airflow, custom scripts) add to the overall cost.

5X’s integrated platform typically reduces TCO by 30-50% compared to a piecemeal approach. A single platform simplifies billing and eliminates the need to manage multiple service costs from Snowflake and various data tools.

Integrated services offering

Snowflake requires additional resources for building and managing data pipelines. This can involve hiring external consultants or building an in-house data engineering team (data salaries are getting expensive), resulting in significant costs.

5X’s integrated services are approximately 25% of the cost of US-based consultancies and 70% of the cost of building and scaling an in-house team in America.

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So, what now?

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Snowflake is a great data warehouse, but it falls short in the broader spectrum of data readiness—ingestion, modeling, orchestration, and business intelligence.

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5X, on the other hand, provides a more comprehensive data readiness platform that ensures your data is clean, accessible, and actionable. Using 5X on top of Snowflake, you can create a powerful and complete data stack.

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Snowflake is expanding its ecosystem with initiatives like advanced AI use cases for GPU and the Cortex suite of AI and ML features. These features can accelerate AI adoption on top 5X + Snowflake, once the foundation for data readiness has been built.

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