The only data platform purpose-built for analytics

Deliver data isolation, scalability, and high-speed analytics in a single, lightweight system.

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The only data platform purpose-built for analytics

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Simplify data access with a unified service layer

Granular multi-tenant isolation

Each tenant has its own in-memory data mart (FlexMart), ensuring strong data governance and exceptional performance.

Flexible real-time and batch

Real-time data streaming combined with in-memory batch processing for optimized performance, latency, and cost.

Modern and open lakehouse stack

With DuckDB, Iceberg, and Arrow, the Analytics Lake integrates seamlessly with existing ecosystems and avoids vendor lock.

Low cost, exceptional performance

The Analytics Lake delivers fast queries without the cost of a full-scale data warehouse.

Easy scalability and automation

Manage thousands of data pipelines, data marts, and analytics environments efficiently.

Introducing FlexConnect

Write custom self-service integrations to any data source.

Integrate niche or homegrown data sources rapidly, reducing time to value and empowering your team to immediately leverage unique data without bottlenecks.

Allow your team to independently build and incorporate any data source into GoodData’s data models, reducing dependency on external support and speeding up deployments.

Connect to virtually any system or data source, including niche or homegrown solutions, using familiar SQL and API standards. This flexibility helps incorporate diverse data assets without complex integration projects.

Embed advanced transformations, data federation, or ML tasks within the connection itself, enabling real-time data insights and a streamlined analytics workflow.

By embedding business logic and governance mechanisms directly within the data source connection, FlexConnect ensures consistent, trusted data flows and robust security, enhancing the quality and reliability of your insights.

The unique purpose of an Analytics Lake

The Analytics Lake is designed to integrate with raw data from a data lake and structured data from a data warehouse to provide advanced analytics, comprehensive business intelligence, and accurate predictive insights, driving better decision-making and outcomes.

	Analytics Lake
Solution
Primary Focus
Scalable raw data storage	Business reporting and decision-making	Analytics and machine learning
Storage Format & Optimization
Optimized for low-cost storage of large raw, unstructured data	Structured data optimized for query performance	Optimized compute for ML workflows
Metadata & Semantic Layers
Limited metadata and semantics	Typically has integrated business metadata	Integrated metadata and headless semantic layer
BI & Visualization Capabilities
Minimal BI support	Full support for BI workflows and visualizations	Integrated BI and visualizations environment
Advanced Analytics Support
Strong support for advanced analytics	Basic predictive modeling capabilities	Optimized for advanced analytics and ML
Data Science & ML Support
Supports data science through big data tools	Limited support for data science workflows	Tailored for data science and ML with compute optimization and APIs
Compliance & Governance
Limited governance capabilities	Strong auditing, security, and governance capabilities	Robust governance through metadata integration
APIs & Programmatic Access
Access via big data APIs and notebooks	Traditionally accessed through SQL	APIs designed specifically for analytics engineers
Cost Efficiency
Very low-cost storage but unpredictable analytics costs	Predictable but relatively high storage costs	Optimized processing reduces overall costs
Flexibility & Future Proofing
Flexible but typically requires migration for BI use	Schema-on-write limits flexibility	Designed to interoperate with multiple data platforms
Key Strengths
Scalability, cost efficiency for storage	Performance, consistency, reliability	Purpose-built for advanced analytics and ML
Key Limitations
Challenging to apply governance or reuse data for BI and reporting	Limited flexibility and ability to handle messy, large, or streaming data	Emerging architecture

Solution	Data Lake	Data Warehouse	Analytics Lake
Primary Focus	Scalable raw data storage	Business reporting and decision-making	Analytics and machine learning
Storage Format & Optimization	Optimized for low-cost storage of large raw, unstructured data	Structured data optimized for query performance	Optimized compute for ML workflows
Metadata & Semantic Layers	Limited metadata and semantics	Typically has integrated business metadata	Integrated metadata and headless semantic layer
BI & Visualization Capabilities	Minimal BI support	Full support for BI workflows and visualizations	Integrated BI and visualizations environment
Advanced Analytics Support	Strong support for advanced analytics	Basic predictive modeling capabilities	Optimized for advanced analytics and ML
Data Science & ML Support	Supports data science through big data tools	Limited support for data science workflows	Tailored for data science and ML with compute optimization and APIs
Compliance & Governance	Limited governance capabilities	Strong auditing, security, and governance capabilities	Robust governance through metadata integration
APIs & Programmatic Access	Access via big data APIs and notebooks	Traditionally accessed through SQL	APIs designed specifically for analytics engineers
Cost Efficiency	Very low-cost storage but unpredictable analytics costs	Predictable but relatively high storage costs	Optimized processing reduces overall costs
Flexibility & Future Proofing	Flexible but typically requires migration for BI use	Schema-on-write limits flexibility	Designed to interoperate with multiple data platforms
Key Strengths	Scalability, cost efficiency for storage	Performance, consistency, reliability	Purpose-built for advanced analytics and ML
Key Limitations	Challenging to apply governance or reuse data for BI and reporting	Limited flexibility and ability to handle messy, large, or streaming data	Emerging architecture