Analytics as a Service vs Data as a Product
Data marketplaces sell raw data that you must analyze yourself. Spartera sells analytics - the insights are already computed. Understand when you need data versus when you need answers.
Data marketplaces (Snowflake Data Marketplace, AWS Data Exchange, Databricks Marketplace) sell raw datasets - tables of records you must process, analyze, and derive insights from yourself. Spartera sells analytics - pre-computed insights delivered via API with all the analysis already done. Different products for different needs.
Quick decision guide to help you choose the right solution
Side-by-side comparison of key features and capabilities
What makes these solutions different
Spartera sells answers to questions. Data marketplaces sell raw data you must analyze to find answers. If you know what insights you need, buying them directly saves 3-6 months of infrastructure and analysis work.
Spartera delivers insights in <1 hour via API. Data marketplaces require 1-3 months to set up infrastructure, ingest data, build analytics, and generate insights. Time to value difference is 100x.
Spartera: $0.50-$5 per insight. Data marketplaces: $10K+ for dataset + $200K-$1M/year infrastructure + engineering team. For most use cases, buying insights is 90% cheaper than buying data.
Spartera requires zero infrastructure - just API calls. Data marketplaces require data warehouse, ETL pipelines, BI tools, and 2-5 data engineers. If you don't already have this infrastructure, building it is a massive undertaking.
Spartera queries live data sources in real-time. Data marketplaces sync datasets on batch schedules (daily/weekly), meaning your data is always hours or days stale. For time-sensitive decisions, real-time matters.
Spartera optimizes for speed and simplicity - 80% of use cases with zero work. Data marketplaces optimize for flexibility - 100% of use cases but massive effort. Choose based on whether you need custom analysis or standard insights.
When each solution shines in practice
A Series A SaaS company wants competitor pricing, market share, and feature comparison data for their sales team. They need answers, not raw data. They have 2 engineers total - no capacity for data infrastructure. Spartera's pre-computed insights cost $100/month vs $500K+ to buy datasets and build analysis infrastructure.
An agency creates monthly reports for 50 clients, needing industry benchmarks and trend data. They need specific statistics to insert in reports, not datasets to analyze. Spartera APIs auto-generate stats for each report. Data marketplace approach would require a full data team.
An e-commerce company needs real-time competitor prices to adjust their pricing hourly. They need current prices on demand, not batch data updates. Spartera's real-time APIs deliver current prices. Data marketplace batch updates would be hours stale and useless.
A fintech is building proprietary credit risk models requiring raw transaction data to train ML algorithms. They need the actual data, not pre-computed scores. Their data science team will do custom analysis that no pre-built API can match. Data marketplaces provide the raw data they need.
A hedge fund is doing unique research combining weather data, satellite imagery, and economic indicators with complex custom joins. Their competitive advantage is the novel combination and analysis. They need raw data to do proprietary analysis. Data marketplaces enable this; pre-built APIs don't.
A company is building a data product they'll sell to others. They need raw data to create proprietary analytics that become their product. Buying someone else's analytics doesn't work - they need to create unique value. Data marketplaces provide raw materials.
Common questions about this comparison