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Gartner outlines best practices for data warehouses, lakes, lakehouses, and hubs — but says little about real-time. Discover the key limitations of these architectures and how SingleStore enables real-time performance, concurrency, and AI application serving.
Explore practical AI database examples with SingleStore, including semantic search, real-time recommendations, multimodal LLM apps, and model evaluation. Learn how to move from notebook to production with vectors and SQL.
Databricks Lakebase simplifies reverse ETL, but SingleStore goes further with zero ETL—activating data instantly without pipelines or sync overhead. Discover how SingleStore delivers real-time analytics, lower costs, and a unified platform.
Snowflake is great for analytics—but when pushed into real-time, costs spiral. Discover the 5 hidden cost drivers inflating Snowflake’s TCO, with real-world enterprise examples and formulas to calculate your true annual spend.
The Lakebase vision is compelling: unify OLTP and OLAP workloads, eliminate complex data movement and enable AI applications to operate at machine speed. Databricks deserves credit for clearly articulating this direction. But the harder question remains: when will it actually be ready?
Discover the challenges of scaling PostgreSQL — from replication lag to lock contention — and learn how SingleStore delivers unified, high-performance SQL for transactional, analytical, and AI workloads without the patchwork architecture.
Discover how the Model Context Protocol (MCP) is transforming AI-native infrastructure by enabling secure, scalable, and structured interactions between LLMs and external systems. Learn from real-world use cases shared at the MCP Lisbon Meetup.