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Introducing ML Functions in SingleStore: Bring Models to the Data
Discover SingleStore ML Functions — a new way to train, deploy, and serve custom machine learning models directly in your database. Build predictive models tailored to your business data with real-time performance, monitoring, and SQL simplicity.
AI Functions in SQL | SingleStore – Run Generative AI on Your Data
Discover SingleStore AI Functions, a breakthrough that brings generative AI and embeddings directly to your data with simple SQL. Perform sentiment analysis, translation, summarization, fraud detection, and more in real time—no data movement, no complexity.
Data Warehouses, Lakes, Lakehouses and Hubs: Great for Analytics — But Not Built for Real Time
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.
AI Database Examples: Vector Search, Recommendations & LLM Workflows with SingleStore
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.
Reverse ETL vs Zero ETL: Why SingleStore Outpaces Databricks Lakebase
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.
Scaling PostgreSQL vs. SingleStore: Overcoming Performance & Complexity Limits
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.
The Lakebase Vision Is Right. Who Will Build It First?
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?
5 Hidden Costs of Running Real-Time Workloads on Snowflake (and How to Calculate Them)
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.
What Is MCP? How the Model Context Protocol Is Powering AI-Native Infrastructure
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.