SingleStore

What is SingleStore?

SingleStore is a high-performance, distributed SQL database designed to unify transactional and analytical processing within a single platform. It leverages Universal Storage—combining in-memory rowstore and on-disk columnstore—to deliver low-latency query responses and handle petabyte-scale data. Delivered as a SaaS solution via SingleStore Helios or self-managed, it supports diverse data models including relational, JSON, vector search, and time-series, making it ideal for real-time analytics, AI applications, and hybrid workloads.

Key Features

• Unified Data Platform

  Combines transactional and analytical workloads with support for multi-model data types—relational, JSON, vector, geospatial, and time-series—on a single platform.

• Real-Time Analytics

  Enables instant insights into large datasets through optimized architecture for real-time data ingestion, processing, and querying.

• High Scalability & Performance

  Supports elastic scaling, high concurrency, and low-latency queries, suitable for demanding enterprise applications.

• Multi-Cloud & Deployment Flexibility

  Available on AWS, Azure, GCP, or self-managed, with support for hybrid cloud and on-premise environments.

• Built-in AI & Vector Search

  Offers native vector search capabilities for AI-powered applications, including fast K-NN and approximate nearest neighbor searches.

• Developer-Friendly SQL & Compatibility

  ANSI SQL compliant with MySQL wire protocol support, enabling easy integration with existing tools and workflows.

Use Cases

• Real-Time Business Intelligence : Power dashboards and analytics that require instant data updates for decision-making in finance, eCommerce, and more.
• AI & Machine Learning : Support for vector search and fast data retrieval accelerates AI model training and inference workflows.
• Fraud Detection & Security : Real-time analysis of streaming data for threat detection, anomaly detection, and security monitoring.
• Operational Analytics : Monitor and analyze IoT sensor data, logs, and other time-series data for predictive maintenance and operational insights.
• Customer Personalization : Leverage real-time data to deliver personalized recommendations and marketing campaigns.
• Hybrid Workloads : Handle complex workloads combining transactional and analytical processing across cloud and on-prem environments.

FAQs