SingleStore
Distributed SQL database platform optimized for real-time analytics and transactional workloads, supporting multi-model data types and high scalability.
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Product Overview
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
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