Lightning+ is a high-performance, in-memory data server designed to eliminate latency bottlenecks in Agentic AI implementations. It provides real-time, structured data retrieval with millisecond response times, enabling faster reasoning and action for AI agents. The platform offers fixed per vCPU pricing and supports deployment across cloud, on-premise, or edge environments without vendor lock-in.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents and analytics workflows require rapid access to structured data, but accessing and preparing data from diverse sources can be slow and complex, creating a bottleneck. Existing cloud-based solutions often incur high egress fees and consumption-based pricing, making them economically unsustainable for real-time applications.
Solution
DADOS Technology offers Lightning+, an in-memory data server designed for real-time AI-native data retrieval. Lightning+ connects to various data sources via zero-copy, parallel, multi-threaded streaming, materializing data as Arrow in-memory tables. Its query engine, built on DuckDB and Arrow, supports SQL-compliant queries with millisecond latency, enabling AI agents to retrieve, reason, and act without delay. Lightning+ can be deployed on cloud, on-premise, or at the edge, and delivers structured answers in Arrow, JSON, CSV, or Markdown formats.
Target Audience
The primary audience includes AI application developers and data scientists who require real-time data access for AI agents and analytics workloads.
Features
- Connects to diverse data sources, including APIs, files, databases, and cloud storage, using zero-copy, parallel, multi-threaded streaming
- Materializes data as Arrow in-memory tables for rapid query execution
- Employs a fully SQL-compliant query engine built on DuckDB and Arrow, supporting joins, unions, subqueries, window functions, filters, aggregations, and derived fields
- Delivers query results in Arrow, JSON, CSV, or Markdown formats
- Supports stateless execution, ensuring data security and compliance
- Enables session reuse, minimizing cloud consumption and egress costs
- Supports real-time data sources, such as updated files and streaming APIs
- Can be deployed on cloud, on-premise, or at the edge using Docker containers