Hotdata offers a fully managed platform that handles massive‑scale search and query workloads for developers, combining object storage, vector search, OLAP, top‑k, and geospatial capabilities in a single query interface. Built with Rust, Apache Arrow, and DataFusion, it lets users create databases, load data, and define indexes via a simple CLI or API, with transparent pricing based on storage and bytes scanned. The service can run in Hotdata’s cloud or be deployed in a user’s own environment.
Funding
Funding not disclosed
Founders
Product
Problem
Developers building AI agents and data‑intensive applications must stitch together multiple storage systems, search engines, vector databases, and analytics tools, leading to high latency, operational complexity, and difficulty creating temporary, composable data pipelines.
Solution
Hotdata provides a fully managed, Rust‑based execution layer that unifies object storage, SQL analytics, vector search, full‑text search, geospatial queries, and time‑series operations behind a single low‑latency API. Users can create databases in milliseconds, load Parquet files directly, and run hybrid queries that combine traditional OLAP with top‑k and vector similarity without managing separate services. The platform charges only for stored data and bytes scanned per query, enabling cost‑effective scaling to billions of rows. Hotdata can be deployed as a managed cloud service or self‑hosted in a private environment, and integrates via a CLI, HTTP API, and language SDKs for seamless automation within AI agents.
Target Audience
Primary customers are developers and data teams building AI‑native applications, autonomous agents, and analytics platforms that require fast, composable access to heterogeneous data sources.
Features
- Unified query engine built on Apache Arrow and DataFusion, supporting SQL, vector, full‑text, and geospatial queries in a single statement
- On‑demand managed databases that can be created, loaded with Parquet files, and torn down instantly
- Pay‑as‑you‑go pricing based solely on storage size and bytes scanned per query
- Rust‑native performance with low latency for both analytical and nearest‑neighbor workloads
- CLI and HTTP API for easy integration into scripts, notebooks, and autonomous agents
- Option to run the service fully managed or self‑hosted in any cloud or on‑premises environment
- Built‑in indexing (BM25, ANN) and caching of sub‑queries to accelerate repeated access patterns