AI Databases & Vector Infrastructure

Spiral is an object-store-native data platform and database for AI research that stores and indexes high-dimensional vector embeddings, images, video, and other multimodal data, enabling machine-scale throughput from S3 directly to GPU with unified governance and granular time-bounded permissioning.

A serverless, object storage-based vector database that stores and retrieves high-dimensional embeddings at scale, supporting semantic search, RAG pipelines, and recommendation systems with low latency and high recall.

ScyllaDB Vector Search is an integrated vector similarity search feature built directly into ScyllaDB, enabling billion-scale approximate nearest-neighbor (ANN) search over high-dimensional embeddings with millisecond P99 latency — eliminating the need for a separate standalone vector database.

A compliance-native API layer and unified platform for enterprise AI workloads, offering a single REST/GraphQL interface, multi-cloud and BYOC deployment, built-in regulatory compliance (GDPR, HIPAA, PCI-DSS), an enterprise sandbox, and a plug-and-play connectors marketplace to accelerate compliant AI application development.

An AI search and data serving platform that stores and indexes high-dimensional vectors, tensors, and structured data, enabling hybrid vector and keyword search, real-time ML ranking, and retrieval-augmented generation pipelines at billions-of-document scale.

A fully managed, cloud-native analytics service built on the ClickHouse engine, offering sub-second query performance at any scale with elastic autoscaling, built-in data ingestion via ClickPipes, automated backups, monitoring, and support for AI/ML and GenAI workloads across AWS, GCP, and Azure.