Serverless Redis, Kafka, and vector database
Upstash provides serverless Redis, Kafka, and vector database services with per-request pricing and zero operational overhead. Redis supports global replication for edge computing. Kafka offers pay-per-message event streaming. QStash provides HTTP-based message queues for serverless. Features REST APIs alongside native protocols, ideal for edge and serverless deployments. Integrates with Vercel, Cloudflare Workers, and AWS Lambda natively.
Serverless data services for modern serverless and edge architectures.
Redis with per-request pricing and global replication. Kafka with per-message pricing. QStash for HTTP queues.
Upstash Vector for serverless embeddings. REST APIs alongside native protocols.
Native integration with Vercel, Cloudflare Workers, AWS Lambda.
Freemium serverless data platform (Redis, Kafka, Vector, QStash). Free tier includes daily command/request quotas (10k commands/day for Redis/Kafka/Vector, 500 messages/day for QStash at $0/mo). Pay-as-you-go charges per request ($0.20-$0.40 per 100k requests) and storage ($0.25/GB/mo) with scale-to-zero idle compute. Pro fixed plans start at $280/mo with dedicated throughput and 99.99% SLA, and Enterprise plans provide dedicated VPC peering and custom compliance.
full pricing breakdown →API, REST, Serverless
Embedded vector database for multimodal AI with petabyte scale
LanceDB is an open-source embedded vector database built on the Lance columnar format for multimodal AI. It delivers near in-memory performance from disk with zero-copy architecture, supporting vector search, full-text search, and SQL. Native SDKs for Python, TypeScript, and Rust integrate with LangChain, LlamaIndex, and DuckDB. Backed by a $30M Series A, used by Harvey AI and Runway, with 18,000+ GitHub stars.
Serverless vector and full-text search on object storage
turbopuffer is a serverless vector and full-text search engine built on object storage and vendor-positioned as roughly 10x cheaper than traditional vector databases. Used by Anthropic, Cursor, Notion, and Atlassian for production search workloads. Official site reports 4T+ documents, 10M+ writes/s, and 25k+ queries/s in production systems. Funded by Thrive Capital.
Fully managed RAG-as-a-Service platform for enterprise AI applications
Ragie is a managed retrieval-augmented generation platform that handles document ingestion, indexing, and retrieval so developers can build grounded AI applications without managing vector databases or chunking pipelines. It connects to Google Drive, Notion, Slack, Confluence, and other enterprise data sources with simple APIs for hybrid search and entity extraction.
Verification dates are editorial checks. Routine CMS saves and automatic updatedAt timestamps do not advance them.
Upstash provides serverless Redis, Kafka, and vector database services with per-request pricing and zero operational overhead. Redis supports global replication for edge computing. Kafka offers pay-per-message event streaming. QStash provides HTTP-based message queues for serverless. Features REST APIs alongside native protocols, ideal for edge and serverless deployments. Integrates with Vercel, Cloudflare Workers, and AWS Lambda natively.
Upstash offers a free tier alongside paid plans. Freemium serverless data platform (Redis, Kafka, Vector, QStash). Free tier includes daily command/request quotas (10k commands/day for Redis/Kafka/Vector, 500 messages/day for QStash at $0/mo). Pay-as-you-go charges per request ($0.20-$0.40 per 100k requests) and storage ($0.25/GB/mo) with scale-to-zero idle compute. Pro fixed plans start at $280/mo with dedicated throughput and 99.99% SLA, and Enterprise plans provide dedicated VPC peering and custom compliance.
Yes — Upstash is active. Its listing was last verified on September 6, 2026.
The first editor-selected Upstash alternatives are LanceDB, turbopuffer, Ragie.
The published editorial review lists Upstash at 93/100 overall across speed, privacy, and developer experience. Check the review's evidence status and test metadata for its verification level.
computed discovery: shared active categories
Serverless Postgres
Serverless Postgres platform separating storage and compute for branching, autoscaling, read replicas, instant restore, and scale-to-zero workloads. Neon works with standard PostgreSQL clients and ORMs, supports extensions such as pgvector, and sits inside a broader Neon backend platform with Auth, Data API, Functions, Object Storage, and AI Gateway features.
The open-source Firebase alternative
Open-source Firebase alternative providing a full backend-as-a-service on PostgreSQL. Auto-generated REST and GraphQL APIs from your schema, real-time subscriptions, built-in auth with 20+ social providers and Row Level Security, S3-compatible file storage with CDN, and Deno-powered Edge Functions. Visual dashboard with SQL editor and table editor. Supports pgvector for AI apps. Self-hostable or managed with a generous free tier. 75K+ GitHub stars.
TypeScript ORM that feels like SQL
Lightweight, serverless-ready TypeScript ORM with zero dependencies bringing SQL-like syntax into TypeScript for maximum type-safety. Maps queries closely to raw SQL with full auto-completion and type inference. Features Drizzle Kit for migrations, Drizzle Studio for visual browsing, supports PostgreSQL, MySQL, SQLite, and Turso. Runs on Node.js, Bun, Deno, Cloudflare Workers, and Vercel Edge. 26K+ GitHub stars, growing fast as a Prisma alternative.
High-performance vector database written in Rust for similarity search at scale.
Qdrant is a high-performance vector similarity search engine and database written in Rust. Designed for production-grade AI applications with advanced filtering, payload indexing, and distributed deployment. Supports billion-scale vector collections with sub-second query times. Popular choice for RAG, recommendation systems, and anomaly detection.
Fully managed vector database built for AI applications at production scale.
Pinecone is a leading managed vector database designed for high-performance similarity search at scale. Purpose-built for AI applications including RAG, recommendation systems, and semantic search. Offers managed serverless infrastructure with automatic scaling, filtering, hybrid retrieval, and namespacing. No infrastructure management required.
High-performance OLTP graph-vector database in Rust built on object storage for AI memory
HelixDB is an open-source, unified graph-vector database engineered in Rust that merges relational, graph, and vector workloads into a single OLTP engine, using LMDB local caching and S3 object storage for scalable agent memory.
