What AI says about Redis
Redis is an in-memory data platform that supports vector search, semantic caching, and real-time feature stores. It comes up for buyers seeking low-latency vector databases, hybrid search on-premises, and tools to cache LLM responses.
AI calls itin-memory,fast,high-performance,low-latency,ultra-low latency,high-speed
Since Jul 5Updated Nov 11, 2026Based on 25,999 AI answers
Reviewed by Dimitry Apollonsky
Mentioned in · Public index
3%
of AI answers about Redis and its rivals · since Jul 5
Based on 25,999 AI answers
- ChatGPT3%
- Google AI Mode3%
How often AI mentions Redis
of AI answers about Redis and its rivals
Track your brand free to see 13 weeks of history.
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Sep 14OctNov 2
- · ChatGPT switched to GPT-6 Luna
Redis products in AI answers
Markets where AI mentions Redis
Mentioned inLowHighFew answers
All marketsChatGPTGoogle AI Mode
- LLM Security and Governance PlatformsChatGPTGoogle AI Mode
- Machine Learning Feature Store PlatformsChatGPT
- Vector Database PlatformsGoogle AI Mode
- Developer Backend & Vector Search ServicesGoogle AI Mode
- Managed Streaming and Messaging PlatformsGoogle AI Mode
- Kubernetes and Container Platform ToolsChatGPT
- Database DevOps and Monitoring ToolsOutside both engines’ top 25
- Fleet Dispatch and Safety SoftwareOutside both engines’ top 25
- Cloud-Native API & Networking PlatformsOutside both engines’ top 25
- LLM Agent Frameworks and ToolingOutside both engines’ top 25
- Enterprise Headless E-commerce PlatformsOutside both engines’ top 25
- Managed Cloud Database ProvidersOutside both engines’ top 25
Topics where AI mentions Redis
TopicMentioned in · on this topicRank
- Budget global key-value caching service
- Serverless global key-value session cache
- Managed message queues
- Affordable managed Redis clusters
- Vector database for generative AI
- Managed vector databases for production RAG
- Self-hosted open source vector database
- Access-controlled semantic search
- Multi-tenant vector isolation
- DevOps agent framework for self-healing systems
- Backend as a service with vector search
- Scalable URL shortener API with custom domains
- Agent memory integration
- RAG pipeline development platform
- Batch and real-time feature store
- Conversational AI chatbot development
- Containerized development environment
- Multi-step stateful task management
- Monitoring platforms with generous custom automation API access
- Least-cost payment routing
- Time-filtered vector analysis
- Hybrid vector and keyword search
- Proxy rotation tools for large-scale scraping
- High-performance API development
- Vector-based recommendation AI for conversion
- Visual search API with custom embedding support
- GIS platform API for complex queries
- Queue streaming platforms for event-driven apps
- Data warehouse activation
- Human-in-the-loop Python orchestration libraries
- LLM integration into existing applications
- Workflow engine for long-running processes
- Conversational AI agent framework
- Contact enrichment API
- Human-in-the-loop task orchestration
- Web research agent frameworks
- Real-time chat APIs
- RAG evaluation
- Serverless edge computing
- API gateways
- PII redaction for LLM pipelines
- Production-grade NLP inference API platform
- High-concurrency dashboard analytics
- Developer forum platforms
- Self-hosted whiteboard access
- Hosted cron job scheduling
- E-commerce platform scalability
- Breaking-news push alerts
- Default-secure cloud infrastructure for startups
- AI model API gateway
- Enterprise AI inference serving
- Image similarity search APIs
- Cloud development environments
- Backend-as-a-service platforms
- Cloud server rental
- Self-hosted open-source LLM management platform
- Multi-agent orchestration
- Supervised AI tutoring
- LLM knowledge graph databases
- Storage certification training
- Most mentionedMentioned in
- My goal is to cache LLM responses to reduce latency and cost. What's the best semantic caching solution?on this questionGPTCache is the most-mentioned brand67%
Excerpts where Redis appeared in the AI's answer
Google AI ModeOct 15, 2026, Google AI Mode Redis Semantic Cache (via LangChain) : Best for teams already running Redis infrastructure
Google AI ModeSep 18, 2026, Google AI Mode Redis / Valkey : Best for self-hosted, high-performance infrastructure.
- I am planning to optimize our token usage costs. Who offers LLM caching and semantic caching tools?on this questionGPTCache is the most-mentioned brand59%
- I need a vector database that runs in-memory for speed and does not rely on SSD storage.on this questionQdrant shares the lead for mentions with 3 more37%
- what is the best database?on this questionMongodb shares the lead for mentions with 2 more90%
Excerpts where Redis appeared in the AI's answer
ChatGPTSep 20, 2026, ChatGPT Redis — primarily for caching, sessions, queues, and very fast key/value operations rather than as your main relational database.
Google AI ModeAug 31, 2026, Google AI Mode Redis: Best in-memory data store for ultra-low latency caching, session management, and real-time leaderboards.
- How do I cut my model bill with caching and smart routing between cheap and premium models?on this questionOpenAI is the most-mentioned brand14%
- I need a proxy that caches LLM responses (semantic caching) to reduce API costs.on this questionLiteLLM is the most-mentioned brand43%
Excerpts where Redis appeared in the AI's answer
ChatGPTOct 25, 2026, ChatGPT Open-source gateway with semantic caching through Redis, Valkey, or Qdrant.
Google AI ModeSep 10, 2026, Google AI Mode Requires a vector/cache database backend like Redis or Qdrant to compute and store prompt vectors.
Redis in AI answers
1 of 8
I need a proxy that caches LLM responses (semantic caching) to reduce API costs.
ChatGPTChatGPT· Oct 25, 2026
Open-source gateway with semantic caching through Redis, Valkey, or Qdrant.
Google AI ModeGoogle AI Mode· Sep 10, 2026
Requires a vector/cache database backend like Redis or Qdrant to compute and store prompt vectors.
Sites AI cites
- Your site30%
- Comparing the best open source vector databases (2026) (opens in a new tab) · 3%Leaves Redis out
- Redis semantic cache | Docs (opens in a new tab) · 3%
- LLM Token Optimization: Cut Costs & Latency in 2026 (opens in a new tab) · 3%Leaves Redis out
- Redis - Real-time data for agents & apps (opens in a new tab) · 2%Leaves Redis out
- Best Vector Database: Dedicated vs Integrated Solutions (opens in a new tab) · 1%Leaves Redis out
- What is Semantic Caching? A Complete Guide (opens in a new tab) · 1%
- What is semantic caching? Guide to faster, smarter LLM apps (opens in a new tab) · 1%
- Benchmarking results for vector databases | Redis (opens in a new tab) · 1%Leaves Redis out
- Redis LangCache | Docs (opens in a new tab) · 1%
- Vector database 101: Factors to consider when choosing a vector database (opens in a new tab) · 1%
- Leaves Redis out4%
- Powerful Alternatives to SQL that Will Revolutionize Database Management (opens in a new tab) · <1%
- How I Reduced LLM Costs by 75% Using Caching (opens in a new tab) · <1%
- Agentic AI: How to Save on Tokens | by Ida Silfverskiöld | Data Science Collective | May, 2026 | Medium (opens in a new tab) · <1%
- ⚡ Best Caching Tools Every Developer Should Know in 2025 | by TechByAL | Medium (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%Leaves Redis out
- Event-Driven Architecture in Java: What It Actually Is and When You Should Use It (opens in a new tab) · <1%
- Building a Semantic Search Engine with Vector Databases: A Practical Guide (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%Leaves Redis out
- Practical optimizations and alternate strategies for high-performance, scalable, Laravel based… (opens in a new tab) · <1%
- LLM Cost Optimization. Optimizing LLM costs is crucial for… | by Bijit Ghosh (opens in a new tab) · <1%
- Leaves Redis out4%
- Cut Your LLM Costs and Latency up to 86% with Semantic Caching | Databases for AI (opens in a new tab) · 1%
- Make LLM Agents Faster and Cheaper with Semantic ... (opens in a new tab) · <1%
- Is Your Vector Database Really Fast? (opens in a new tab) · <1%
- Building Smarter AI Agents: Memory Management with AgentCore (opens in a new tab) · <1%
- Cut Your LLM Costs and Latency up to 86% with Semantic ... (opens in a new tab) · <1%
- Top 15 Vector Databases for AI Builders in 2026 | Pinecone, Milvus, Qdrant, Chroma & More (opens in a new tab) · <1%Leaves Redis out
- Vector Database Explained for AI Agents & RAG Systems (opens in a new tab) · <1%
- What’s new with Memorystore: How Redis provides speed, reliability, ease of use, and lower costs - YouTube (opens in a new tab) · <1%
- AI Cost and Token Optimization Tutorial (in Claude Code ... (opens in a new tab) · <1%
- Introducing Temporal Similarity Search for Vector Databases (opens in a new tab) · <1%
- 4%
- Reddit - Prove your humanity (opens in a new tab) · 1%
- Open source vs proprietary vector database? (opens in a new tab) · 1%
- AI agent memory that doesn't suck - a practical guide (opens in a new tab) · <1%
- Dummy question - how can I build in vector search solution without a cloud database? (opens in a new tab) · <1%
- What are people actually using for long term agent memory? (opens in a new tab) · <1%
- which platforms offer the easiest way to manage long-term memory ... (opens in a new tab) · <1%
- How Caching Saved Us Hundreds of Dollars in AI Costs Every Month (opens in a new tab) · <1%
- Performant architecture for user sessions - DynamoDB, ElastiCache Redis, high availability, data persistence, latency, stickiness (opens in a new tab) · <1%
- I ran a semantic caching experiment on LLM inference cost. Here are the actual numbers. (opens in a new tab) · <1%
- In 2025 what is the best realtime database? - Reddit (opens in a new tab) · <1%
- 2%
- [2411.05276] GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching (opens in a new tab) · <1%
- [2203.08323] Redis for Market Monitoring (opens in a new tab) · <1%
- [2505.05885] Cost-Effective, Low Latency Vector Search with Azure Cosmos DB (opens in a new tab) · <1%
- [2601.01885] Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents (opens in a new tab) · <1%
- Continuous Semantic Caching for Low-Cost LLM Serving (opens in a new tab) · <1%
- [2604.27707] Contextual Agentic Memory is a Memo, Not True Memory (opens in a new tab) · <1%
- MVR-cache: Optimizing Semantic Caching via Multi-Vector Retrieval and Learned Prompt Segmentation (opens in a new tab) · <1%
- Beyond Semantic Organization: Memory as Execution State Management for Long-Horizon Agents (opens in a new tab) · <1%
- Cloud and AI Infrastructure Cost Optimization: A Comprehensive Review of Strategies and Case Studies (opens in a new tab) · <1%
- LLMProxy: Reducing Cost to Access Large Language Models (opens in a new tab) · <1%
- 2%
- Cutting LLM Inference Costs by 72% with 5 Key Optimizations (opens in a new tab) · 1%
- The Real Cost of False Positives: Why Fraud Detection AI ... (opens in a new tab) · <1%
- Build smarter AI agents: Manage short-term and long-term memory with Redis (opens in a new tab) · <1%
- How to Implement Real-Time Data Synchronization in Mobile Apps for 2025 (opens in a new tab) · <1%
- Lakebase Search on Neon: your questions, answered (opens in a new tab) · <1%
- Tokens! What they actually are and why they drive your costs! (opens in a new tab) · <1%
- Understanding Messaging Queues: Examples, Necessity, and Popular Open-Source Tools (opens in a new tab) · <1%
- Vector Databases in Azure: Current State, Selection Criteria, and Benefits (opens in a new tab) · <1%
- How to reduce LLM calls by 90% with Redis | Ricardo Ferreira posted on the topic (opens in a new tab) · <1%
- 2%
- Redis: The Key to Performance and Scalability in Modern Applications (opens in a new tab) · <1%
- Introduction to Asynchronous Processing and Message Queues (opens in a new tab) · <1%
- Databases you should know as a developer - DEV Community (opens in a new tab) · <1%
- AI Recommendation Engine with Redis:Real-Time AI Innovators - DEV Community (opens in a new tab) · <1%
- Best Open Source Semantic Caching Tools for Smart LLM ... (opens in a new tab) · <1%
- Top Backend Technologies for Scalable Web Development - DEV Community (opens in a new tab) · <1%
- Building an AI-Powered Real-Time Recommendation Engine with Redis Vector Search - DEV Community (opens in a new tab) · <1%
- How to Choose the Ideal Database for Your App: Prototypes, App at Scale, and Event-Driven App - DEV Community (opens in a new tab) · <1%
- Top AI Gateways with Semantic Caching and Dynamic Routing (2026 Guide) - DEV Community (opens in a new tab) · <1%
- 🚀Introduction to Building a Micro-SaaS with Next.js 🤑 (opens in a new tab) · <1%
- Leaves Redis out1%
- Semantic Caching for LLMs: How to Cut Token Spend with AI Gateways (opens in a new tab) · <1%
- How to Optimize LLM Cost and Latency With Semantic Caching (opens in a new tab) · <1%
- Top 3 Token Optimization Techniques in 2026 (opens in a new tab) · <1%
- Top 5 AI Gateways to Reduce LLM Cost in 2026 (opens in a new tab) · <1%
- Top 5 AI Gateways with Semantic Caching to Cut LLM API Calls (opens in a new tab) · <1%Leaves Redis out
- Top 5 Enterprise AI Gateways to Eliminate LLM Rate Limiting in Production (opens in a new tab) · <1%Leaves Redis out
- Top AI Gateways for Semantic Caching in 2026 (opens in a new tab) · <1%
- Top Enterprise LLM Gateways to Optimize Token Costs with Caching and Smart Routing (opens in a new tab) · <1%
- Top Semantic Caching Solutions for AI Applications in 2026 (opens in a new tab) · <1%
