Resources

Events

• [6th MLOps World Summit] Inside the Foundational Data Layer | The Next Wave of AI
• [Data Systems for AI] Foundational Data Layer For The AI Era
• [IRL Hackathon] Multimodal AI Agents - 2 day Hackathon
• [OSS4AI SF] What Makes a Multimodal Database? - Excerpt from Awesome AI Dev Tools September
• [AI Innovation Summit '24] Building AI Databases: Insights on Vector and Graph Solutions
• [AIQCon '24] Why You Can't Ignore Foundational Data Systems When Building Reliable
• [GenAI Zoo '24] A Database for Multimodal AI
• [2024 DataConnect Conference Start Up Showcase] Database for Multimodal AI
• [OSS4AI] Tuesday Tech Talks: Multimodal Search for Generative AI
• [ApertureData] ApertureData Youtube channel
• [AICamp] Are Vector Databases Enough for Multimodal Data ; [Slides]

Customers & Partners

• [Industry Experts] State Of The Union: AI In 2025 And Its Future, From Leaders In The Industry
• [User Contribution] Engineering the Memory Layer For An AI Agent To Navigate Large-scale Event Data - Part 1
• [User Contribution] Engineering An AI Agent To Navigate Large-scale Event Data - Part 2
• [User Contribution] How Multimodal Vector Databases Are Transforming Challenges Across Industries (Multimodal RAG)
• [User Contribution] Automating Knowledge Graph Creation with Gemini and ApertureDB - (GraphRAG) Part 1
• [User Contribution] Automating Knowledge Graph Creation with Gemini and ApertureDB - (GraphRAG) Part 2
• [User Contribution] Automating Knowledge Graph Creation with Gemini and ApertureDB – (GraphRAG) Part 3
• [User Contribution] Automating Knowledge Graph Creation with Gemini and ApertureDB – (GraphRAG Evaluation) Part 4
• [User Contribution] Beyond Vanilla RAG: Unlocking Enhanced Retrieval with GraphRAG and ApertureDB
• [Data Systems for AI] Multimodal Madness Panel
• [Badger Tech] Badger Technologies Uses ApertureDB to Solve "Wrong Product" Placement Problems at Scale
• [CoffeeBlack.ai] Building a VLM Agent to Automate Desktop Tasks with ApertureDB
• [Addy AI] Why Addy AI Switched from QDrant to ApertureDB
• [User Contribution] Agentic RAG with ApertureDB and HuggingFace SmolAgents
• [Realm Labs] Is Your ChatBot Secure?
• [AIMon] How to improve the accuracy of your RAG-LLM chatbot with AIMon [Python, ApertureDB, LlamaIndex]
• [Twelve Labs] Managing Video Data with ApertureDB and Twelve Labs
• [OSS4AI] RAG Overview - Example built with ApertureDB vector search
• [OSS4AI] RAG Workshop: Optimization - Example built with ApertureDB vector search
• [OSS4AI] RAG Workshop: Agentic RAG - Example built with ApertureDB vector search
• [User Contribution] Semantic Search to Glean Valuable Insights from Podcast - 3 Part Series
• [AIMon] A Quick Comparison of Vector Databases for RAG Systems
• [Intel] Seeing Further Down the Visual Cloud Road
• [Intel] Overcoming Visual Analysis Paralysis
• [Intel] Visual Data: Pack Rat to Explorer

Newsletter

• [ApertureData] Multimodal AI In Real World - Subscribe on LinkedIn

Lunch & Learn

• [Community] RAG to GraphRAG — Smarter AI Retrieval
• [Realm Labs] Secure Your Agentic RAG Chatbots With Realm Labs & ApertureDB
• [Community] Chat With Your Unstructured Data On ApertureData
• [ApertureData] Launch Your AI Project Today With ApertureDB Multimodal AI Workflows
• [AIMon] Crack the Code to Higher RAG Relevancy: The AIMon & ApertureData Solution
• [Twelve Labs] Build a Powerful Semantic Video Search Engine With Twelve Labs and ApertureDB

Blogs

• [News] Reflecting on 2025: ApertureData's Journey and What's Next for Multimodal AI Data Management And Agent Memory in 2026
• [Agents] Smarter Agents Start with Smarter Data
• [Agents] Your Smart AI Agent Needs A Multimodal Brain
• [Agents] Smart AI Agents In the Wild
• [Query Interface] Beyond SQL: The Query Language Multimodal AI Really Needs
• [Product] ApertureDB and AI Workflows: Building Blocks of Multimodal AI Applications
• [Multimodal AI] What Does Multimodality Truly Mean For AI?
• [Knowledge Graphs] The Misunderstood World of Knowledge Graphs
• [News] Reflecting on 2024: ApertureData's Journey and What's Next for Multimodal AI Data Management in 2025
• [RAG / Agents] Building Real World RAG-based Applications with ApertureDB
• [Experts Panel] Insights and Musings from the Grace Hopper Panel: Navigating Conflicts and Synergies in Multimodal AI Across Industries
• [Engineering] Why AI Teams Need A Cloud-Agnostic Database
• [Engineering] Lessons Learned Building a Cloud-Agnostic Database
• [RAG] Can A RAG Chatbot Really Improve Content?
• [Product] ApertureDB Now Available on DockerHub
• [Engineering] Vector Databases and Beyond for Multimodal AI: A Beginner's Guide Part 1
• [Engineering] Vector Databases and Beyond for Multimodal AI: A Beginner's Guide Part 2
• [Engineering] Why Do We Need A Purpose-Built Database For Multimodal Data?
• [Engineering] Your Multimodal Data Is Constantly Evolving - How Bad Can It Get?
• [Cost] How a Purpose-Built Database for Multimodal AI Can Save You Time and Money
• [Industrial & Visual Inspection] Accelerate Industrial and Visual Inspection with Multimodal AI
• [Life Sciences] Challenges and Triumphs: Multimodal AI in Life Sciences
• [Retail] Transforming Retail and E-commerce with Multimodal AI
• [Engineering] Are Vector Databases Enough for Visual Data Use Cases?
• [Product] What's in Your Visual Dataset?
• [Engineering] ApertureDB 2.0: Redefining Visual Data Management for AI
• [News] Building a Specialized Database for Analytics on Images and Videos
• [Product] Minute-Made Data Preparation with ApertureDB
• [Engineering] Managing Visual Data for Machine Learning and Data Science. Painlessly.

Tutorials

• [Integration] RAG ChatBot with LangChain and ApertureDB
• [Multimodal vector search] Find Matching Faces: Metadata and Vector Search in ApertureDB
• [Setup Options] Setup ApertureDB to Manage Data as Needed
• [Community edition setup] Setup Guide for ApertureDB Docker
• [Setup Options] Setup ApertureDB Communication to Navigate Around Your Data
• [Configuration] Configure ApertureDB Communication to Suit Your Environment
• [Datacamp] Simplifying Image Recognition using ApertureDB and Python
• [ApertureDB query fundamentals] Start with Basics
• [Complex data ingestion] Manage Multimodal Datasets
• [Regions of interest] Bounding boxes, polygons, and IoU examples
• [Video clips and frames] Clips and Frames in Videos
• [Multimodal vector search] Image Similarity Search
• [PyTorch classification] Image classification with PyTorch
• [Tensorflow training] Train a model using data from ApertureDB

Videos

• [Summer of Workflows] Demo of Croissant Ingestion Workflow on ApertureDB Cloud
• [Summer of Workflows] Demo of MCP Server Workflow on ApertureDB Cloud
• [Summer of Workflows] Demo of Bucket Ingestion Workflow on ApertureDB Cloud
• [Summer of Workflows] Website Chatbot Workflow on ApertureDB Cloud
• [Summer of Workflows] Generate PDF Embeddings Workflow Demo
• [Summer of Workflows] Ingest Multimodal Data from PostgreSQL database into ApertureDB in Minutes | AI Workflow Demo
• [Summer of Workflows] Query ApertureDB with SQL | SQL Server Workflow Demo
• [Summer of Workflows] Object Detection with ApertureDB Workflows | Multimodal AI Made Simple
• [Summer of Workflows] Face Detection & AI Similarity Search in Minutes with ApertureDB
• [Summer of Workflows] ApertureDB + Label Studio Workflow | Fast Image Labeling for AI & ML
• [Summer of Workflows] Extract Text from Images & PDFs Workflow on ApertureDB
• [Summer of Workflows] Embedding Generation for Videos | ApertureDB Workflow Demo | Semantic Video Search & AI
• [Workflows] Introducing ApertureDB Multimodal AI Workflows
• [Intro] Data science challenges in extracting value from image and video based data
• [Business intro] How does a purpose built database for analytics on images and videos benefit your organizations?
• [E-commerce intro] E-commerce Data Science Needs Sophisticated Visual Data Management
• [Demo] Find Matching Faces: Metadata and Vector Search in ApertureDB
• [Demo] How do you find what’s in your image or video datasets?
• [Multimodal Weekly 2023] Are Vector Databases Enough for Visual Data Use Cases? A Demo
• [Data Council 2022] Just Because Your Data Is Unstructured Doesn’t Mean it Should be Onerous.
• [CMU Database Group 2022] ApertureDB: Designing a Purpose-built System for Visual Data and Data Science

Podcasts

• [Tech Field Day Plus] Moving Beyond Text for Agentic AI Applications with ApertureData
• [XTRAW AI] Can Your AI Handle the Future of Multi-Modal Data?
• [Data Product Management in Action] Minisode on Simplifying Life of Data and ML Teams
• [AI Chronicles] Transforming Data Challenges into Entrepreneurial Triumphs

Github

• AI workflows repository
• Our Python client repository
• Our Cookbook dataset repository
• Our application examplesrepository

Academic Papers

• [Very Large Data Bases 2021 (VLDB 21)] Using VDMS to Index and Search 100M Images
• [Hot Topics in Edge Computing (HotEdge 19)]Navigating the Visual Fog: Analyzing and Managing Visual Data from Edge to Cloud
• [Workshop on Systems for Machine Learning at NIPS 2018] VDMS: An Efficient Big-Visual-Data Access for Machine Learning Workloads
• [Workshop on HotStorage at USENIX ATC 2017] Addressing the Dark Side of Vision Research: Storage

News

• [ApertureData] ApertureDB is Now Available on Google Cloud Marketplace
• [VentureBeat] ApertureData offers 10x speed boost to enterprises using multimodal data
• [TechCrunch] ApertureData is building a database focused on images with $3M seed
• [2048.vc] 2048 Ventures: Our Investment in ApertureData
• [Business Insider] 32 startups in the red-hot 'new data stack' being built around Snowflake and Databricks that are poised to explode in 2021
• [VentureBeat] Second Transform 2019 AI showcase highlights people and processes