Observed Signal · Nov 4, 2026 · Technical Release · Source: https://martechseries.com/feed/ · Impact: 1/5 · Sentiment: Positive
Percona Launches Search for MongoDB with Local Embeddings
Percona, a provider of open source database software, has announced the general availability of Percona Search for MongoDB. This new offering enables organizations to run full-text, vector, and hybrid search within their own infrastructure, without relying on external services for embedding generation. The solution integrates with Percona Server for MongoDB and the Percona Operator, allowing teams to deploy and scale search alongside their database. It supports local embedding providers like Ollama, vLLM, and LocalAI, as well as hosted options such as OpenAI and Azure OpenAI. Key features include local-first embedding generation, no vendor lock-in, support for air-gapped environments, and enterprise security. Percona plans to extend backup and monitoring support to the search layer in the future.
This is a niche technical product launch by a database services provider, relevant to infrastructure but not directly impacting the AdTech/MarTech industry at large.
Track Real-Time Infrastructure Signals & Market Shifts
Polaris7 autonomous intelligence agents track regulatory filings, primary sources, executive changes, and deal flow 24/7. Create your Polaris7 workspace to monitor these entities.
Key Takeaways & Evidence Grounding
- Percona announced general availability of Percona Search for MongoDB.
- The solution enables full-text, vector, and hybrid search within customer infrastructure.
- It supports local embedding providers (Ollama, vLLM, LocalAI) and hosted options (OpenAI, Azure OpenAI, Hugging Face).
- Integration with Percona Operator is available; backup and monitoring support are planned.
- Targeted at self-managed MongoDB environments with strict data-residency requirements.
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Azure Cosmos DB launches Integrated Embeddings Public Preview
Microsoft announced the public preview of Integrated Embeddings for Azure Cosmos DB, a feature that automatically generates and maintains vector embeddings as items are inserted or updated. Developers configure embeddings via a new embeddingSource block in the container vector policy, selecting source properties, a Microsoft Foundry embedding model deployment, and an output vector path. The preview supports Azure OpenAI embedding models deployed through Microsoft Foundry (text-embedding-3-small, text-embedding-3-large, text-embedding-ada-002) and uses Microsoft Entra authentication. Initial SDK support includes the Azure Cosmos DB SDK (Python) with key-based auth and the management SDK (Python/JavaScript) with Entra ID; Azure Portal configuration is not yet available. Microsoft provides a sample Python app and a LangChain-based RAG walkthrough. Costs are limited to Foundry inference calls and Cosmos DB request units for change-feed reads/writes.
LocalFind Gemma: Local AI Semantic Search for Files
LocalFind Gemma is an open-source, local-first semantic search and conversational assistant for personal files (documents, images, audio). The project uses Google’s Gemma 4 models running via Ollama for image captioning and agent reasoning, Whisper for audio transcription, ChromaDB for vector storage, and the nomic-embed-text-v2-moe embedding model for multilingual embeddings. Image captioning occurs at index time and is stored in ChromaDB to avoid repeated inference; the conversational agent (recommended model gemma4:e4b) can read images via Ollama’s vision API to answer questions directly. All core components are designed to run locally on the user’s machine, with an optional Claude Desktop integration via MCP for users who opt to share files with a third party. Published May 23, 2026.
Microsoft Open-Sources OmniVec Embedding Platform
Microsoft (Azure Cosmos DB team) open-sourced OmniVec, a platform to build and operate embedding pipelines that keep vector representations of operational data in sync. OmniVec lets users register sources, embedding models, destinations (vector stores) and pipelines; it handles backfill, change tracking, model invocation, retries and writes to vector stores. The release includes support for Azure Cosmos DB, PostgreSQL, SQL Server (source and destination) and Azure Blob Storage (destination). OmniVec is deployed into an Azure subscription and provisions AKS, an Azure Cosmos DB metadata store and an ACR; it can call hosted Azure OpenAI models or self-hosted GPU models. The project is available on GitHub (AzureCosmosDB/OmniVec) and is published as a public preview.
Receive all future signals for Infrastructure in your executive briefing
Never miss material M&A deals, leadership changes, account wins, or product rollouts. Polaris7 monitors 20,000+ primary sources 24/7, delivering verified telemetry directly into your executive briefing.