![]() Support for various data types, enhanced vector search with attribute filtering, UDF support, configurable consistency level, time travel, and more. Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage and allowing you to scale both up and out. The distributed and high-throughput nature of Milvus makes it a natural fit for serving large scale vector data. MongoDB Compass is available as part of subscriptions. This means that everybody is free to use the full version of Compass, no matter if they have a commercial MongoDB or an Atlas subscription. As the GUI for MongoDB, MongoDB Compass allows you to make smarter decisions about document structure, querying, indexing, document validation, and more. With extensive isolation of individual system components, Milvus is highly resilient and reliable. Back in September, we announced that we made the source code of Compass available on Github under the SSPL and that we were making it free for all users. Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed. Simple and intuitive SDKs are also available for a variety of different languages. This tutorial’s examples will install version, the latest stable version at the time of this writing. There, find the section on the right-hand side of the page and select your desired from the drop-down menus there. ![]() ![]() ![]() With Milvus vector database, you can create a large scale similarity search service in less than a minute. To find the appropriate package for your system, navigate to the MongoDB Compass Downloads page in your web browser. Download MongoDB Compass for Mac Direct link As the GUI for MongoDB, MongoDB Compass for Mac allows you to make smarter decisions about document structure. Fuel your machine learning deployment Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models. ![]()
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