Qdrant
Weaviate
Milvus
Vespa.ai
Pinecone
ElasticSearch
Zilliz
Algolia
Code42
Symantec Data Loss Prevention
Microsoft BitLocker
Paubox
OpenSSH
GravityZone
Virtru
Arcserve UDP
Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.
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Qdrant's answer
Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
Qdrant's answer
Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
Qdrant's answer
Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, Qdrant seems to be a lot more popular than Code42. While we know about 64 links to Qdrant, we've tracked only 1 mention of Code42. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you build on the JVM and want to use Qdrant, the official client is io.qdrant:client โ and it's built for Java. Every call returns a ListenableFuture, requests are assembled with protobuf builders, and it drags a gRPC/Netty stack onto your classpath. From Kotlin, that means fighting the language:. - Source: dev.to / 8 days ago
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago
Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 8 months ago
Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild. - Source: dev.to / 9 months ago
James Allsopp adds, "LangChain or LlamaIndex for managing LLM workflows, especially if you're adding vector search or documents." These tools handle multi-step processes, essential for complex apps. - Source: dev.to / 12 months ago
It's not a big surprise, given that Code42 (the parent company) pretends they have nothing to do with Crashplan. They've done a massive pivot to some kind of security company, with ZERO references to the OG product of Crashplan on code42.com, which (I'm guessing) is the bulk of their revenue. If you do a site search on google, you'll find some old links, but they just push you over to crashplan.com. Source: about 4 years ago
Weaviate - Welcome to Weaviate
Symantec Data Loss Prevention - Fully protect your data with the comprehensive detection technologies and unified policies of Symantec's industry leading Data Loss Prevention (DLP).
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Microsoft BitLocker - BitLocker is a full disk encryption feature included with Windows Vista and later.
Vespa.ai - Store, search, rank and organize big data
Paubox - Paubox provides HIPAA compliant email encryption without the hassle of extra steps.