Milvus
Pinecone
Qdrant
Weaviate
ElasticSearch
Zilliz Cloud
Vespa.ai
Apache Solr
PostHog
Mixpanel
Amplitude
Plausible.io
Google Analytics
Hotjar
Heap
LaunchDarkly
Milvus is a highly flexible, reliable, and blazing-fast cloud-native, open-source vector database. It powers embedding similarity search and AI applications and strives to make vector databases accessible to every organization. Milvus can store, index, and manage a billion+ embedding vectors generated by deep neural networks and other machine learning (ML) models. This level of scale is vital to handling the volumes of unstructured data generated to help organizations to analyze and act on it to provide better service, reduce fraud, avoid downtime, and make decisions faster.
Milvus is a graduated-stage project of the LF AI & Data Foundation.
For developers just starting out, PostHog is a free way to understand how your product is being used, without having to send any data to 3rd parties.
For enterprise customers, one data security becomes a key concern, or B2C businesses where using a SaaS solution is unaffordable, it's typical to see teams hosting an event capture platform, a data lake, and sophisticated analytics tools. The end result is that data scientists are needed and most developers don't have easy access to product intel. PostHog solves that gap - it lets everyone understand how your product is being used, without having to send data to 3rd parties, even once you have scaled to millions of visitors.
It has a JS snippet that can autocapture events, and pre-built libraries to push backend data to. Build up full user histories, visualize product trends, funnels, and run experiments with new features.
Milvus PostHogMilvus is ideal for data scientists, AI researchers, and engineers who require efficient and scalable vector search solutions. It is also recommended for companies and projects dealing with recommendation systems, image and video search, natural language processing, and more.
PostHog is particularly well-suited for product teams, developers, and startups that require deep insights into user interactions and need the flexibility of a self-hosted solution. It is also a good fit for organizations that prioritize data privacy and want to maintain full control over their data.
Based on our record, PostHog should be more popular than Milvus. It has been mentiond 72 times since March 2021. 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.
More engines. The engine abstraction is clean, adding a new one means implementing four methods (initialize, upsert, search, count). Weaviate, Chroma, and Milvus are very interesting candidates. I should evaluate if they fit the ecosystem and what they offer as peculiarity. Maybe a "plugin system" would be a good implementation to let folks implement their preferred semantic engine. - Source: dev.to / 3 months ago
Weaviate and Milvus: Additional open-source options. - Source: dev.to / 12 months ago
If you like this tutorial, show your support by giving our Milvus GitHub repo a star โญโit means the world to us and inspires us to keep creating! ๐. - Source: dev.to / over 1 year ago
Overview: Milvus is an open-source vector database designed for handling massive-scale vector data. It supports both NNS and ANNS and integrates well with various ML frameworks. - Source: dev.to / almost 2 years ago
If you enjoyed this blog post, consider giving us a star on Github and joining our Discord to share your experiences with the community. - Source: dev.to / about 2 years ago
Opus, zero nudges. Realised on its own that an abandoned signup never fires identify, triangulated the anonymous session from time, platform and registration events, decoded the PostHog replay blobs, confirmed the duplicate account in Supabase, proved the reset email never sent, and pulled the root cause out of an unmasked DOM field. One prompt in; root cause out. - Source: dev.to / 9 days ago
This is the same model that PostHog, Supabase, and dozens of other developer tools use. Open core, with a managed offering on top. - Source: dev.to / 4 months ago
Offchain: Website traffic, in-app behaviour, marketing channels, growth campaigns (Google Analytics or PostHog). - Source: dev.to / 3 months ago
--- Title: "Validate Your Startup Idea in One Weekend: Next.js + PostHog + Stripe Test Mode" Published: true Description: "A step-by-step workshop for wiring up a landing page with analytics, a waitlist, and Stripe test-mode checkout to measure real willingness-to-pay before writing product code." Tags: typescript, api, architecture, cloud Canonical_url:... - Source: dev.to / 3 months ago
Topic PostHog (Web Vitals) Apogee Watcher Primary job Product analytics OS; Web Vitals are real-user metrics from the browser Synthetic PageSpeed monitoring + CrUX in results Instrumentation Requires posthog-js on the site No script on monitored sites Metrics FCP, LCP, INP, CLS from real sessions ($web\_vitals) when capture runs Lighthouse lab + CrUX (where available) via PSI Cookieless analytics With... - Source: dev.to / 4 months ago
Pinecone - Search through billions of items for similar matches to any object, in milliseconds. Itโs the next generation of search, an API call away.
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
Qdrant - Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Amplitude - Chart Your Path to Growth with Digital Analytics
Weaviate - Welcome to Weaviate
Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure ๐ช๐บ
