Mixpanel Reviews

1. Deepak Kumar

   | Technical Reviewer at A/B Testing | over 3 years ago
   Mixpanel helps track user behavior and measure success for your application

   I recommend Mixpanel to anyone who needs to do tracking of user behavior in web applications in order to measure against goals.

   🏁 Competitors: VWO, Optimizely, Convertize.io, Picreel

   👍 Pros:    Easy to use|Powerful analytics|Tracks every user actions

   👎 Cons:    Dashboard is complex|Pricing is too high|Hard to implement own data

Apache Arrow Reviews

Mixpanel mentions (22)

• A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev

  Mixpanel — 100,000 monthly tracked users, unlimited data history and seats, US or EU data residency. - Source: dev.to / 4 months ago

• What do I do after ProductHunt?

  You can test sales copy with Mixpanel to see where your traffic is coming from so you can see which content (Informative or promotional) generates the most engagement. Source: 7 months ago

• Essential Product Metrics Every Startup Founder Should Know

  Custom Data Collection As you grow you can consider a bit more precise configurations and data analytics approachs. Implement custom data collection through or event tracking for example via Mixpanel. This allows you to capture specific metrics tailored to your product's unique needs. - Source: dev.to / 12 months ago

• What issues / painpoints have you experienced with current Analytics Platforms? Mixpanel, Plausible etc.

  I am looking into whether you have experienced any pain points or issues not solved by current analytics platforms. By current solutions I'm talking plausible.io, mixpanel.com, usermaven.com and alike, providing features such as: total visitors, page views, online users, custom events tracking, top sources. Source: over 1 year ago

• Ask HN: What’s your startup’s analytics setup? (2023)

  Ten years ago, there was a popular Ask HN: "what's your startup’s analytics setup?” [0]. Like the poster then (malandrew), I have the same problem in 2023: Selecting analytics solutions for the startup I'm working at has proven to be more daunting than I imagined. There are many services to choose from and it's not immediately obvious how you should choose from the many offerings to get not only complete analytics... - Source: Hacker News / over 1 year ago

Apache Arrow mentions (34)

• Arrow Flight SQL in Apache Doris for 10X faster data transfer

  Apache Doris 2.1 has a data transmission channel built on Arrow Flight SQL. (Apache Arrow is a software development platform designed for high data movement efficiency across systems and languages, and the Arrow format aims for high-performance, lossless data exchange.) It allows high-speed, large-scale data reading from Doris via SQL in various mainstream programming languages. For target clients that also... - Source: dev.to / 15 days ago

• How moving from Pandas to Polars made me write better code without writing better code

  In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++. - Source: dev.to / 3 months ago

• Time Series Analysis with Polars

  One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on... - Source: dev.to / 6 months ago

• TXR Lisp

  IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/. - Source: Hacker News / 6 months ago

• A Polars exploration into Kedro

  Polars is an open-source library for Python, Rust, and NodeJS that provides in-memory dataframes, out-of-core processing capabilities, and more. It is based on the Rust implementation of the Apache Arrow columnar data format (you can read more about Arrow on my earlier blog post “Demystifying Apache Arrow”), and it is optimised to be blazing fast. - Source: dev.to / about 1 year ago