PostHog VS Qubole
Compare PostHog VS Qubole and see what are their differences
Fight user churn with great user onboarding. Interactive product tours and smart tips significantly improve your user retention.
featured
PostHog
Mixpanel
June
Amplitude
Segment
ObsidianLaunch.co
State of Product Analytics Report
Countly
Qubole
Google BigQuery
MATLAB
Amazon EMR
Snowflake
RapidMiner
Turbonomic
MicroStrategy
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.
PostHog QuboleBased on our record, PostHog seems to be more popular. It has been mentiond 46 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.
It would be a shame not to mention PostHog as the telemetry provider we are using, since it turned out to be extremely useful. Because it is hard to find people who will talk with you about your product, gathering statistics gave us a much greater insight into our users. - Source: dev.to / about 1 month ago
PostHog - Full Product Analytics suite free for up to 1m tracked events per month. - Source: dev.to / 3 months ago
Don't insert the logs/events/analytics into your Application DB. Usually, you send those to specialist datastores (OLAP etc) that process such high volume of data. You can use something like clickhouse [0] for example or use 3rd party SAAS solutions like posthog [1] etc that are built on top of clickhouse [0] https://clickhouse.com [1] https://posthog.com. - Source: Hacker News / 7 months ago
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable. Now... Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application... - Source: Hacker News / 8 months ago
PostHog | Remote (US/Europe timezones) | Full stack engineer, technical ex-founder, tech lead | https://posthog.com or email us careers@posthog.com [0] https://posthog.com/handbook/. - Source: Hacker News / 11 months ago
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
June - Instant analytics reports, built on top of Segment
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
Amplitude - Mobile analytics: come with questions, leave with answers
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.