Snowplow alternatives and similar software solutions
Based on the "Analytics" category.
Alternatively, view Snowplow alternatives based on common mentions on social networks and blogs.
10.0 10.0 L2 Snowplow VS ElasticsearchFree and Open, Distributed, RESTful Search Engine
9.9 9.9 L2 Snowplow VS SupersetApache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
9.8 10.0 Snowplow VS MetabaseThe simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
9.7 7.8 L4 Snowplow VS RedashMake Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
9.6 9.8 L3 Snowplow VS PiwikLiberating Web Analytics. Star us on Github? +1. Matomo is the leading open alternative to Google Analytics that gives you full control over your data. Matomo lets you easily collect data from websites & apps and visualise this data and extract insights. Privacy is built-in. We love Pull Requests!
9.3 9.7 Snowplow VS UmamiUmami is a simple, fast, privacy-focused alternative to Google Analytics.
9.3 9.9 Snowplow VS cube.js📊 Cube — Headless Business Intelligence for Building Data Applications
9.2 9.7 Snowplow VS PlausibleSimple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics.
8.8 9.9 Snowplow VS PostHog🦔 PostHog provides open-source product analytics that you can self-host.
8.5 6.5 Snowplow VS Fathom AnalyticsFathom Lite. Simple, privacy-focused website analytics. Built with Golang & Preact.
8.5 7.8 L2 Snowplow VS CountlyCountly helps you get insights from your application. Available self-hosted or on private cloud.
8.0 0.0 L2 Snowplow VS ThinkUpThinkUp gives you insights into your social networking activity on Twitter, Facebook, Instagram, and beyond.
7.4 9.8 Snowplow VS RudderStackPrivacy and Security focused Segment-alternative, in Golang and React
7.0 8.8 L2 Snowplow VS Open Web AnalyticsOfficial repository for Open Web Analytics which is an open source alternative to commercial tools such as Google Analytics. Stay in control of the data you collect about the use of your website or app. Please consider sponsoring this project.
5.2 1.7 L2 Snowplow VS Rakam📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
4.9 9.6 Snowplow VS ChartbrewOpen-source web platform used to create live reporting dashboards from APIs, MongoDB, Firestore, MySQL, PostgreSQL, and more 📈📊
3.6 7.3 Snowplow VS Koko AnalyticsPrivacy-friendly analytics for your WordPress site.
3.3 9.5 Snowplow VS TelleryTellery lets you build metrics using SQL and bring them to your team. As easy as using a document. As powerful as a data modeling tool.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of Snowplow or a related project?
Snowplow is a developer-first engine for collecting behavioral data. In short, it allows you to:
- Collect events such as impressions, clicks, video playback (or even custom events of your choosing).
- Store the data in a scalable data warehouse you control (Amazon Redshift, Databricks, Elasticsearch, Google BigQuery, Snowflake) or emit it via a stream (Amazon Kinesis, Google PubSub, Kafka).
- Leverage a wide range of tools to model and analyze the behavioral data: dbt, Looker, Metabase, Mode, Streamlit, Superset, Redash, and more.
Table of contents
- Why Snowplow?
- [Where to start?](#-where-to-start-%EF%B8%8F)
- Snowplow technology 101
- Version compatibility matrix
- About this umbrella repository
- Public roadmap
- 🏔️ Rock solid architecture capable of processing billions of events per day.
- 🛠️ Over 20 SDKs to collect data from web, mobile, server-side, and other sources.
- ✅ A unique approach based on schemas and validation ensures your data is as clean as possible.
- 🪄 Over 15 enrichments to get the most out of your data.
- 🏭 Send data to popular warehouses and streams — Snowplow fits nicely within the Modern Data Stack.
➡ Where to start? ⬅️
|Snowplow Open Source||Snowplow Behavioral Data Platform|
|Our Open Source solution equips you with everything you need to start creating behavioral data in a high-fidelity, machine-readable way. Head over to the Quick Start Guide to set things up.||Looking for an enterprise solution with a console, APIs, data governance, workflow tooling? The Behavioral Data Platform is our managed service that runs in your AWS or GCP cloud. Check out Try Snowplow.|
The documentation is a great place to learn more, especially:
- Tracking design — discover how to approach creating your data the Snowplow way.
- Pipelines — understand what’s under the hood of Snowplow.
Would rather dive into the code? Then you are already in the right place!
Snowplow technology 101
The repository structure follows the conceptual architecture of Snowplow, which consists of six loosely-coupled sub-systems connected by five standardized data protocols/formats.
To briefly explain these six sub-systems:
- Trackers fire Snowplow events. Currently we have 15 trackers, covering web, mobile, desktop, server and IoT
- Collector receives Snowplow events from trackers. Currently we have one official collector implementation with different sinks: Amazon Kinesis, Google PubSub, Amazon SQS, Apache Kafka and NSQ
- Enrich cleans up the raw Snowplow events, enriches them and puts them into storage. Currently we have several implementations, built for different environments (GCP, AWS, Apache Kafka) and one core library
- Storage is where the Snowplow events live. Currently we store the Snowplow events in a flat file structure on S3, and in the Redshift, Postgres, Snowflake and BigQuery databases
- Data modeling is where event-level data is joined with other data sets and aggregated into smaller data sets, and business logic is applied. This produces a clean set of tables which make it easier to perform analysis on the data. We officially support data models for Redshift, Snowflake and BigQuery.
- Analytics are performed on the Snowplow events or on the aggregate tables.
For more information on the current Snowplow architecture, please see the [Technical architecture][architecture].
Version Compatibility Matrix
To make sure all the components work well together, we strongly recommended you take a look at the compatibility matrix when setting up a Snowplow pipeline.
About this repository
This repository is an umbrella repository for all loosely-coupled Snowplow components and is updated on each component release.
Since June 2020, all components have been extracted into their dedicated repositories (more info here) and this repository serves as an entry point for Snowplow users, the home of our public roadmap and as a historical artifact.
Components that have been extracted to their own repository are still here as git submodules.
A full list of supported trackers can be found on our documentation site. Popular trackers and use cases include:
|Web||Mobile||Gaming||TV||Desktop & Server|
- BigQuery (streaming)
- Redshift (batch)
- Snowflake (batch)
- Google Cloud Storage (streaming)
- Amazon S3 (streaming)
- Postgres (streaming)
- Elasticsearch (streaming)
Parsing enriched event
- Analytics SDK Scala
- Analytics SDK Python
- Analytics SDK .NET
- Analytics SDK Golang
This repository also contains the Snowplow Public Roadmap. The Public Roadmap lets you stay up to date and find out what's happening on the Snowplow Platform. Help us prioritize our cards: open the issue and leave a 👍 to vote for your favorites. Want us to build a feature or function? Tell us by heading to our Discourse forum 💬.
We want to make it super easy for Snowplow users and contributors to talk to us and connect with one another, to share ideas, solve problems and help make Snowplow awesome. Join the conversation:
- Meetups. Don’t miss your chance to talk to us in person. We are often on the move with meetups in Amsterdam, Berlin, Boston, London, and more.
- Discourse. Our forum for all Snowplow users: engineers setting up Snowplow, data modelers structuring the data, and data consumers building insights. You can find guides, recipes, questions and answers from Snowplow users and the Snowplow team. All questions and contributions are welcome!
- Twitter. Follow @Snowplow for official news and @SnowplowLabs for engineering-heavy conversations and release announcements.
- GitHub. If you spot a bug, please raise an issue in the GitHub repository of the component in question. Likewise, if you have developed a cool new feature or an improvement, please open a pull request, we’ll be glad to integrate it in the codebase! For brainstorming a potential new feature, Discourse is the best place to start.
- Email. If you want to talk to Snowplow directly, email is the easiest way. Get in touch at [email protected].
Copyright and license
Snowplow is copyright 2012-2022 Snowplow Analytics Ltd.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License.
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
*Note that all licence references and agreements mentioned in the Snowplow README section above are relevant to that project's source code only.