The vote for Superset passes with 11 +1 binding votes, 3 +1 non-binding votes and no -1 votes. Below are the overall results:
*Binding:* Ashutosh Chauhan +1 Luke Han + 1 Julian Hyde +1 Jitendra Pandey +1 Joe Witt +1 Ted Dunning +1 P. Taylor Goetz +1 Edward Yoon +1 Jacques Nadeau +1 Julian Le Dem +1 Jim Jagielski +1 *Non-Binding:* Moon Soo Lee +1 Naresh Agarwal +1 Felix Cheng +1 Thank you to everyone who participated in the vote. Please welcome Superset to the Apache Incubator! Jeff On Sun, Apr 23, 2017 at 7:53 AM, Jeff Feng <jeff.f...@gmail.com> wrote: > Dear Apache Incubator Community, > > We have updated the Superset proposal > <https://wiki.apache.org/incubator/SupersetProposal> (copied below) for > Apache Incubation with an additional mentor (Luke Han - > luke....@apache.org), and would like to start a vote thread for > acceptance into the incubator. > > Our team is excited to share Superset with the Apache community and we > hope for the your continued support! > > Cheers, > Jeff & the Superset Team > > > > > = Superset = > > == Abstract == > Superset is an enterprise-ready web application for data exploration, data > visualization and dashboarding. > > == Proposal == > Superset is business intelligence (BI) software that helps modern > organizations visualize and interact with their data. Superset enables > users explore data from a variety of databases, assemble beautiful > dashboards and share their findings. Superset works neatly with all modern > SQL-speaking databases, and integrates with Druid.io to provide real-time, > interactive, blazing fast data access to large datasets. > > == Background == > Data is mission critical. To succeed in this era, organizations need to > provide low-friction, intuitive and interactive access to data. It is > paramount for knowledge workers to be capable of answering their own > questions by querying, exploring and visualizing data. > > The entire business intelligence industry has pivoted from a model of > centralized top-down platforms driven by IT organizations to self-service > analytics and agile workflows by any user. This shift unblocks centralized > service bottlenecks for creating data visualizations while also creating an > environment that is iterative and fast-moving. This means that business > intelligence software must also be easy and delightful to use. > Self-service analytics doesn’t mean that admin and governance features are > not needed. > Modern BI tools provide fine-grain access controls and auditing > capabilities to understand how data is being used. Superset is a solution > that delivers on all of these vectors. > > The technology stack is also constantly morphing - vendors are struggling > to provide cheap, quick and easy solutions to access data. Business > intelligence users are finding existing solutions lacking as these software > products either disregard or react slowly to recent game-changing > technologies like Druid.io, PrestoDB, Apache Drill, Apache Kylin, d3.js, > React.js and iPython’s Jupyter for instance. > > == Rationale == > Business intelligence is more relevant today than at any other point in > history. Organizations are currently very limited in options for open > source data visualization solutions, especially solutions that are both > self-service and enterprise-ready. Every company informing their decisions > with data needs a BI tool. > > We believe that Superset will be a strong compliment to existing Apache > Software Foundation technologies by offering scalable user interactions to > distributed storage and computation solutions. Users will often find that > Superset can act as a catalyst for tooling that can visualize the byproduct > of data and computation infrastructure. > > Superset has many key design elements that help fill a gap in current > solutions for organizations: > * Easy, low friction access to data through a simple, web-based data > exploration interface. Composing charts and dashboards are intuitive. > Eliminating the need to write code or SQL empowers anyone to use it. > * Access to a wide array of rich, interactive data visualization types. > * Enterprise-ready: Integration with different authentication mechanisms > and granular permissions centered around actions and data access. > * Realtime & fast: Superset provides realtime analytics at the speed of > thought on very large datasets when integrated with Druid.io. > * Broad data access: Consume data out of any SQL-speaking relational > database. > * Extensible: Can be extended to talk to many noSQL databases like Apache > Drill, Elastic Search, and other popular database engines. > * Fast loading dashboards with configurable web-scale caching. > * Plug-in framework that enables organizations to build custom analytical > applications with new UI/UX interfaces. > * SQL Lab, a state-of-the-art SQL IDE that empowers SQL-speaking users > with more flexibility. SQL Lab integrates with the visualization engine > seamlessly. > > == Initial Goals == > The initial goals of the Superset project are several-fold: > * Move the existing codebase to Apache and integrate with the Apache > development process. > * Redesign the user interface and interaction model for creating > visualizations/dashboards and connecting to data sources > * Build robust support for security and governance of the tool including > popular authorization modules (including Apache Ranger and Apache Sentry) > and a more sophisticated permissions system > * Grow the extensibility of the project both in terms of enhanced > connectivity to NoSQL-based data sources and creating a plug-in framework > that enables organizations to build custom analytical applications which > require a new UI/UX > > == Current Status == > By many standards, Superset is already a successful open source project. > As of March 2017, Superset is officially used in production at about a > dozen companies, has received contributions from over one hundred > contributors on Github, 1500+ forks, and 12k+ stars. > > Sizeable companies like Airbnb, Yahoo! and Hortonworks have made > significant contributions, and expressed their commitment to the project. > The product is feature complete and has been viable for months. It already > serves as the main interface for consuming data at many companies of > different sizes. > > While the product is usable, there’s room for improvement across the > board, starting with providing a smoother user experience around content > creation, making sure all features work out-of-the-box on more platforms > and databases, providing better user training guides and videos, having a > predictable release process, and increasing the overall quality of the > Superset releases. > > === Meritocracy === > We plan to invest in supporting a meritocracy. We will discuss the > requirements in an open forum. Several companies have expressed interest in > this project, and we intend to invite additional developers to participate. > We will encourage and monitor community participation so that privileges > can be extended to those that contribute. > > === Community === > The need for an enterprise-ready data visualization and exploration > platform in the open source community is tremendous. While Superset is > fairly well known, recognized and used within the Druid.io community, > adoption is currently limited outside of that niche. There is a huge > opportunity to grow the community to hundreds if not thousands of > organizations, and we are hoping that embracing “the Apache way” will > accelerate the growth of our community. > > We have already been active at seeking and inviting contributions, and are > planning to scale the project by investing time and growing the support > structure to grow the community. > > === Core Developers === > The initial committers for Superset include experienced full stack, > front-end and data engineers: > * Maxime Beauchemin (Airbnb) > * Alanna Scott (Airbnb) > * Bogdan Kyryliuk (Airbnb) > * Vera Liu (Airbnb) > * Jeff Feng (Airbnb) > * Ashutosh Chauhan (Hortonworks) > * Nishant Bangarwa (Hortonworks) > * Slim Bouguerra (Hortonworks) > * Priyank Shah (Hortonworks) > * Sriharsha Chintalapani (Hortonworks) > * Daniel Dai (Hortonworks) > > We realize that additional employer diversity is needed, and we will work > aggressively to recruit developers from additional companies. > > === Alignment === > The initial committers strongly believe that a system for interactive > visualization of data will gain broader adoption as an open source, > community driven project, where the community can contribute not only to > the core components, but also to a growing collection of connectors, > visualizations and improving integration a all potential data sources. > Superset already integrates closely with Apache Hive, the Hive metastore, > as well as most SQL-speaking databases found in modern data ecosystems. > > == Known Risks == > > === Orphaned Products === > Superset is a vital component for both visualizing, accessing and > democratizing data at Airbnb. Also at Hortonworks, Superset is a core > component of the DataFlow product offering. Thus, the risk of the project > being orphaned is relatively low. The project could be at risk if Airbnb > changes their approach for democratizing data or if Hortonworks changes > their strategy in the market. In such an event, the committers plan to > continue working on the project on their own time, thought the progress > will likely be slower. We plan to mitigate this risk by recruiting > additional committers. > > === Inexperience with Open Source === > The initial committers include veteran Apache members (committers and PPMC > members) and other developers who have varying degrees of experience with > open source projects. All have been involved with source code that has been > released under an open source license, and several also have experience > developing code with an open source development process. > > === Homogenous Developers === > The initial committers are employed by Airbnb Inc. and Hortonworks. We are > committed to recruiting additional committers from other companies. > > === Reliance on Salaried Developers === > It is expected that Superset development will occur on both salaried time > and on volunteer time, after hours. The majority of initial committers are > paid by their employer to contribute to this project. However, they are all > passionate about the project, and we are confident that the project will > continue even if no salaried developers contribute to the project. We are > committed to recruiting additional committers including non-salaried > developers. > > === Relationships with Other Apache Products === > To the knowledge of the Initial Committers, there are no direct > competitors to Superset within the Apache Software Foundation. That said, > Apache Zeppelin is an indirect competitor, but it solves a different use > case. > > Apache Zeppelin is a web-based notebook that enables interactive data > analytics. It enables the creation of beautiful data-driven, interactive > and collaborative documents with SQL, Scala and more. Although a user can > create data visualizations using this project, it leverages a notebook > style user interfaces and it is geared towards the Spark community where > Scala and SQL co-exist > > We look forward to collaborating with those communities, as well as other > Apache communities. > > === An Excessive Fascination with the Apache Brand === > Superset is solving two huge challenges: > The challenge of enabling every knowledge worker to make data informed > decisions, particularly those who are not deeply skilled at writing SQL. > The challenge of visualizing huge amounts of data interactively and in > real-time > > Superset was first developed as a data visualization solution for Druid.io > as a way to visualize billions of rows of data. Since then, usage of > Superset has expanded to address data visualization use cases across SQL > speaking data sources as well. > > Our rationale for developing Superset as an Apache project is detailed in > the Rationale Section. We believe that the Apache brand and community > process will help us attract more contributors to this project, and help > grow the footprint of the project through usage at other organizations and > within other applications. Establishing consensus among users and > developers will result in a more valuable tool for everyone. > > == Documentation == > References to further reading material: > * [[http://airbnb.io/superset/|Superset Documentation]] > * [[https://medium.com/airbnb-engineering/caravel-airbnb-s-dat > a-exploration-platform-15a72aa610e5#.npqmmbu25|Blog Post: Superset: > Airbnb’s Data Exploration Platform]] > * [[https://medium.com/airbnb-engineering/superset-scaling-dat > a-access-and-visual-insights-at-airbnb-3ce3e9b88a7f#.a505zvb1t|Blog Post: > Superset: Scaling Data Access & Visual Insights at Airbnb]] > > == Initial Source == > The origin of the proposed code base can be found at > https://github.com/airbnb/superset. The code base is primarily in > Python. > > == Source and Intellectual Property Submission Plan == > We do not expect any complications for the submission of the Superset code > base. Our code is already in Github and there is only a single code base. > > == External Dependencies == > List of Python packages, from the Python Package Index (Pypi): > > * boto3 > * celery > * cryptography > * flask-appbuilder > * flask-cache > * flask-migrate > * flask-script > * flask-sqlalchemy > * flask-testing > * humanize > * gunicorn > * markdown > * pandas > * parsedatetime > * pydruid > * PyHive > * python-dateutil > * requests > * simplejson > * six > * sqlalchemy > * sqlalchemy-utils > * sqlparse > * thrift > * thrift-sasl > * werkzeug > > List of Javascript packages, from NPM: > * autobind-decorator > * bootstrap > * bootstrap-datepicker > * brace > * brfs > * cal-heatmap > * classnames > * d3 > * d3-cloud > * d3-sankey > * d3-scale > * d3-tip > * datamaps > * datatables-bootstrap3-plugin > * datatables.net-bs > * font-awesome > * gridster > * immutability-helper > * immutable > * jquery > * lodash.throttle > * mapbox-gl > * moment > * moments > * mustache > * nvd3 > * react > * react-ace > * react-bootstrap > * react-bootstrap-table > * react-dom > * react-draggable > * react-gravatar > * react-grid-layout > * react-map-gl > * react-redux > * react-resizable > * react-select > * react-syntax-highlighter > * reactable > * redux > * redux-localstorage > * redux-thunk > * shortid > * style-loader > * supercluster > * topojson > * victory > * viewport-mercator-project > > == Cryptography == > The proposal does not include cryptographic code. > > == Required Resources == > > === Mailing List === > There is a current mailing list as a Google Group “airbnb_superset” that > we are planning on deprecating as the Apache.org become ready to serve our > community. > > * superset-private > * superset-dev > * superset-user > > === Subversion Directory === > Git is the preferred source control system. http://svn.apache.org/repos/as > f/incubator/superset > > == Git Repository == > Git is the preferred source control system, we’re assuming > https://github.com/apache/incubator-superset based on the naming scheme > > == Issue Tracking == > JIRA Superset (SUPERSET). If possible, we’d like to use Github issues & > PRs to manage our project as much as possible. It’s been said that there > are ways to keep Github’s issues in sync with Jira, allowing us to get best > of both worlds. If that is not possible, we will comply to using Jira. > > == Other Resources == > We currently use a set of Github integrated services that are free to the > open source community, like Travis-ci, Code Climate, Coveralls, > Landscape.io, Requires.io, david-dm and Gitter. We would like to keep using > these services as they allow us to scale contributions and optimize our > development flows. These services require some elevated rights on the > Github repository in order to set up or tune and we would like for the > committers to have the required rights. > > > == Initial Committers == > > * Maxime Beauchemin <maxime.beauche...@airbnb.com> - PPMC & Committer > * Alanna Scott <alanna.sc...@airbnb.com> - PPMC & Committer > * Bogdan Kyryliuk <b.kyryl...@gmail.com> - PPMC & Committer > * Vera Liu <vera....@airbnb.com> - Committer > * Jeff Feng <jeff.f...@airbnb.com> - PPMC & Committer > * Ashutosh Chauhan <hashut...@apache.org> - Mentor & Committer > * Nishant Bangarwa <nbanga...@hortonworks.com> - PPMC & Committer > * Slim Bouguerra <sbougue...@hortonworks.com> - Committer > * Priyank Shah <ps...@hortonworks.com> - Committer > * Harsha Chintalapani <schintalap...@hortonworks.com> - Committer > * Daniel Dai <da...@apache.org> - Champion & Committer > * Luke Han <luke....@apache.org> - Mentor > > == Affiliations == > The initial committers are employees of Airbnb Inc. and Hortonworks. > > == Sponsors == > > === Champion === > Daniel Dai <da...@apache.org> > > === Nominated Mentors === > * Ashutosh Chauhan <hashut...@apache.org> > * Luke Han <luke....@apache.org> > > === Sponsoring Entity === > Incubator PMC > >
