Apache Pinot Community Contributors
It Happened, Pinot is a Top-Level ASF Project!
Having your open-source project be a part of the Apache Software Foundation is a pretty big deal. After meeting all the ASF guidelines, Pinot has graduated to become a top-level ASF project. ❤️
As mentioned by Pinot co-author, Kishore Gopalakrishna, in his latest blog post Apache Pinot’s Graduation: A Celebration of Community and a Look Ahead, “it speaks to the strength of our community” as “community is the heart of any open source project.”
With this in mind, we wanted to take a moment and not only recognize some of Pinot’s top contributors but also allow them the opportunity to share a little bit about what it means to them to be part of this incredible group and help pave a better path in real-time and user-facing analytics.
Xiaotian (Jackie) Jiang
Founding Engineer at StarTree, Apache Pinot PMC
Jackie is one of the top contributors for Apache Pinot and has contributed several important features such as JSON index, TIMESTAMP support, HAVING and post-aggregation support etc. He is also very active in the Pinot community and has been presenting a series of tech-talks at Pinot Meetup.
“It is very satisfying to solve the challenging problems and see the fancy use cases powered by Apache Pinot.”
Xiang Fu
Co-founder at StarTree Inc, Apache Pinot PMC
Xiang is a founding member and engineered multiple core Pinot parts and features. He has built up the Pinot ecosystem with other projects like Presto/Superset. His goal is to support the community in all possible aspects.
“It’s fun to work with people to gold mining real-time data.”
Neha Pawar
Founding Engineer at StarTree, Apache Pinot PMC
Neha is one of the top contributors to the Apache Pinot codebase. She has made numerous impactful contributions to Pinot around ingestion capabilities & operational efficiency, such as integrations with realtime streams, ease of realtime operations, tiered storage and ingestion transformations. She enjoys actively fostering the community by presenting at conferences and meetups, making entertaining explainer videos & tutorials and participating in community questions & discussions.
“The community is packed with the best mentors and highly passionate folks, which helped me learn a lot about the distributed systems and realtime analytics world. There are always several exciting projects ongoing, and I get to take on challenging problems to solve. Plus, everyone’s really nice to each other!”
Mayank Shrivastava
Founding Engineer at StarTree Inc, Apache Pinot PMC
Mayank was a part of the original team that created Apache Pinot at LinkedIn. He built this awesome system to solve all realtime analytics applications at LinkedIn member scale, and then evangelized it in the open source community for wider impact. His experience has been truly gratifying.
“As a developer, it provides me an opportunity to work on really interesting as well as challenging problems. Knowing that that impact Apache Pinot creates for its users by making them decision makers is a great added benefit.”
Subbu Subramaniam
Sr Staff Engineer at LinkedIn, Apache Pinot PMC
Subbu has designed and built the Realtime Ingestion and indexing mechanisms (segment completion, auto-segment size tuning, realtime off-heap dictionary, auto-healing, etc.). In addition, Subbu has contributed to many other areas of Pinot such as helix/pinot controller separation, moving from Restlet to Jersey framework, etc. More recently, he has built the compatibility test framework to test cross-release compatibility.
“Pinot is not a solution built in search of a problem. Instead, it takes the problem of realtime analytics head on, and solves it. There is still good bit of work to be done, and the adoption is growing.”
Alexander Pucher
Founding Engineer at StarTree, Apache Pinot Committer
Alex brought to you REST authentication, TLS encryption, and a random collection of late-night patches in Apache Pinot. He also spent way too much time on ThirdEye’s Root-Cause Analysis while it was still a thing. You may have come across Alex from litany of blogs, podcasts, talks, and Slack conversations.
“Bigger, Better, Faster Analytics. Bring on those terabytes. Apache Pinot is awesome.”
Seunghyun Lee
Sr. Software Engineer at LinkedIn, Apache Pinot PMC
Seunghyun is a PMC/Committer of Apache Pinot. He has contributed a lot of interesting features and he also gave a tech talk in multiple venues including ApacheCon and Pinot meetups.
“I love to work on distributed systems and Apache Pinot covers all different aspects of systems including query processing engine, columnar data format, sharding, routing, and etc.”
Jialiang Li
Sr. Software Engineer at LinkedIn, Apache Pinot Committer
Jialiang (Jack) is a Sr. Software Engineer at LinkedIn. He’s been working on making Pinot the best OLAP in the market since 2018. He likes making contributions on things like writing code with good quality, reviewing feature design, providing community support and online Q&A, etc.
“Pinot is a fast growing OLAP that it’s changing the way people leverage big data and provide insightful strategies. I’d love to make it better!”
Siddharth Teotia
Senior Software Engineer at LinkedIn, Apache Pinot PMC
Siddharth contributed the Text index feature, several bug fixes, enhancements, and performance improvements. He presented at an Uber Meetup, ApacheCon 2021, and the Advanced Indexing meetup and wrote two blog posts.
“The community is super helpful, people are nice and I love databases and distributed systems and believe can make a difference”
Yupeng Fu
Staff Software Engineer at Uber Inc, Apache Pinot Committer
Yupeng contributed a few core features to Pinot, such as upsert and geospatial support. He also spoke at a number of meetups and conferences like Kafka Summit on those features. Yupeng leads the real-time data infrastructure at Uber, and published a blog on the operational learnings at https://eng.uber.com/operating-apache-pinot/. He is also the co-author of Uber’s research paper “Real Time Data Infrastructure at Uber”, which highlights Pinot as the real-time OLAP engine solution for Uber.
“Apache Pinot plays a key role in Uber’s real-time data infrastructure. It’s my honor to be part of this amazing community and I had a lot of fun collaborating with other awesome Pinot community members.”
Mingqiang Liang
Software Engineer – Systems & Infrastructure at LinkedIn, Apache Pinot Contributor
Ming contributed a lot to the Pinot codebase, including metrics, data table v3 and v4, CombineOperator instrumentation, Compatibility Regression Testing framework, etc.
“Pinot is a very good real-time distributed OLAP datastore, built to deliver scalable real-time analytics with low latency. It has an elegant architecture and high quality codebase, as well as an active community. Contributing to Pinot helps me gain a much deeper knowledge about the codebase and know more people in the community.”
Kartik Khare
Software Engineer III at Walmart, Apache Pinot Committer
Refactored documentation for better discoverability. Added JDBC driver for Pinot and support for ingesting data from Apache Kinesis, Apache Pulsar, and Amazon S3. Added support for Scalar functions allowing users to register their custom java functions for a query. Also, had minor contributions in JSON indexing.
“Apache Pinot’s community is exceptionally good and engaging. They were quick to help me out from day 1 and were not afraid to provide bigger projects after initial bug fixes. They also put a lot of thought into designing features which is reflected in the discussions on PRs.”
Ting Chen
Software Engineer at Uber, Apache Pinot Committer
Ting contributed to several features for Pinot including realtime ingestion with deepstore support, upsert table and so on. He gave two meetup talks about how Uber deploys Pinot. He is a release manager for Pinot 0.5.
“Apache Pinot solves a real technical problem many companies face today for the needs of fast realtime data analytics. Its community is open and welcoming to new ideas.”
Sanket Shah
Director at Deuex Solutions Private Limited, Apache Pinot Contributor
Sanket has contributed by developing and revamping the cluster manager UI with guidance from the Pinot team, especially Kishore Gopalakrishna and Neha Pawar.
“Apache Pinot didn’t have an intuitive UI and when Kishore approached me for revamping the UI, I jumped on the opportunity. Along the way, the whole team helped and their support motivated me to keep going with contributions.”
Chinmay Soman
Founding Engineer at StarTree, Apache Pinot Committer
Chinmay has made code contributions for null value predicate support, table config validation improvements, ingestion status and so on. He has been actively involved in the design of decoupling deep store for realtime table and has made several documentation enhancements. Besides this, he has presented in several conferences (QCon, Berlin Buzzwords), meetups and published blogs on Apache Pinot.
“Apache Pinot is on the cutting edge of real-time analytics. It is amazing to be part of a project that is powering mission critical use cases for large companies like LinkedIn and Uber.”
Amrish Lal
Staff Software Engineer at LinkedIn, Apache Pinot Contributor
Amrish has contributed towards improving querying capability of JSON data in Pinot and towards enhancing the use of numerical datatypes in query filters.
“It’s great to be able to work alongside developers and contributors who bring their diverse range of experiences and ideas across the industry to collaborate and develop Pinot. As compared to some of the other query engines and databases that I have worked on, Pinot has a relatively clean architecture and codebase – this not only allows Pinot to scale and perform well, but also makes it a joy to work with and develop ideas into working features.”
Haibo Wang
Software Engineer, Apache Pinot Committer
Haibo contributed to the design, implementation, and open-source efforts of the Presto-Pinot connector, allowing users to query the fresh data in Pinot in a more versatile and efficient way. He also made other contributions to Pinot like the schema evolution support.
“I love the strong vision and technical expertise of leaders and contributors, supportive community.”
Sajjad Moradi
Senior Software Engineer at LinkedIn, Apache Pinot Contributor
Sajjad worked on different projects in the Pinot team in Linkedin which resulted in contributions in Pinot OSS like enabling segment encryption in offline push jobs, ACL based authentication, or recently added some rules to Rule Engine for optimizing table configurations.
“In my opinion, Pinot is amazing when you look at it from a system design perspective. It’s a distributed system with offline and realtime components which happens to be a database with query execution, storage, …! So there are a lot of things to learn here.”
Jiapeng Tao
Software Engineer at LinkedIn, Apache Pinot Contributor
Jiapeng implemented the broker time-based pruner and co-worked on segment merge/rollup task with Seunghyun Lee and Jackie Jiang. He participated in the compatibility test suite, bug fix and feature improvement, etc.
“I enjoy working with these brilliant and talented people, improving my abilities such as coding and teamwork, in the development of this industry-leading project.”
Sharayu Gandhi
Software Engineer at LinkedIn, Apache Pinot Contributor
Sharayu has made contributions to segment size pruning, No-Dictionary compression codec support like ZSTD, LZ4, and pass through transform operators for improving query latency. Notable contributions in Apache Pinot include backward compatibility regression test suite development.
“I believe in the idea of the product. I am highly motivated by open source contributions and activity.”
Elon Azoulay
Software Engineer at a Stealth Startup, Apache Pinot Contributor
Elon has contributed Realtime Ingestion using kafka and confluent schema registry schema, GCS plugin for deepstore, and Build and run with java11
“I love contributing to pinot because it is a great piece of software, with great and easy to reason about architecture which allows people to add features or plugins without an excessive learning curve. The community is so great and really helpful in terms of engagement and reviews which is a major factor in both adoption and open source evolution.”
James Shao
Software Engineer at Netflix, Apache Pinot Committer
James helped with the previous version of Pinot Kafka support improvement and drove the initial design of the Pinot Upsert feature. He also presents Pinot/real-time infrastructure usage within Uber in various talks/meetups.
“I love working with distributed systems and large-scale data applications. I found Pinot offers a unique solution for a lot of problems we face in production. It also has a thriving community with a lot of exciting opportunities for contributing to open source.”
Chethan UK
Senior Data Engineer at Rapido (India), Apache Pinot Contributor
Chethan has contributed to Pinot deployments mainly in K8s with Helm charts etc. He built the current Pinot website and has helped people set up Pinot for POC’s.
“Pinot overall is a great fit for the realtime ecosystem of any company which wants to build User facing analytics products or even analytics with features like Pluggable indexing, easy ingestion framework etc.. Also, the Community which StarTree is building is awesome, I guess most projects’ success depends on it.”
Jia Guo
Software Engineer at LinkedIn, Apache Pinot Contributor
During his two internships on the Pinot group of LinkedIn, Jia has prototyped, designed, and implemented the config recommender of Pinot. This project aims to improve query latency at minimum cost by providing optimized settings, e.g., sorting, indexing, partitioning, etc.
“I love to work with the incredible team and community of Apache Pinot. They put great effort into reviewing and refining my design.”
Yash Agarwal
Sr. Engineer at Target, Apache Pinot Contributor
Helped in improving the batch ingestion process, and also worked with the team to design SegmentPartitionedDistinctCount. Worked with the team to profile and improve query performance by implementing multithreading in brokers. Continue to push pinot at Target by sharing the same at multiple forums.
“It is just a great product and built by a great team.”
Pradeep Gopanapalli Venkata
Member of technical staff at Confluera, Apache Pinot Contributor
Pradeep’s primary contribution was the addition of FST_INDEX for speeding up regexp_like queries, this would be useful for those who care about recall than precision with their regex queries and with optimal use of storage.
“Apache Pinot’s modular and extendable structure makes it easy to add newer features and this coupled with a very helpful & a growing community makes features addition faster and fun.”
Ken Krugler
President at Scale Unlimited, Apache Pinot Contributor
Ken has provided patches, updated documentation, answered questions on Slack, and spoken at a Pinot meetup about his experience with Pinot.
“It’s a really good backend solution for many dashboard analytics systems, and the community is very transparent, friendly, responsive and helpful.”
Joey Pereira
Software Engineer at Stripe, Apache Pinot Contributor
While getting Pinot adopted in his org, Joey made a few small contributions (issues, minor changes) and also did advocacy through speaking at Kafka Summit EU 2021 about using Pinot to analyze large-scale data at Stripe.
“Apache Pinot is a fantastic project that really simplifies so many needs for internal data accessibility and business intelligence. With Pinot’s interoperability, flexibility, and ease of iterating we have been able to use it with little effort. And when we need to, we had no issue digging into the details and contributing back to Pinot for specific capabilities or fixes!”
Ananth Packkildurai
Principal Software Engineer at Zendesk, Apache Pinot Contributor
Perhaps his single greatest contribution, Ananth created the Apache Pinot Slack community.
“It’s the people & the community. Apache Pinot provides many distributed system challenges at scale, but above all, it is the welcoming community that excites me to contribute to Apache Pinot.”
Aditya S
Senior Software Engineer at Myntra, Apache Pinot Contributor
Aditya who is a software engineer working in the domain of real-time analytics has created a Udemy course on pinot which will help new users of Pinot understand all the basic concepts of Pinot. Here Is A Link to the course.
“Realtime analytics is very critical for most companies. Apache Pinot greatly simplifies how one can ingest realtime data, run analytical queries on them and serve a large number of these queries in a few milliseconds. I was impressed with the features provided by Pinot and hence decided to play my part in it by creating a course on Pinot.”
Atri Sharma
Distinguished Engineer at Securonix, Apache Pinot Contributor
Atri focuses on core engine improvements, primarily in the query processing layer. He has been instrumental in improving the performance of DISTINCT queries, allowing OR predicates to run on Star Tree indexes, and is currently focused on making the Pinot query planner more pluggable and future ready.
“I love contributing to Pinot because it is a myriad of nicely crafted technologies and is a very well written codebase. As a product, it is industry leading. The community is exceptionally welcoming and helpful and I love being a part of it.”
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