Video Resources

Watch videos on the past, present, and future of Real-Time Analytics. All in one place.


    Learn about fundamental concepts and terms

    What is Real-Time Analytics?

    Real-time analytics is a computer science discipline wherein massive amounts of data generated in relatively short time needs to be ingested, stored, and indexed, followed by additional processes that can search, filter, aggregate, and process that stored data against specific queries to produce results.

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    What is User-Facing Analytics?

    User-facing analytics, or customer-facing analytics, are a subset of the domain of real-time analytics that provide massively concurrent query support.

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    StarTree ThirdEye

    Everything around Anomaly Detection with ThirdEye

    What is Real-Time Anomaly Detection?

    Join Tim Berglund as he breaks down the intricacies of anomaly detection, emphasizing the pitfalls of traditional methods.


    StarTree ThirdEye: Automated Monitoring & Anomaly Detection

    Learn practical examples for implementing automated monitoring and anomaly using StarTree ThirdEye.

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    Preventing eCommerce Fraud Using StarTree ThirdEye

    StarTree's ThirdEye, an automated anomaly detection system that operates seamlessly with Apache Pinot, transforms your e-commerce operations by identifying and flagging potential fraudulent activities in real-time.


    StarTree Tiered Storage

    Process petabytes of data in a cost-efficient manner with Tiered Storage

    Tiered Storage at Sovrn - Powered by StarTree & Apache Pinot

    Sovrn is leveraging Tiered Storage to manage data storage, which allows them to save money on cloud storage and keep their customers' data for when they need it.


    Tiered Storage in StarTree Cloud (Lightboard)

    Tim and Neha explain the need for a system that combines the speed of tightly-coupled systems and the cost-efficiency of decoupled systems.


    The Magic of Tiered Storage in StarTree Cloud | Neha Pawar & Tim Berglund

    See how the concept of Tiered Storage in StarTree Cloud compares to the wizarding world of Harry Potter in this lightboard video.

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    StarTree Features

    Get your data into Apache Pinot with the no-code, self-service tool

    Get your Pinot faster with StarTree Data Manager

    Introducing StarTree Data Manager: a no-code, self-service tool that helps users of all caliber to quickly get started with Pinot.

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    Get Data into Pinot Faster with StarTree’s Data Manager

    StarTree’s Data Manager is a no-code, self-service tool that helps users of all calibers quickly get started with Pinot.


    Apache Pinot Updates

    Learn what's new for THE real-time database

    Apache Pinot 1.0 | Overview of Latest Features and Updates

    Announcing Apache Pinot 1.0! 1.0 has introduced new features to support query-time native JOINs, upsert capabilities, NULL value support in queries, and more.

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    Discovering Apache Pinot 1.0: Feature Spotlight

    Explore the pivotal features driving this milestone release. From amplified real-time analytics to robust querying capabilities, we'll navigate the core highlights of Apache Pinot 1.0.


    Apache Pinot Roadmap 2023

    Get to hear from Linkedin, Uber, StarTree and more, what they have in store this year for Pinot. Explore what other community members are working on and Hear what the community wants to see in Pinot.


    Apache Pinot User Stories

    Industry leaders that are using Apache Pinot

    DoorDash: Supporting Multiple Pinot Use Cases at Scale

    Will Gan (Software Engineer, DoorDash) focuses on two use cases at DoorDash: Mx Portal Ads Campaign Reporting and Risk Platform Dashboarding.


    Beaconstac: From ElasticSearch to Apache Pinot for our Analytics Needs

    Why Beaconstac moved from ElasticSearch to Apache Pinot for their Analytics Needs


    LinkedIn Profile Insights: Apache Pinot vs Apache Druid & Real-Time Analytics

    StarTree CEO, Kishore Gopalakrishna, discusses Apache Pinot and performance comparisons with Apache Druid at Crunch Data Conference 2018 in Budapest.


    StarTree Customer Stories

    Hear from StarTree customers and their real-time analytics use case

    Sovrn: Revolutionizing AdTech with Apache Pinot and StarTree

    Hear how Sovrn, a leader in the AdTech industry, partnered with StarTree to help them bring real-time analytics to their customers.

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    Real-Time Anomaly Detection: Just Eat + StarTree ThirdEye

    Leon Graveland highlights Just Eat's data-driven evolution amidst pandemic-induced challenges.


    Real-Time Analytics Podcast with Tim Berglund

    A podcast dedicated to bringing analytics from the dashboard to the user interface

    Bridging Data with Trino and Pinot | Ep. 31

    Dive into the world of advanced SQL querying with Elon Azoulay, a software engineer at Starburst.


    Unveiling the Speed of Star-Tree Index | Ep. 30

    Discover how this advanced feature optimizes OLAP databases, balancing storage and high-speed query performance.


    Optimize Pinot Performance: Capacity Planning with Sandeep Dabade | Ep. 29

    Discover how to calculate the perfect cluster size for your real-time analytics requirements and explore essential technical KPIs like read throughput, write throughput, and data size.


    Deep Dive: Exploring StarTree's Advanced Features with Neha Pawar - Part 2 | Ep. 28

    Delve into Apache Pinot's advanced features including its pluggable architecture, upserts, and Kafka integration.


    Neha Pawar on Apache Pinot's Edge in Real-Time Analytics | Ep. 27

    Tim and guest Neha Pawar explore Apache Pinot’s unique capabilities in real-time analytics. Neha unpacks Pinot's efficiency, low latency, and high throughput, revealing its prowess in offering real-time insights to end users.


    Inside Stripe’s Data Revolution with Johan Adami | Ep. 26

    Johan Adami, a seasoned software engineer from Stripe, shares his experience building out Pinot as an internal service for enhanced real-time analytics.


    The Evolution of Data Silos with Guru Sattanathan | Ep. 25

    Join Tim Berglund and Guru Sattanathan as they navigate through the intriguing phases of data silos, application integrations, and the inevitable rise of real-time analytics.


    From KSQL to DeltaStreams: A Conversation with Hojjat Jafarpour | Ep. 24

    From the early days of KSQL to the cutting-edge work with DeltaStreams, they dive deep into the evolution and impact of real-time analytics, streaming SQL, and cloud-native data solutions.


    Exploring Data Mesh and Event Streaming with Hubert Dulay | Ep. 23

    Delve into the intriguing intersection of data mesh and event streaming with Hubert Dulay, a developer advocate at StarTree and the author of "Streaming Data Mesh."


    Wix's Smart Approach to Real-Time Analytics with Josef Goldstein | Ep. 22

    Discover the secrets behind Wix's cutting-edge real-time analytics.


    Stripe's Real-time Revolution with Engineer Lakshmi Rao | Ep. 21

    Dive into Lakshmi's journey from Kafka to Flink and finally to Pinot, understanding the growth and development of real-time analytics in the payment sector.

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    StarTree Recipes

    Short tutorials on Apache Pinot and StarTree Cloud

    Indexing JSON Data with Apache Pinot | StarTree Recipes

    Mark Needham is back with another StarTree Recipe, this time about using JSON indexes in Apache Pinot. He first demonstrates how to ingest semi-structured data Apache Kafka using the kcat command line tool, before showing how to configure Apache Pinot to ingest the data from Kafka. He further illustrates querying the Pinot table, using the JSON match function and details handling of arrays, nested data, and exclusion of fields. The tutorial underscores the improved efficiency and flexibility of using JSON indexes introduced in Pinot 0.12.


    Merging Real-Time Segments in Apache Pinot | StarTree Recipes

    In this StarTree Recipe, Mark Needham explains how to merge segments in real-time tables in Apache Pinot, which we want to do as small segments can lead to higher query latency. He demonstrates how to use the kcat tool to setup the Pinot schema, followed by the table config, which includes the MergeRollupTask. After checking data ingestion through the Pinot UI, Mark shows how to manually run the MergeRollupTask, and what it looks like when the segments are merged successfully. This process, when done properly, can improve query performance significantly.


    Rollup Segments in Apache Pinot | StarTree Recipes

    Mark is back with another recipe where he explains the process of rolling up segments in real-time tables in Apache Pinot. This process aims to reduce the amount of space that data occupies by aggregating it up to the nearest minute, hour, or even day. He uses an example involving product purchases streamed in Kafka, which are aggregated according to parameters such as minimum stock, sum of quantity, maximum price, and sum of sales amount. Needham also demonstrates how these rollups are configured in Apache Pinot, and visualized via the Pinot UI, while explaining the concept of task types, ingestion configuration, segment names, and the influence of time intervals on aggregation.


    Filtering Streaming Ingestion with Apache Pinot | StarTree Recipes

    Join Mark Needham from Startree as we delve into filtering data streams during ingestion in Apache Pinot! With help from a flight-related dataset, we'll learn how to filter events on their way into Apache Pinot without needing to use a stream processor. Whether you're a beginner or experienced with Apache Pinot, this tutorial is packed with hands-on insights to elevate your streaming data game.


    Full Upserts in Apache Pinot | StarTree Recipes

    Dive deep into the world of full upserts in Apache Pinot with Mark Needham. This tutorial unveils the process of modifying and updating records, emphasizing real-time data streaming. Utilizing a NASDAQ stock prices simulator and Apache Kafka, Mark illustrates the distinction between full and partial upserts, the role of Redpanda Keeper in topic management, and the importance of consistency in partition keys and Pinot configurations.


    Multi-Volume Support in Apache Pinot | StarTree Recipes

    Mark Needham explains multi volume support in Apache Pinot, with help of an example showing how to store hot and cold data on


    A Deep Dive into Apache Pinot’s Geospatial Indexes | StarTree Recipes

    In this video we'll do a deep dive into Apache Pinot's Geospatial index, learning when it gets used, as well as what happens when the query engines are querying a geoindexe


    Partial Upserts in Apache Pinot | StarTree Recipes

    Join Mark Needham as he unravels the intricacies of partial upserts in Apache Pinot. In this comprehensive guide, Mark demonstrates the process using a simulated data generator mimicking motor traffic at imaginary junctions. You’ll be walked through the creation of a Kafka topic with Redpanda Keeper, and witness real-time data streaming using JQ and K cat. Discover the significance of the junction ID as a key and delve deep into the configuration and optimization of Pinot schema for efficient data handling. Watch as he navigates through table configs, ensuring optimal settings for partial upsert functionality. Witness data transformation and understand the dynamics of min/max speeds and vehicle counts. Lastly, explore the Pinot UI and query execution, offering insights into real-time data evolution.


    Segment Threshold in Apache Pinot | StarTree Recipes

    This video is all about the segment threshold in Apache Pinot. Mark Needham explains what it is, why we should care, and how to go about configuring it.


    Tracking Ingestion Lag from Apache Kafka | StarTree Recipes


    Storing Geospatial Objects in Apache Pinot | StarTree Recipes

    In this video we explore the types of geospatial objects that can be stored in Apache Pinot. We also learn about the geospatial index and use it to write a super fast query to find the points within 50km of the centre of San Francisco.


    Ingesting Avro Encoded Messages Into Apache Pinot | StarTree Recipes

    Dive deep into data serialization and ingestion with Mark Needham in this informative session on ingesting Avro encoded data into Apache Pinot. Learn to generate data in Avro format using the Confluent Kafka library, create topics with Redpanda Keeper, and navigate real-time data streaming. This walkthrough covers transforming Avro to Pinot schema and explores telemetry data and streaming configurations. Perfect for those looking to master real-time data handling and processing.

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