In this guide you'll learn about Apache Pinot, a real-time distributed OLAP datastore, purpose-built to provide ultra low-latency analytics at extremely high throughput. You will need to understand the basics of [real-time analytics](. what-is-real-time-analytics.md).
Apache Pinot is a real-time distributed OLAP datastore, purpose-built to provide ultra low-latency analytics at extremely high throughput. It helps you make very large amounts of data, query-able, very very fast, at scale.
It can be used in all types of real-time applications, like BI Dashboards, user analytics, and machine learning analytics.
Tim Berglund explains Apache Pinot
What is user facing analytics?
Users expect the applications that they use to provide real-time analytics and provide them with actionable insights. Actionable insights gives your users the ability to take actions or make decisions as a result of having real-time analytics.
You want to empower your end-users by giving them these capabilities.
The origins of Apache Pinot
So, what makes the process of building real-time analytics systems so difficult? Chances are, you have a lot of data, and you need to be able to ingest it and have lots of users query it, in subsecond time.
Pinot was originally built by the engineering team at LinkedIn who faced exactly this problem. With 800+ million users on the platform and constant engagement, they have a lot of data coming in. To provide their users with their own real time analytics, they needed to make this massive amount of data accessible, in real-time.
The challenge they faced was 3 parts:
- Ingesting the data as soon as events happen.
- Making the data queryable as soon as it’s pulled in, and
- Doing it at scale. LinkedIn often has more than 250 thousand queries per second by their users.
How can you possibly do all of this? Enter Apache Pinot!
So...what is Apache Pinot?
Apache Pinot is a real-time distributed OLAP datastore, built to do a number of things:
- Pinot is built to ingest from all kinds of different data sources, batch, ETL, and streams such as Kafka and Kinesis.
- Instant insights
- Pinot then indexes the ingested data, in real-time, maintaining seconds freshness SLAs.
- Interactive querying
- Pinot enables superfast queries, with query latency in the milliseconds.
- At Scale
- Pinot can ingest data with a very high velocity of ingestion, proven to ingest as high as 1M of events/s, while maintaining high throughput for queries, often hundreds of thousands queries per second.
- Query anything and everything
- The data ingested into Pinot can have extremely high dimensionality, while supporting ad hoc slicing and dicing of that data. Pinot has powerful indexes, smart optimizations in routing, data partitioning, and segment/server assignment, making it a powerhouse of analytics.
Pinot will help you build a rich analytics ecosystem for your users, putting the power of actionable insights into their hands.