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Apache Pinot™

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latencyPinotOverviewUSE-CASESUser-facingData ProductsBusinessIntelligenceAnomalyDetectionSOURCESEVENTSSmart IndexBlazing-FastPerformantAggregationPre-MaterializationSegment Optimizer

Pinot is proven at scale in LinkedIn powers 50+ user-facing apps and serving 100k+ queries

What is Apache Pinot?


Fast queries

Pinot can filter and aggregate petabyte data sets with P90 latencies in the tens of milliseconds—fast enough to return live results interactively in the UI.

High concurrency

With user-facing applications querying Pinot directly, it can serve hundreds of thousands of concurrent queries per second.

Batch and streaming ingest

Ingest from Apache Kafka, Apache Pulsar, and AWS Kinesis in real time. Batch ingest from Hadoop, Spark, AWS S3, and more. Combine batch and streaming sources into a single table for querying.


Ingest the same record many times, but see only the latest value at query time. Upserts are built-in and production-tested since version 0.6.

Versatile joins

Perform arbitrary fact/dimension and fact/fact joins on petabyte data sets.

Rich indexing options

Choose from pluggable indexes including timestamp, inverted, star-tree, Bloom filter, range, text, JSON, and geospatial options.

Built for scale

Pinot is horizontally scalable and fault-tolerant, adaptable to workloads across the storage and throughput spectrum.

SQL query interface

The highly standard SQL query interface is accessible through a built-in query editor and a REST API.

Built-in multitenancy

Manage and secure data in isolated logical namespaces for cloud-friendly resource management.

Ingest and Query Options#

Ingest with Kafka, Spark, HDFS or Cloud Storages
Query using PQL(Pinot Query Language ), SQL or Trino/Presto(supports Joins)
PinotOverviewQUERYSQLPQLJoins inTrino or PrestoSOURCESEVENTSSmart IndexBlazing-FastPerformantAggregationPre-MaterializationSegment Optimizer

User-Facing Analytics#

Building Latency Sensitive User Facing Analytics via Apache Pinot

Using Apache Kafka and Apache Pinot for User-Facing Analytics

Installs Everywhere#

Pinot can be installed using docker with Trino/Presto
Helm or K8s crds
Public Cloud


helm repo add pinot create ns pinothelm install pinot pinot/pinot -n pinot --set

Or choose your preferred method: