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Apache Pinot

Apache Pinot is a real-time distributed OLAP datastore designed to deliver scalable real-time analytics with low latency. It ingests data from batch and streaming sources and provides fast analytical queries for user-facing applications.

1 APIs 7 Features
AnalyticsDatabaseLow LatencyOLAPReal-TimeApacheOpen Source

APIs

Apache Pinot REST API

The Pinot API provides REST endpoints for SQL queries, schema management, table management, segment management, cluster administration, and task management, along with a JDBC dr...

Features

Real-Time OLAP

Sub-second analytical queries over real-time and historical data

SQL Support

Standard SQL query interface with Pinot-specific extensions

Streaming Ingestion

Real-time data ingestion from Kafka, Kinesis, and Pulsar

Batch Ingestion

Offline data ingestion from HDFS, S3, GCS, and local files

Columnar Storage

Column-oriented storage with bitmap indexing for fast queries

Multi-Tenancy

Tenant isolation for broker and server resources

Star-Tree Index

Pre-aggregated star-tree index for metric rollup queries

Use Cases

User-Facing Analytics

Power user-facing dashboards like LinkedIn Who Viewed Profile

Real-Time Dashboards

Business intelligence dashboards over streaming data

Anomaly Detection

Real-time anomaly detection over metric time series

A/B Testing

Real-time experiment analysis and statistical significance

Integrations

Apache Kafka

Real-time stream ingestion from Kafka topics

Apache Flink

Flink connector for streaming data into Pinot

Apache Superset

Visual analytics and dashboards via SQL

Presto/Trino

Federated query access to Pinot via Presto connector

Grafana

Grafana data source plugin for Pinot metrics

Semantic Vocabularies

Apache Pinot Context

12 classes · 34 properties

JSON-LD

API Governance Rules

Apache Pinot API Rules

5 rules · 4 errors 1 info

SPECTRAL

Resources

👥
GitHubOrganization
GitHubOrganization
🔗
Documentation
Documentation
🔗
SpectralRules
SpectralRules
🔗
Vocabulary
Vocabulary
🔗
JSONLD
JSONLD
🔗
LLMsTxt
LLMsTxt

Sources

Raw ↑
aid: apache-pinot
name: Apache Pinot
description: Apache Pinot is a real-time distributed OLAP datastore designed to deliver scalable real-time analytics with
  low latency. It ingests data from batch and streaming sources and provides fast analytical queries for user-facing applications.
type: Index
position: Consumer
access: 3rd-Party
image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
- Analytics
- Database
- Low Latency
- OLAP
- Real-Time
- Apache
- Open Source
created: '2026-03-16'
modified: '2026-05-19'
url: https://raw.githubusercontent.com/api-evangelist/apache-pinot/refs/heads/main/apis.yml
specificationVersion: '0.19'
apis:
- aid: apache-pinot:apache-pinot-rest-api
  name: Apache Pinot REST API
  description: The Pinot API provides REST endpoints for SQL queries, schema management, table management, segment management,
    cluster administration, and task management, along with a JDBC driver for SQL access.
  humanURL: https://docs.pinot.apache.org/
  tags:
  - Analytics
  - OLAP
  - REST
  - SQL
  - Apache
  - Open Source
  properties:
  - type: Documentation
    url: https://docs.pinot.apache.org/
  - type: OpenAPI
    url: openapi/apache-pinot-rest-api.yaml
  - type: NaftikoCapability
    url: capabilities/rest-cluster.yaml
  - type: NaftikoCapability
    url: capabilities/rest-queries.yaml
  - type: NaftikoCapability
    url: capabilities/rest-schemas.yaml
  - type: NaftikoCapability
    url: capabilities/rest-segments.yaml
  - type: NaftikoCapability
    url: capabilities/rest-tables.yaml
maintainers:
- FN: Kin Lane
  email: [email protected]
common:
- type: GitHubOrganization
  url: https://github.com/apache/pinot
- type: Documentation
  url: https://docs.pinot.apache.org/
- type: SpectralRules
  url: rules/apache-pinot-spectral-rules.yml
- type: Vocabulary
  url: vocabulary/apache-pinot-vocabulary.yaml
- type: JSONLD
  url: json-ld/apache-pinot-context.jsonld
- type: Features
  data:
  - name: Real-Time OLAP
    description: Sub-second analytical queries over real-time and historical data
  - name: SQL Support
    description: Standard SQL query interface with Pinot-specific extensions
  - name: Streaming Ingestion
    description: Real-time data ingestion from Kafka, Kinesis, and Pulsar
  - name: Batch Ingestion
    description: Offline data ingestion from HDFS, S3, GCS, and local files
  - name: Columnar Storage
    description: Column-oriented storage with bitmap indexing for fast queries
  - name: Multi-Tenancy
    description: Tenant isolation for broker and server resources
  - name: Star-Tree Index
    description: Pre-aggregated star-tree index for metric rollup queries
- type: UseCases
  data:
  - name: User-Facing Analytics
    description: Power user-facing dashboards like LinkedIn Who Viewed Profile
  - name: Real-Time Dashboards
    description: Business intelligence dashboards over streaming data
  - name: Anomaly Detection
    description: Real-time anomaly detection over metric time series
  - name: A/B Testing
    description: Real-time experiment analysis and statistical significance
- type: Integrations
  data:
  - name: Apache Kafka
    description: Real-time stream ingestion from Kafka topics
  - name: Apache Flink
    description: Flink connector for streaming data into Pinot
  - name: Apache Superset
    description: Visual analytics and dashboards via SQL
  - name: Presto/Trino
    description: Federated query access to Pinot via Presto connector
  - name: Grafana
    description: Grafana data source plugin for Pinot metrics
- type: LLMsTxt
  url: https://docs.pinot.apache.org/llms.txt