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Apache Pinot

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by Apache Software Foundation · since 2015 · also known as Pinot

Real-time OLAP store from LinkedIn for user-facing analytics at very high query rates.

columnar / olaprelationaltime-seriesdatabase engineopen source (permissive)mature
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Overview

Apache Pinot is a distributed columnar datastore designed to serve analytics to end users: think 'who viewed my profile' at LinkedIn scale. It ingests from Kafka and batch sources, supports upserts on streaming data, and offers a rich index menu (inverted, sorted, range, star-tree, JSON, text, geospatial H3, vector) so queries stay in the millisecond range at tens of thousands of QPS. The multi-stage engine adds distributed joins. Pinot is excellent when latency and concurrency matter more than SQL breadth; it needs a ZooKeeper-backed cluster and careful table and index design.

Real-time analyticsAnalytics (OLAP)Observability

Strengths & trade-offs

Strengths

  • +Millisecond latency at tens of thousands of queries per second
  • +Star-tree index pre-aggregates for predictable fast group-bys
  • +Real-time upserts on Kafka streams for mutable entities
  • +Broad index types: inverted, range, JSON, text, H3 geospatial, vector
  • +Proven at LinkedIn, Uber and Stripe scale

Trade-offs

  • −Requires ZooKeeper (or Helix) plus several component types to operate
  • −Schema and index design is manual and drives performance
  • −SQL coverage and join support trail general-purpose warehouses
  • −Smaller ecosystem of BI connectors than mainstream warehouses

Great for

  • +User-facing analytics in products
  • +Real-time business metrics and anomaly detection
  • +Ad and marketplace analytics
  • +Operational dashboards on streaming data

Think twice for

  • −Ad-hoc warehouse exploration with heavy joins
  • −OLTP
  • −Small single-node analytics

Capabilities

Native or official first-party support · 12 of 25 tracked

✓Joins
✓Secondary indexes
✓Full-text search
✓Vector search
✓Geospatial
✓JSON
✓TTL / expiry
✓Columnar storage
✓Durable persistence
✓Compression
✓Role-based access
✓Streaming ingest
–Transactions
–Change data capture
–Triggers
–Stored procedures
–Materialized views
–Pub/Sub
–In-memory
–Encryption at rest
–Time travel
–Branching
–Online schema changes
–Offline sync
–Runs in WebAssembly

Scale & consistency

Comfortable data size
Massive · Multi-PB
Horizontal scaling
Native
Multi-region
No
Transactions
None
Consistency
Eventual
Schema
Strict
Architecture
Distributed, Shared storage
Query languages
SQL (Calcite-based)

Controllers, brokers, servers and minions scale independently; tiered storage offloads old segments to S3.

Deployment

Self-hosted Vendor-managed cloud Serverless Embedded Edge Kubernetes operator
StarTree CloudStarTree

Ecosystem

apis & protocolsHTTP/JSON broker API, JDBC, gRPC
client languagesJava, Python, Go, JavaScript, C#
used byLinkedIn, Uber, Stripe

Alternatives to Apache Pinot

Compare all→
Apache DruidColumnar / OLAP35.0

Real-time analytics database for sub-second slice-and-dice over streaming event data.

apache-pinot vs apache-druid →
ClickHouseColumnar / OLAP69.8

Open-source columnar OLAP database known for very fast aggregations over billions of rows.

apache-pinot vs clickhouse →
StarRocksColumnar / OLAP15.6

MPP OLAP database with a fast vectorized engine, real-time upserts and native lakehouse queries.

apache-pinot vs starrocks →
Apache DorisColumnar / OLAP15.9

Real-time MPP analytical database with MySQL compatibility, search indexes and lakehouse access.

apache-pinot vs apache-doris →
RocksetDocument0.4

Former real-time search and analytics cloud on RocksDB, shut down after OpenAI acquired it in 2024.

apache-pinot vs rockset →
TinybirdColumnar / OLAP12.6

Managed ClickHouse platform that turns SQL pipes into low-latency, versioned HTTP APIs.

apache-pinot vs tinybird →

Apache Pinot FAQ

What is Apache Pinot?

Apache Pinot is a columnar / OLAP database by Apache Software Foundation, first released in 2015. Apache Pinot is a distributed columnar datastore designed to serve analytics to end users: think 'who viewed my profile' at LinkedIn scale. It ingests from Kafka and batch sources, supports upserts on streaming data, and offers a rich index menu (inverted, sorted, range, star-tree, JSON, text, geospatial H3, vector) so queries stay in the millisecond range at tens of thousands of QPS. The multi-stage engine adds distributed joins. Pinot is excellent when latency and concurrency matter more than SQL breadth; it needs a ZooKeeper-backed cluster and careful table and index design.

Is Apache Pinot open source?

Yes. Apache Pinot is open source. License: Apache License 2.0.

Does Apache Pinot support ACID transactions?

No. Apache Pinot does not provide ACID transactions; its consistency model is eventual.

Does Apache Pinot scale horizontally?

Apache Pinot scales horizontally out of the box, with built-in sharding or partitioning. It is comfortable at massive scale (Multi-PB).

How can I run Apache Pinot?

You can self-host it. Managed offerings include StarTree Cloud.

What is Apache Pinot best for?

Apache Pinot is a strong fit for user-facing analytics in products; real-time business metrics and anomaly detection; and ad and marketplace analytics. Think twice for ad-hoc warehouse exploration with heavy joins.

What are the best alternatives to Apache Pinot?

Common alternatives to Apache Pinot include Apache Druid, ClickHouse, StarRocks, Apache Doris and Rockset. The right choice depends on your workload, scale and hosting; WhichDB's smart match ranks them against your requirements.

How popular is Apache Pinot?

Apache Pinot ranks #88 of 844 databases on the WhichDB Score (29.9/100), and #12 among columnar / OLAP databases. The score combines public adoption signals such as package downloads, GitHub activity, job posts and developer discussion.