CIOPages
For vendorsCorrections to your listing are free
Fix an error, free List a company, free Order a Spotlight listingAbout Spotlight listings
DirectoryData & AnalyticsStreaming & Real-Time AnalyticsPinot (Apache)

Pinot (Apache)

Open Source

About Pinot (Apache)

Apache Pinot is an open-source distributed OLAP database for user-facing and agent-facing real-time analytics. It delivers sub-second queries on fresh data at petabyte scale. It uses a distributed architecture and columnar storage. Pinot is used to ingest and immediately query data from streaming or batch data sources.

Used for

  • Shipping interactive dashboards inside a product
  • Letting customers explore their own data in real time
  • Exposing low-latency analytics endpoints for leaderboards, usage meters, and reporting
  • Retrieving real-time context from streaming data for LLMs
  • Feeding live signals to models that act in milliseconds

From Pinot (Apache)'s own website, read 2026-10-23. How we build listings.

How to evaluate Streaming & Real-Time Analytics

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Pinot (Apache). It comes from our Streaming Data & Event Processing buyer guide.

25%
Throughput, Latency & Durability
Sustained throughput and tail latency at your partition count, ordering and exactly-once / at-least-once delivery guarantees, replication and multi-AZ durability, retention limits, and behavior under broker failure and rebalancing
20%
Operating Model & Architecture
Self-managed vs. fully managed vs. serverless vs. bring-your-own-cloud, KRaft (post-ZooKeeper) operations, diskless / object-storage-backed options, autoscaling, partition rebalancing, and upgrade and patching burden on your team
20%
Kafka-API Compatibility & Portability
Fidelity of the Kafka protocol (consumer groups, transactions, compaction), reuse of existing clients, connectors and tooling, lock-in to a single cloud, and the realistic effort to migrate in or out
15%
Stream Processing & Ecosystem
Native or integrated processing (Flink, Kafka Streams, Spark Structured Streaming, ksqlDB), connector catalog (CDC, sinks, sources), schema registry and governance, and direct landing into Iceberg / Delta lakehouse tables
10%
Security, Governance & Compliance
Encryption in transit and at rest, mTLS / SASL / OAuth and RBAC, audit logging, private networking, data residency and BYOC data-boundary control, and SOC 2 / ISO 27001 / GDPR coverage
10%
Cost Model & Economics at Scale
Pricing unit (capacity / throughput / consumption), inter-AZ and egress charges, storage and retention cost, processing billed separately, and how the bill behaves as volume, partitions, and connectors grow

CIOPages put this listing together from public sources. It’s information, not an endorsement. How we build listings. Work here? Claim this listing or .

Quick Facts

pinot.apache.org
CategoryData & Analytics
SubcategoryStreaming & Real-Time Analytics

We publish a detail only when we can point at the page it came from. Know when Pinot (Apache) was founded or where it is based? Send it to us, free.

Keep reading

Buyer Guide
Real-Time Analytics Databases
Toolkits
Frameworks and templates

Capability models, architecture templates and IT strategy tools to download.

Job 05
Modernize the estate

AI agents need clean data and systems they can call, and old systems block both.