#5555th of 146 in Backends, databases and hosting

pinot

Distributed real-time OLAP datastore with SQL queries over streaming and batch data

Stars
6.2k
License
Apache-2.0
Last commit
Nov 2026
Last release
Oct 2026
Language
Java
Stars, last 29 weeks+132
22 Apr 2026: 6,042 stars29 Apr 2026: 6,043 stars6 May 2026: 6,048 stars13 May 2026: 6,056 stars20 May 2026: 6,058 stars27 May 2026: 6,064 stars3 Jun 2026: 6,073 stars10 Jun 2026: 6,077 stars17 Jun 2026: 6,079 stars24 Jun 2026: 6,080 stars1 Jul 2026: 6,087 stars8 Jul 2026: 6,091 stars15 Jul 2026: 6,098 stars22 Jul 2026: 6,104 stars29 Jul 2026: 6,109 stars5 Aug 2026: 6,113 stars12 Aug 2026: 6,117 stars19 Aug 2026: 6,117 stars26 Aug 2026: 6,123 stars2 Sept 2026: 6,125 stars9 Sept 2026: 6,128 stars16 Sept 2026: 6,135 stars23 Sept 2026: 6,142 stars30 Sept 2026: 6,145 stars7 Oct 2026: 6,150 stars14 Oct 2026: 6,155 stars21 Oct 2026: 6,165 stars28 Oct 2026: 6,170 stars4 Nov 2026: 6,173 stars11 Nov 2026: 6,174 stars

6,042 on 22 Apr 20266,174 on 11 Nov 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

Apache Pinot is a column-oriented distributed datastore for low-latency analytical SQL on fresh data. It ingests from Kafka, Pulsar and Kinesis as well as batch sources such as HDFS, S3, ADLS and GCS, and can combine both in one table. It also offers vector similarity search, with a built-in query console and REST API.

Who it is for: Teams building user-facing real-time analytics on streaming data at scale

Strengths

  • Pluggable indexes: timestamp, inverted, StarTree, Bloom, range, text, JSON, geospatial
  • Real-time ingest from Kafka, Pulsar and Kinesis, with upserts and batch/stream hybrid tables
  • Joins, built-in multitenancy and a Helm chart for Kubernetes clusters
  • Vector index supports semantic search and RAG on the same SQL engine

Weaknesses

  • Multi-component cluster to operate; not a single-process database
  • Building from source requires JDK 25+ and a long Maven build
  • Suited to immutable, time-series style analytics rather than transactional workloads
  • Lucene upgrades or downgrades can trigger index rebuilds, adding CPU and load time

What it needs

  • RAM ≥ 6 GB
  • no GPU
  • Needs Apache Kafka (optional, for streaming ingest), Kubernetes/Helm (optional, for cluster deployment), JDK 25+ (to build)
  • port 9000

What changed

  1. “Pinot services now require Java 25 or newer to build and run. Java/JDBC”

  2. release-1.5.1 ↗ (opens in a new tab)BreakingSecurity fix

    “Drop-in security update for 1.5.0 — no behavioral changes.”

    CVE-2025-55163, CVE-2025-59419, CVE-2026-33870, CVE-2026-33871, CVE-2026-42579, CVE-2026-42583, CVE-2026-42584, CVE-2026-42587, CVE-2026-34478, CVE-2026-34479, CVE-2026-34480, CVE-2026-34481, CVE-2026-45300, CVE-2026-40542, CVE-2026-5598, CVE-2026-0636, CVE-2026-5588, CVE-2026-45205, CVE-2026-2332. “Apache Pinot 1.5.1 is a security patch release based on 1.5.0. It contains only dependency updates and dependency-exclusion changes to resolve reported CVEs — no functional, API, configuration, or wi…”

  3. “TLS protocol allowlist: Allow configuring permitted TLS protocols and hardened JVM SSL initialization. #17776”

From the release notes. No flag means the note does not say so, not that the upgrade is safe.

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