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APACHE PINOT

Real-time distributed OLAP datastore for instant analytics

Apache-2.0

ABOUT

Organizations building user-facing analytics and real-time dashboards often struggle with high query latency and low ingestion throughput when handling large-scale event data in traditional databases. Apache Pinot solves this by providing a horizontally scalable OLAP datastore that ingests from streaming sources with millisecond-level freshness, automatically indexes and compresses data for efficient storage, and serves complex aggregation queries with sub-second latency at high concurrency.

INSTALL
docker pull apachepinot/pinot:latest docker run -p 9000:9000 apachepinot/pinot:latest QuickStart -type batch

INTEGRATION GUIDE

1. Serve real-time analytics dashboards for AI model monitoring, user-facing metrics, and operational intelligence 2. Ingest and query high-throughput streaming event data from Kafka for instant business insights and anomaly detection 3. Power interactive OLAP workloads with sub-second query response times on multi-billion-row datasets 4. Build customer-facing analytics features that require high concurrency and low latency on real-time data

TAGS

databaseolapanalyticsreal-timebig-dataapachejavastreamingkafka