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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