How it helps your business
Key Benefits
- Millisecond Query Latency: Optimized for interactive analytics.
- Real-Time Ingestion: Seamless integration with streaming platforms.
- Scalable Architecture: Independent scaling of brokers and servers.
- Flexible Indexing: Multiple index types for query acceleration.
- Production-Ready Resilience: Replication and fault-tolerant design.
Production Architecture Overview
- Controller: Manages cluster metadata and schema.
- Broker: Routes queries to appropriate servers.
- Server: Stores data segments and executes queries.
- Minion: Handles background tasks (compaction, retention).
- ZooKeeper: Cluster coordination.
- Streaming Source: Kafka for real-time ingestion.
- Distributed Storage: S3 or HDFS for segment backup.
- Monitoring Stack: Prometheus + Grafana.
- Load Balancer: Distributes query traffic across brokers.
How we deploy this for you
Security Hardened
Firewalls, SSL, and hardened kernels out of the box.
Performance Tuned
Optimized for speed with cache and DB fine-tuning.
Automated Backups
Daily off-site backups so you never lose your data.
Private Cloud
You own the server and the data. No middleman.
Implementation Blueprint
Prerequisites
sudo apt update && sudo apt upgrade -y
sudo apt install docker.io docker-compose -y
sudo systemctl enable docker
sudo systemctl start dockerDocker Compose (Single-Node Production Test Setup)
version: "3.8"
services:
zookeeper:
image: zookeeper:3.8
container_name: pinot-zookeeper
ports:
- "2181:2181"
pinot-controller:
image: apachepinot/pinot:latest
container_name: pinot-controller
command: StartController -zkAddress zookeeper:2181
ports:
- "9000:9000"
depends_on:
- zookeeper
pinot-broker:
image: apachepinot/pinot:latest
container_name: pinot-broker
command: StartBroker -zkAddress zookeeper:2181
ports:
- "8099:8099"
depends_on:
- pinot-controller
pinot-server:
image: apachepinot/pinot:latest
container_name: pinot-server
command: StartServer -zkAddress zookeeper:2181
ports:
- "8098:8098"
depends_on:
- pinot-controllerdocker-compose up -d
docker pshttp://localhost:9000Real-Time Table Configuration Example
{
"schemaName": "events",
"dimensionFieldSpecs": [
{ "name": "userId", "dataType": "STRING" }
],
"dateTimeFieldSpecs": [
{
"name": "eventTime",
"dataType": "LONG",
"format": "1:MILLISECONDS:EPOCH",
"granularity": "1:MILLISECONDS"
}
]
}{
"tableName": "events_REALTIME",
"tableType": "REALTIME",
"segmentsConfig": {
"replication": "3",
"schemaName": "events"
},
"streamConfigs": {
"streamType": "kafka",
"stream.kafka.topic.name": "events-topic",
"stream.kafka.broker.list": "kafka:9092"
}
}Scaling Strategy
- Deploy multiple brokers behind a load balancer.
- Scale servers horizontally based on data volume.
- Use replication factor ≥ 3.
- Separate real-time and offline workloads.
- Deploy across multiple availability zones.
Backup & Retention Strategy
- Enable segment push to S3 or HDFS.
- Configure retention policy:
"retentionTimeUnit": "DAYS",
"retentionTimeValue": "30"- Schedule automated segment compaction via Minion tasks.
- Regularly test segment restoration.
Monitoring & Observability
- Prometheus Pinot metrics exporter
- Grafana dashboards
- Alerts for:
- Server unavailability
- Segment load failures
- Query latency spikes
- Disk usage > 75%
-Dpinot.metrics.enable=trueSecurity Best Practices
- Enable TLS for broker and controller APIs.
- Restrict network exposure via VPC/firewall.
- Use authentication plugins for API access.
- Encrypt backups in object storage.
- Rotate Kafka credentials regularly.
- Monitor query logs for suspicious patterns.
High Availability Checklist
- Minimum 3 controllers in production
- Replication factor ≥ 3
- Multi-broker deployment
- Distributed storage backups enabled
- Load-balanced query layer
- Centralized monitoring and alerting
- Disaster recovery procedures tested
Includes Security & performance standards
Best place to host Apache Pinot
We recommend Hostinger for its reliability and low cost. It's the perfect home for your new apps, featuring easy setup and 24/7 support.
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