Apache Pinot Realtime OLAP Datastore

This is a repackaged open source software product wherein additional charges apply for cloudimg support services.

## Apache Pinot - Production-Ready Real-Time OLAP Datastore AMI

Deploy a fully configured Apache Pinot analytics datastore on AWS in minutes - not hours. This AMI delivers Pinot preinstalled and running as a managed single-instance cluster, so you can create tables, ingest batch and streaming data, and run low-latency SQL analytics from the built-in web console immediately after launch.

Built for data engineers and analytics teams who need a production-grade OLAP datastore for user-facing analytics without the overhead of manual installation, JVM tuning and security hardening - especially teams that need sub-second queries over event and time-series data feeding dashboards.

### Why This AMI Instead of a DIY Install

• Versus manual EC2 setup: Skip the hours of installing a Java runtime, verifying the Pinot distribution, wiring up ZooKeeper, the Controller, Broker and Server, writing systemd units, provisioning a data disk and tuning JVM memory so the cluster fits your instance.
• Versus a raw upstream install: Pinot's Controller console and Broker query endpoint ship with no authentication. This image keeps every Pinot component and ZooKeeper off the public network and fronts the console with an authenticated nginx reverse proxy, so the only exposed application entry point is a password-protected console on port 80.
• Versus other community AMIs: Benefit from a first-boot process that generates a unique console password per instance, a dedicated data disk for cluster state and segments, JVM heaps sized to the recommended instance, and 24/7 professional support from cloudimg.

### Application Stack

• Apache Pinot installed under /opt/pinot, run by a dedicated unprivileged service account
• A single-instance cluster: the bundled ZooKeeper, the Pinot Controller (web console), the Pinot Broker (query endpoint) and the Pinot Server, each a systemd service
• Headless OpenJDK 17 Java runtime with JVM heaps sized to fit the recommended instance
• A dedicated EBS data disk holding the ZooKeeper data, Controller segment store and Server segments - independently resizable for IOPS and capacity
• systemd services that start the cluster in dependency order on boot and restart on failure
• nginx reverse proxy publishing the authenticated Pinot console on port 80

### Real-Time OLAP and Web Console

Pinot is built for low-latency, high-concurrency analytics over large event and time-series datasets. Create a schema and table, ingest streaming or batch data, then explore it with sub-second aggregations, filters and time-range scans. The web console (served on port 80 through nginx) provides a SQL query editor, a table and schema manager, a cluster and instance view and an ingestion job manager; Pinot also exposes a SQL-over-HTTP query API through the Broker for your applications and dashboards. See our deployment guide for annotated console walkthrough screenshots and a worked batch-ingestion example.

### Security

Secure First Boot: A one-shot service generates a fresh console password unique to each instance and stores it in a root-only file. No shared or default credentials ship in the image.

Network Isolation: Every Pinot component and the bundled ZooKeeper stay off the public network - the security group exposes only port 22 (SSH) and port 80 (the authenticated console). The single public application entry point is the nginx reverse proxy on port 80, protected by HTTP basic authentication. Restrict port 80 to your own CIDR and terminate TLS at a load balancer or proxy for production.

Encryption at Rest: The dedicated data disk can leverage AWS EBS encryption. Enable EBS encryption when launching the instance or use encrypted snapshots.

### Use Cases

• User-facing analytics: power sub-second, high-concurrency dashboards and in-product metrics over event data for your own customers.
• Real-time operational monitoring over streaming event data, with fast group-bys and time-range filters.
• Interactive exploration of time-series and clickstream data with low-latency SQL over billions of rows.

### Evaluation Path

Launch this AMI on the recommended instance type to evaluate Pinot with minimal AWS infrastructure cost. Use the web console's query editor and the worked batch-ingestion example in our guide to validate table creation, ingestion and query before scaling up.

### 24/7 cloudimg Support

Technical support by email and live chat covers deployment and instance sizing, schema and table design, batch and streaming ingestion configuration, query tuning, JVM and memory administration, and console authentication and TLS setup.

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