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Apache Pinot

Brand: The Apache Software Foundation

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A free open-source database that delivers real-time analytics with sub-second query speeds for user-facing applications.

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Apache Pinot Software Overview

What is Apache Pinot?

Apache Pinot is an open-source database management software designed for real-time analytics on massive datasets with ultra-low latency. It acts as a cloud services bridge between streaming data sources like Kafka and front-end applications.

Originally built at LinkedIn to power user-facing features like Who Viewed My Profile, Pinot delivers interactive insights in milliseconds, even at high concurrency levels, making it ideal for customer-facing dashboards and real-time personalization.

It bridges streaming and batch data seamlessly, enabling organizations to query fresh and historical data together without building separate systems.

Why Choose Apache Pinot?

  • Sub-second Query Performance: Delivers P90 latency in tens of milliseconds for instant data insights.
  • High Concurrency Handling: Serves hundreds of thousands of queries per second simultaneously.
  • Real-time and Batch Ingestion: Ingests data from streams like Kafka and batch sources like S3.
  • Unrivaled Indexing Support: Supports inverted, sorted, star-tree, text, and JSON indexes for fast retrieval.
  • Native Upsert Support: Updates existing records in real-time streams maintaining fresh data views.
  • Hybrid Tables: Blends real-time streaming data with historical batch data into a single queryable table.
  • Horizontally Scalable Architecture: No single point of failure with controller, broker, server, and minion components.
  • Columnar Data Storage: Optimizes aggregation queries for analytical workloads.

Benefits of Apache Pinot

  • Powers User-Facing Analytics: Enables interactive features like 'Who Viewed My Profile' at LinkedIn.
  • Provides Real-time Dashboards: Delivers up-to-the-second metrics for operational intelligence.
  • Enables Real-time Personalization: Fuels recommendation engines by analyzing behavior instantly.
  • Supports Anomaly Detection: Detects fraud or operational glitches as they happen.
  • Handles Massive Log Analysis: Manages large volumes of event logs with familiar SQL.
  • Outperforms Data Warehouses: Millisecond response times versus seconds for high QPS workloads.
  • Fresher Data Than Traditional Tools: Data becomes queryable within milliseconds of the event.
  • Reduces Infrastructure Costs: Open-source model eliminates licensing fees for database software.
  • Scales Without Downtime: Horizontally scalable with fault-tolerant design and no single point of failure.

Apache Pinot Pricing

Apache Pinot is available as a free open-source download at techjockey.com. The pricing model is based on different parameters, including extra features, deployment type, and the total number of users. For further queries related to the product, you can contact the product team to learn more about pricing and available offers.

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The Apache Software Foundation Company Details

Founded Year:  1999

Apache Software Foundation provides organizational, legal and financial support for Apache open-source software projects.

Director/Founders Brian Behlendorf, Grant Ingersoll, Isabel Drost-Fromm, Jim Jagielski, Lars Eilebrecht, Patrick Stued
Company Size 1-100 Employees

Apache Pinot Pricing & Plans

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Apache Pinot Features

  • icon_check Data Ingestion
    Continuously ingests streaming data from sources like Kafka, enabling instant analytics on fresh data streams.
  • icon_check Low-Latency Query Processing
    Delivers millisecond-level query responses even on large-scale datasets for interactive analytics use cases.
  • icon_check Columnar Storage
    Stores data in columnar format, improving compression and enabling faster aggregation and filtering operations.
  • icon_check Distributed Architecture
    Uses a cluster-based design with brokers, servers, and controllers to ensure scalability and fault tolerance.
  • icon_check Horizontal Scalability
    Scales seamlessly by adding nodes, allowing it to handle growing data volumes and high query workloads.
  • icon_check SQL Query Support
    Provides ANSI SQL-like query interface, making it easy for analysts to explore and query datasets efficiently.
  • icon_check Advanced Indexing
    Supports inverted, star-tree, range, and JSON indexes to optimize query performance across diverse datasets.
  • icon_check Upsert Capability
    Allows updating existing records by maintaining the latest version of data for real-time consistency.
  • icon_check Multi-Tenancy
    Enables isolation of workloads across teams or applications, ensuring performance and resource management.
  • icon_check Data Partitioning
    Distributes data across nodes using partitioning strategies to improve query efficiency and scalability.
  • icon_check Stream Processing Integration
    Integrates with streaming systems like Kafka and Pulsar for seamless real-time data pipeline ingestion.
  • icon_check JSON Data Support
    Allows querying and indexing of semi-structured JSON data for flexible schema and analytics use cases.
  • icon_check Time Series Optimization
    Optimized for time-based queries, making it ideal for monitoring, metrics, and event-driven analytics.
  • icon_check Pluggable Architecture
    Supports custom extensions and plugins for ingestion, indexing, and query processing enhancements.

Apache Pinot Specifications

Supported Platforms
Windows Windows
Devices
Desktop Desktop
Deployment
Perpetual Perpetual
Suitable For
All Industries
Business Specific
All Businesses
Business Size
Small Business Startups Medium Business Enterprises
Customer Support
Email Communities
Language
English

Apache Pinot Review

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How much does Apache Pinot cost?

Apache Pinot is available as a free open-source download at Techjockey.com.

How does Apache Pinot work?

Pinot ingests streaming data from sources like Kafka and batch data from S3, stores it in columnar format with advanced indexes, and serves queries through broker nodes that route requests to server nodes holding data segments.

Who uses Apache Pinot?

It is used by companies like LinkedIn, Uber, and Stripe to power user-facing analytics, real-time dashboards, and personalization features.

What is a hybrid table?

It combines real-time streaming data with historical batch data into one queryable table for unified analytics.

Can it handle upserts?

Yes, Pinot supports native upserts in real-time streams, allowing updates and deletions of existing records.

What indexing options are available?

Pinot supports inverted, sorted, star-tree, text, JSON, and geospatial indexes for fast data retrieval.

Is it good for log analysis?

Yes, Pinot excels at managing large volumes of event logs with SQL-based querying.

How is it different from Druid?

Pinot is more optimized for user-facing applications with high QPS and superior upsert capabilities.

What query language does it use?

Pinot uses standard SQL for querying its columnar data storage.

Can it replace my data warehouse?

Pinot is designed for low-latency user-facing analytics, while data warehouses are better for complex ad-hoc ETL as they work well together.

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