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Apache Pinot logo Apache Pinot-analytics Apache Pinot-features Apache Pinot-ai agents Apache Pinot-benefits
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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. ...Read more

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Apache Pinot Software Pricing, Features & Reviews

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.

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 :
  • Device:
  • Deployment :
  • Suitable For :
  • Business Specific:
  • Business Size:
  • Customer Support:
  • Language:
  • Windows
  • Desktop
  • Perpetual
  • All Industries
  • All Businesses
  • Small Business, Startups, Medium Business, Enterprises
  • Email, Communities
  • English

Apache Pinot Reviews and Ratings

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The Apache Software Foundation Company Details

Brand Name The Apache Software Foundation
Information Apache Software Foundation provides organizational, legal and financial support for Apache open-source software projects.
Founded Year 1999
Director/Founders Brian Behlendorf, Grant Ingersoll, Isabel Drost-Fromm, Jim Jagielski, Lars Eilebrecht, Patrick Stued
Company Size 1-100 Employees
Other Products Apache Airflow, Apache Flink, Apache HBase, Apache Jmeter, Apache Kafka

Apache Pinot FAQ

A Apache Pinot is available as a free open-source download at Techjockey.com.
A 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.
A It is used by companies like LinkedIn, Uber, and Stripe to power user-facing analytics, real-time dashboards, and personalization features.
A It combines real-time streaming data with historical batch data into one queryable table for unified analytics.
A Yes, Pinot supports native upserts in real-time streams, allowing updates and deletions of existing records.
A Pinot supports inverted, sorted, star-tree, text, JSON, and geospatial indexes for fast data retrieval.
A Yes, Pinot excels at managing large volumes of event logs with SQL-based querying.
A Pinot is more optimized for user-facing applications with high QPS and superior upsert capabilities.
A Pinot uses standard SQL for querying its columnar data storage.
A 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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