Last updated on
Company health
Ratings
Apache Pinot description
Apache Pinot is an open-source software designed for analyzing large volumes of data and getting rapid results. It's like a high-performance database that excels at quickly finding answers within massive datasets, even when handling a huge number of requests at the same time. Pinot achieves this speed by organizing data efficiently and using smart techniques for searching and filtering. This makes it suitable for applications that need to make sense of data in real time, like dashboards, reporting systems, and user-facing analytics.
Who is Apache Pinot best for
Apache Pinot is a powerful open-source database for real-time analytics on large datasets. It's designed for data engineers and developers at medium to large companies, particularly in e-commerce, finance, and technology, who need to analyze massive datasets with millisecond-level latency. Pinot's ability to handle high concurrency makes it ideal for user-facing applications.
-
Ideal for medium to large enterprises (101+ employees).
-
Best fit for Finance, E-commerce, and Tech.
Apache Pinot features
Supported Pinot enables filtering and aggregation of petabyte-scale datasets with P90 latencies in tens of milliseconds. |
Supported Pinot can handle hundreds of thousands of concurrent queries per second for direct user-facing applications. |
Supported Pinot ingests data in real-time from Apache Kafka, Apache Pulsar, and AWS Kinesis. |
Supported Pinot supports batch ingestion from Hadoop, Spark, AWS S3, and other sources. |
Supported Pinot allows combining batch and streaming data sources into a single table. |
Supported Pinot has built-in upsert functionality to ensure only the latest record value is visible during queries. |
Supported Pinot supports various joins, including fact/dimension and fact/fact joins, on petabyte-scale datasets. |
Apache Pinot pricing
The commentary is based on 1 reviews from Apache Pinot G2 reviews.
Apache Pinot is praised for its low cost compared to other SaaS solutions, particularly its low cost-per-GB data ingestion. Its multi-tenant architecture allows for workload and cost splitting, contributing to its affordability.
See the Apache Pinot pricing page.
-
Apache Pinot has a free plan.
Apache Pinot alternatives
Apache Pinot FAQ
Apache Pinot is an open-source real-time analytics database designed for low-latency queries on large datasets. It handles high concurrency and ingests both batch and streaming data, making it ideal for user-facing analytics, dashboards, and reporting.
What is Apache Pinot and what does Apache Pinot do?
Apache Pinot is an open-source real-time analytics database designed for low-latency queries on large datasets. It handles high concurrency and ingests both batch and streaming data, making it ideal for user-facing analytics, dashboards, and reporting.
Apache Pinot integrates with various data ingestion tools like Apache Kafka, Apache Pulsar, and AWS Kinesis. It also supports batch ingestion from Hadoop, Spark, and AWS S3, allowing for versatile data integration. It seamlessly connects with visualization tools, enabling real-time dashboards and reporting.
How does Apache Pinot integrate with other tools?
Apache Pinot integrates with various data ingestion tools like Apache Kafka, Apache Pulsar, and AWS Kinesis. It also supports batch ingestion from Hadoop, Spark, and AWS S3, allowing for versatile data integration. It seamlessly connects with visualization tools, enabling real-time dashboards and reporting.
Apache Pinot's main competitors include Rockset, CrateDB, DuckDB, SingleStore, StarTree, and Cloudera Analytic DB. These alternatives offer similar real-time analytics capabilities for large datasets.
What the main competitors of Apache Pinot?
Apache Pinot's main competitors include Rockset, CrateDB, DuckDB, SingleStore, StarTree, and Cloudera Analytic DB. These alternatives offer similar real-time analytics capabilities for large datasets.
Yes, Apache Pinot is a legitimate open-source real-time analytics database. It's known for its speed and scalability in handling large datasets, making it safe for high-volume data analysis and real-time applications. Apache Pinot is trusted by various organizations for demanding analytical workloads.
Is Apache Pinot legit?
Yes, Apache Pinot is a legitimate open-source real-time analytics database. It's known for its speed and scalability in handling large datasets, making it safe for high-volume data analysis and real-time applications. Apache Pinot is trusted by various organizations for demanding analytical workloads.
Apache Pinot is open-source software, so it's free to use. However, users bear the costs associated with infrastructure, resources, and potential support or consulting services if needed. Therefore, determining if Apache Pinot is "worth it" depends entirely on your specific needs and resources.
How much does Apache Pinot cost?
Apache Pinot is open-source software, so it's free to use. However, users bear the costs associated with infrastructure, resources, and potential support or consulting services if needed. Therefore, determining if Apache Pinot is "worth it" depends entirely on your specific needs and resources.
There is no customer service information available for Apache Pinot. However, it's worth noting that Apache Pinot is an open-source platform, so support may primarily come from community forums and documentation.
Is Apache Pinot customer service good?
There is no customer service information available for Apache Pinot. However, it's worth noting that Apache Pinot is an open-source platform, so support may primarily come from community forums and documentation.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.