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What is Apache Pinot?

Pinot is designed to optimize the handling of OLAP queries with low latency when working with static data. It supports a variety of pluggable indexing techniques, such as Sorted Index, Bitmap Index, and Inverted Index. Although it does not currently facilitate joins, this can be circumvented by employing Trino or PrestoDB for executing queries. The platform offers an SQL-like syntax that enables users to perform selection, aggregation, filtering, grouping, ordering, and distinct queries on the data. It comprises both offline and real-time tables, where real-time tables are specifically implemented to fill gaps in offline data availability. Furthermore, users have the capability to customize the anomaly detection and notification processes, allowing for precise identification of significant anomalies. This adaptability ensures users can uphold robust data integrity while effectively addressing their analytical requirements, ultimately enhancing their overall data management strategy.

What is Apache Doris?

Apache Doris is a sophisticated data warehouse specifically designed for real-time analytics, allowing for remarkably quick access to large-scale real-time datasets. This system supports both push-based micro-batch and pull-based streaming data ingestion, processing information within seconds, while its storage engine facilitates real-time updates, appends, and pre-aggregations. Doris excels in managing high-concurrency and high-throughput queries, leveraging its columnar storage engine, MPP architecture, cost-based query optimizer, and vectorized execution engine for optimal performance. Additionally, it enables federated querying across various data lakes such as Hive, Iceberg, and Hudi, in addition to traditional databases like MySQL and PostgreSQL. The platform also supports intricate data types, including Array, Map, and JSON, and includes a variant data type that allows for the automatic inference of JSON data structures. Moreover, advanced indexing methods like NGram bloomfilter and inverted index are utilized to enhance its text search functionalities. With a distributed architecture, Doris provides linear scalability, incorporates workload isolation, and implements tiered storage for effective resource management. Beyond these features, it is engineered to accommodate both shared-nothing clusters and the separation of storage and compute resources, thereby offering a flexible solution for a wide range of analytical requirements. In conclusion, Apache Doris not only meets the demands of modern data analytics but also adapts to various environments, making it an invaluable asset for businesses striving for data-driven insights.

Media

Media

Integrations Supported

OpenMetadata
Amazon S3
Apache Kafka
Astro by Astronomer
Azure Data Lake
Hadoop
Hue
Kestra
Onehouse
StarTree

Integrations Supported

OpenMetadata
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
Dosi
MySQL
PostgreSQL
SelectDB
TapData
VeloDB

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Apache Corporation

Date Founded

1954

Company Location

United Statess

Company Website

pinot.apache.org

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

doris.apache.org

Categories and Features

Columnar Databases

Not specified

OLAP Databases

Not specified

Categories and Features

Data Warehouse

Not specified

OLAP Databases

Not specified

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