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features
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Description

Apache Kylin™ is a distributed, open-source Analytical Data Warehouse designed for Big Data, aimed at delivering OLAP (Online Analytical Processing) capabilities in the modern big data landscape. By enhancing multi-dimensional cube technology and precalculation methods on platforms like Hadoop and Spark, Kylin maintains a consistent query performance, even as data volumes continue to expand. This innovation reduces query response times from several minutes to just milliseconds, effectively reintroducing online analytics into the realm of big data. Capable of processing over 10 billion rows in under a second, Kylin eliminates the delays previously associated with report generation, facilitating timely decision-making. It seamlessly integrates data stored on Hadoop with popular BI tools such as Tableau, PowerBI/Excel, MSTR, QlikSense, Hue, and SuperSet, significantly accelerating business intelligence operations on Hadoop. As a robust Analytical Data Warehouse, Kylin supports ANSI SQL queries on Hadoop/Spark and encompasses a wide array of ANSI SQL functions. Moreover, Kylin’s architecture allows it to handle thousands of simultaneous interactive queries with minimal resource usage, ensuring efficient analytics even under heavy loads. This efficiency positions Kylin as an essential tool for organizations seeking to leverage their data for strategic insights.

Description

Pinot is built to efficiently handle OLAP queries on static data with minimal latency. It incorporates various pluggable indexing methods, including Sorted Index, Bitmap Index, and Inverted Index. While it currently lacks support for joins, this limitation can be mitigated by utilizing Trino or PrestoDB for querying purposes. The system offers an SQL-like language that enables selection, aggregation, filtering, grouping, ordering, and distinct queries on datasets. It comprises both offline and real-time tables, with real-time tables being utilized to address segments lacking offline data. Additionally, users can tailor the anomaly detection process and notification mechanisms to accurately identify anomalies. This flexibility ensures that users can maintain data integrity and respond proactively to potential issues.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Kafka
Astro by Astronomer
Hadoop
Hue
Amazon S3
Apache Hive
Apache Spark
Apache Superset
Azure Data Lake
Chat2DB
Kestra
Microsoft Excel
Microsoft Power BI
Onehouse
OpenMetadata
Preset
Qlik Sense
RATH
StarTree
Tableau

Integrations

Apache Kafka
Astro by Astronomer
Hadoop
Hue
Amazon S3
Apache Hive
Apache Spark
Apache Superset
Azure Data Lake
Chat2DB
Kestra
Microsoft Excel
Microsoft Power BI
Onehouse
OpenMetadata
Preset
Qlik Sense
RATH
StarTree
Tableau

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

kylin.apache.org

Vendor Details

Company Name

Apache Corporation

Founded

1954

Country

United Statess

Website

pinot.apache.org

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Alternatives

SSAS Reviews

SSAS

Microsoft

Alternatives

Apache Pinot Reviews

Apache Pinot

Apache Corporation
Apache Doris Reviews

Apache Doris

The Apache Software Foundation
Apache Doris Reviews

Apache Doris

The Apache Software Foundation