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What is Apache Flume?

Flume serves as a powerful service tailored for the reliable, accessible, and efficient collection, aggregation, and transfer of large volumes of log data across distributed systems. Its design is both simple and flexible, relying on streaming data flows that provide robustness and fault tolerance through multiple reliability and recovery strategies. The system features a straightforward and extensible data model, making it well-suited for online analytical applications. The Apache Flume team is thrilled to announce the launch of Flume 1.8.0, which significantly boosts its capacity to handle extensive streaming event data effortlessly. This latest version promises enhanced performance and improved efficiency in the management of data flows, ultimately benefiting users in their data handling processes. Furthermore, this update reinforces Flume's commitment to evolving in response to the growing demands of data management in modern applications.

What is Apache Druid?

Apache Druid stands out as a robust open-source distributed data storage system that harmonizes elements from data warehousing, timeseries databases, and search technologies to facilitate superior performance in real-time analytics across diverse applications. The system's ingenious design incorporates critical attributes from these three domains, which is prominently reflected in its ingestion processes, storage methodologies, query execution, and overall architectural framework. By isolating and compressing individual columns, Druid adeptly retrieves only the data necessary for specific queries, which significantly enhances the speed of scanning, sorting, and grouping tasks. Moreover, the implementation of inverted indexes for string data considerably boosts the efficiency of search and filter operations. With readily available connectors for platforms such as Apache Kafka, HDFS, and AWS S3, Druid integrates effortlessly into existing data management workflows. Its intelligent partitioning approach markedly improves the speed of time-based queries when juxtaposed with traditional databases, yielding exceptional performance outcomes. Users benefit from the flexibility to easily scale their systems by adding or removing servers, as Druid autonomously manages the process of data rebalancing. In addition, its fault-tolerant architecture guarantees that the system can proficiently handle server failures, thus preserving operational stability. This resilience and adaptability make Druid a highly appealing option for organizations in search of dependable and efficient analytics solutions, ultimately driving better decision-making and insights.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Amundsen
Apache Airflow
Apache Kafka
Apache Superset
Azure Marketplace
DataHub
Gravity Data
Hue
Imply
Manticore Search
Metabase
Observo AI
Onum
Preset
Stackable
StrongDM
Yandex Data Proc

Integrations Supported

Amazon Web Services (AWS)
Amundsen
Apache Airflow
Apache Kafka
Apache Superset
Azure Marketplace
DataHub
Gravity Data
Hue
Imply
Manticore Search
Metabase
Observo AI
Onum
Preset
Stackable
StrongDM
Yandex Data Proc

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

flume.apache.org

Company Facts

Organization Name

Druid

Date Founded

2013

Company Website

druid.apache.org/technology

Categories and Features

Data Warehouse

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

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Warehouse

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

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

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