BI reporting and analysis of data visualization, recommended three open source tools!

Open source article

A, Superset

1, Technical Architecture: Python + Flask + React + Redux + SQLAlchemy

2, use of the crowd:

(1) Development / analysts do Kanban, Kanban business people browsing data

(2) business people can edit charts to see the results that satisfy the conditions, but the use is not very friendly to business people

3, installation and deployment:

(1) installation of the easiest ways to deploy docker

4, Source: supports a variety of data sources, including Hive, Kylin etc.

5, create the steps of: connecting a data source -> defined Table / SQL Query -> Chart -> Kanban

6, Visualization:

(1) supported chart types and more, up to 47 kinds

(2) less graph visualization options, e.g., data formatting options too few, To add, modify the configuration file

(3) can be added to the filter box in the kanban, supports viewing under different conditions

(4) does not support the group management charts and Kanban

(5) does not provide the function chart of the drill, does not support complex interaction between multiple charts

(6) is not supported across the table associated with the query libraries

7, supporting documentation:

(1) Quick Start Installation and deployment aspects of the document details

(2) However, the specific features and aspects of the chart describes the document produced almost no need to try to find their own way

8, mail notification: not supported

9, rights management:

(1) Report permissions complex, cumbersome, difficult to use

(2) may be implemented on the menu, data sources, data tables, fields, graphs, and other access control kanban

10, the second development:

(1) support RESTful API

(2) formerly Airbnb open source project, our team has a big maintenance, version updates, Bug fixes, secondary development have greater protection.

11, source code: code quality is poor

12, Github star number: 22132

BI reporting and analysis of data visualization, recommended three open source tools!

 

BI reporting and analysis of data visualization, recommended three open source tools!

 

 

Two, Redash

1, Technical Architecture: Python + Flask + AngularJS + SQLAlchemy

2. Use the crowd: Is the SQL query results visualization, need to develop / analysts do Kanban, Kanban business people browsing data.

3, installation and deployment:

(1) mounted relatively cumbersome to deploy

(2) Reference document:

4, data source: data source that supports less than a superset, do not support Kylin

5, create the steps of: connecting data sources -> SQL query -> Chart -> Kanban

6, Visualization:

(1) supported chart types as good as Superset more, only 12 kinds

(2) multi-chart visualization options

(3)不支持在看板种添加筛选框

(4)不支持图表和看板分组管理

(5)没有提供图表的下钻功能,不支持多图表间的复杂联动

(6)不支持跨库的表关联查询

7、支持文档:

(1)提供快速入门教程

(2)每一个功能模块都有文档且条理清晰

8、邮件通知:支持定时发送邮件

9、权限管理:权限设置简单,仅控制用户组对数据源的权限(只有两个权限:Full access或View only)

10、二次开发:

(1)提供完整的 RESTful API 接口

11、源代码:代码质量比Superset要好,但比Metabase差一点

12、Github星数:10891

BI reporting and analysis of data visualization, recommended three open source tools!

 

BI reporting and analysis of data visualization, recommended three open source tools!

 

 

三、Metabase

1、技术架构:Clojure + React + Redux

2、使用人群:界面漂亮、友好,使用体验好,适合业务人员使用

3、安装部署:

(1)windows下安装部署非常简单

4、数据源:支持数据源少(12种),不支持Hive、Kylin

5、创建步骤:连接数据源-->图表-->看板-->定时任务

6、可视化:

(1)支持的图表类型不如superset多,仅14种

(2)图表可视化选项多,例如,提供数据格式多,设置灵活

(3)可在看板中添加筛选框,支持在不同条件下查看

(4)通过创建集合,支持图表、看板、定时任务分组管理

(5)提供图表的简单钻取功能,不支持图表间的复杂联动

(6)不支持跨库的表关联查询

7、支持文档:

(1)安装部署、快速入门、具体功能、API等方面的文档详细

8、邮件通知:支持定时发送邮件

9、权限管理:

(1)权限设置单一,只有访问权限

(2)仅实现对数据源、数据表、图表、集合等权限控制

10、二次开发:提供完整的API文档,即使完全不会 Clojure,依然可以凭借丰富的 API 与文档完成许多二次开发。

11、源代码:代码质量最好,结构清晰,整洁度高

12、Github星数:12368

BI reporting and analysis of data visualization, recommended three open source tools!

 

最后,几个开源BI工具的详细对比

BI reporting and analysis of data visualization, recommended three open source tools!

 

最后,除了以上的开源BI产品(大规模推广应用还是有难度的),可以试试个人版免费的FineBI,学习文档,产品稳定性,易用性相对开源都比较成熟。

FineBI

1、技术架构:纯java开发,后台业务层spring mvc + Hibernate,前台框架fineui,底层架构引擎不明,只知道有大数据引擎。

2、使用人群:

(1)开发/数据人员准备好数据,数据人员/业务人员分析。

(2)业务人员完全可自行分析、制作可视化。整个数据分析流程分工明确。

3、安装部署:

(1)直接官网下载电脑适配的版本安装激活即可

4、数据源:支持各种数据源,支持Apache Kylin、Derby、HP Vertica、IBM DB2、Informix、Sql Server、MySQL、Oracle、Pivotal Greenplum Database、Postgresql、ADS、Amazon Redshift、Apache Impala、Apache Phoenix、Gbase 8A、Gbase8S、Gbase 8T、Hadoop Hive、Kingbase、Presto、SAP HANA、SAP Sybase、Spark、Transwarp Inceptor、Hbase等主流的一些关系型数据库及非关系数据库MongoDB等

5、创建步骤:连接数据源-->建立数据业务包-->建立分析数据表-->图表分析-->看板

6、可视化:

(1)支持的图表类型多,达47种

(2)图表可视化选项少,例如,数据格式选项偏少,如需添加,需要修改配置文件

(3)可在看板中添加筛选框,支持在不同条件下查看

(4)不支持图表和看板分组管理

(5)没有提供图表的下钻功能,不支持多图表间的复杂联动

(6)不支持跨库的表关联查询

7、支持文档:

(1)安装部署和快速入门方面的文档详细,还有教学视频

(2)但具体功能和图表制作方面的介绍文档几乎没有,需要自己摸索尝试

8、邮件通知:支持

9、权限管理:

(1)有一套完整的数据、业务包、报表、人员部门权限管理,有流程节点。

(2)可实现数据源、数据表、字段、图表、看板等权限控制

10、二次开发:

(1)不支持java层面的开发

(2)只有web接口

(3) integration with .NET, JBPM workflow integration, CAS single sign-on

11, Source: No public, people commercial products, the entire team in the operation.

12, individual users for free, there are two concurrent deployment of commercial restrictions, more money is necessary, but this is not expensive compared to the sap.

BI reporting and analysis of data visualization, recommended three open source tools!

 

BI reporting and analysis of data visualization, recommended three open source tools!

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Origin www.cnblogs.com/cuiyubo/p/11448815.html