blocks|key|2095032|text|MongoDB和CouchDB提供了解决方案，但没有内置功能。在representing+hierarchy+in+a+relational+database上可以看到这个问题，因为我见过的大多数其他NoSQL解决方案在这方面都是相似的；在这些解决方案中，您必须编写自己的算法，以便在添加、删除和移动节点时重新计算信息。一般来说，你是在快速读取时间(例如nested+set)还是快速写入时间(adjacency+list)之间做出选择。请参阅前面提到的SO问题，了解这些问题的更多选项-+flat+table+approach与您的问题最接近。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2095033|Apache+JackRabbit和JBoss+eXo都是Java+Content+Repository+(JCR)，它确实抽象了这些注意事项。请注意，在幕后，两者仍在进行某种算法计算，以维护如上所述的层次结构。此外，JCR还处理权限、文件存储和其他几个方面-因此它对您的项目来说可能有些过分了。|2095034|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/4048151/what-are-the-options-for-storing-hierarchical-data-in-a-relational-database|1|http://en.wikipedia.org/wiki/Nested_set_model|2|http://en.wikipedia.org/wiki/Adjacency_list|3|http://evolt.org/node/4047|4|http://jackrabbit.apache.org/|5|http://www.jboss.org/exojcr.html|6|http://en.wikipedia.org/wiki/Content_repository_API_for_Java^0|W|1B|0|4X|A|1|5H|E|2|6T|J|3|0|0|H|4|I|9|5|T|N|6|0^^$0|@$1|2|3|4|5|6|7|Z|8|@]|9|@$A|10|B|11|1|12]|$A|13|B|14|1|15]|$A|16|B|17|1|18]|$A|19|B|1A|1|1B]]|C|$]]|$1|D|3|E|5|6|7|1C|8|@]|9|@$A|1D|B|1E|1|1F]|$A|1G|B|1H|1|1I]|$A|1J|B|1K|1|1L]]|C|$]]|$1|F|3|-4|5|6|7|1M|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]|P|$5|I|J|K|C|$L|Q]]|R|$5|I|J|K|C|$L|S]]|T|$5|I|J|K|C|$L|U]]|V|$5|I|J|K|C|$L|W]]|X|$5|I|J|K|C|$L|Y]]]]

MongoDB and CouchDB offer solutions, but not built in functionality. See this SO question on <a href="https://stackoverflow.com/questions/4048151/what-are-the-options-for-storing-hierarchical-data-in-a-relational-database">representing hierarchy in a relational database</a> as most other NoSQL solutions I've seen are similar in this regard; where you have to write your own algorithms for recalculating that information as nodes are added, deleted and moved. Generally speaking you're making a decision between fast read times (e.g. <a href="http://en.wikipedia.org/wiki/Nested_set_model" rel="noreferrer">nested set</a>) or fast write times (<a href="http://en.wikipedia.org/wiki/Adjacency_list" rel="noreferrer">adjacency list</a>). See aforementioned SO question for more options along these lines - the <a href="http://evolt.org/node/4047" rel="noreferrer">flat table approach</a> appears most aligned with your question. 

One standard that does abstract away these considerations is the <a href="http://en.wikipedia.org/wiki/Content_repository_API_for_Java" rel="noreferrer">Java Content Repository</a> (JCR), both <a href="http://jackrabbit.apache.org/" rel="noreferrer">Apache JackRabbit</a> and <a href="http://www.jboss.org/exojcr.html" rel="noreferrer">JBoss eXo</a> are implementations. Note, behind the scenes both are still doing some sort of algorithmic calculations to maintain hierarchy as described above. In addition, the JCR also handles permissions, file storage, and several other aspects - so it may be overkill for your project.

blocks|key|4205726|text|您可能需要一个像MongoDB或CouchDB这样的面向文档的数据库。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4205727|查看允许您在MongoDB中存储分层数据的不同技术的示例：http://www.mongodb.org/display/DOCS/Trees%2Bin%2BMongoDB|4205728|entityMap|0|LINK|mutability|MUTABLE|url|http://www.mongodb.org/|1|http://couchdb.apache.org/|2|http://www.mongodb.org/display/DOCS/Trees%2Bin%2BMongoDB^0|8|7|0|G|7|1|0|T|1G|2|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@$A|S|B|T|1|U]|$A|V|B|W|1|X]]|C|$]]|$1|D|3|E|5|6|7|Y|8|@]|9|@$A|Z|B|10|1|11]]|C|$]]|$1|F|3|-4|5|6|7|12|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]|P|$5|I|J|K|C|$L|Q]]]]

What you possibly need is a document-oriented database like <a href="http://www.mongodb.org/">MongoDB</a> or <a href="http://couchdb.apache.org/">CouchDB</a>.

See examples of different techniques which allow you to store hierarchical data in MongoDB:
<a href="http://www.mongodb.org/display/DOCS/Trees+in+MongoDB">http://www.mongodb.org/display/DOCS/Trees+in+MongoDB</a>

blocks|key|4205797|text|最常见的是IBM's+IMS.There也是Cache+Database|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4205798|请参阅this+question+posted+on+dba+section+of+stackexchange.|4205799|entityMap|0|LINK|mutability|MUTABLE|url|http://www-01.ibm.com/software/data/ims/|1|http://www.intersystems.com/cache/index.html|2|https://dba.stackexchange.com/questions/1437/are-there-opensource-hierarchical-database-management-systems^0|5|9|0|M|E|1|0|3|1H|2|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@$A|S|B|T|1|U]|$A|V|B|W|1|X]]|C|$]]|$1|D|3|E|5|6|7|Y|8|@]|9|@$A|Z|B|10|1|11]]|C|$]]|$1|F|3|-4|5|6|7|12|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]|P|$5|I|J|K|C|$L|Q]]]]

The most common one is <a href="http://www-01.ibm.com/software/data/ims/" rel="nofollow noreferrer">IBM's IMS</a>.There is also <a href="http://www.intersystems.com/cache/index.html" rel="nofollow noreferrer">Cache Database</a>

See <a href="https://dba.stackexchange.com/questions/1437/are-there-opensource-hierarchical-database-management-systems">this question posted on dba section of stackexchange.</a>

blocks|key|4205905|text|面对同样的问题，我决定使用Lua+%2B+Redis+https://github.com/qbolec/Redis-Tree/创建我自己的(非常简单的)解决方案|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4205906|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/qbolec/Redis-Tree/^0|P|11|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Faced with the same issue, I decided to create my own (very simple) solution using Lua + Redis <a href="https://github.com/qbolec/Redis-Tree/" rel="nofollow">https://github.com/qbolec/Redis-Tree/</a>

blocks|key|4205844|text|Exist-db实现了支持xml持久化的层次化数据模型|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4205845|entityMap|0|LINK|mutability|MUTABLE|url|http://exist-db.org/^0|0|8|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

<a href="http://exist-db.org/" rel="nofollow">Exist-db</a> implemented hierarchical data model for xml persistence

blocks|key|1667880|text|图形数据库也可能解决这个问题。如果neo4j在可伸缩性方面不能满足您的需求，可以考虑Titan，它基于包括HBase在内的各种存储后端，应该可以很好地扩展。它不像neo4j那样成熟，但它是一个非常有前途的项目。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1667881|entityMap|0|LINK|mutability|MUTABLE|url|http://thinkaurelius.github.io/titan/^0|16|5|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Graph databases would probably also solve this problem. If neo4j is not enough for you in terms of scaling, consider <a href="http://thinkaurelius.github.io/titan/" rel="nofollow">Titan</a>, which is based on various storage back-ends including HBase and should scale very well. It is not as mature as neo4j, but it is a very promising project.

blocks|key|5623942|text|显然，是LDAP。OpenLDAP会把它做得很短。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5623943|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

LDAP, obviously. OpenLDAP would make short work of it.

blocks|key|5623962|text|In+mathematics,+and,+more+specifically,+in+graph+theory,+a+tree+is+an+undirected+graph+in+which+any+two+vertices+are+connected+by+exactly+one+path。因此，任何graph+db都肯定能完成这项工作。顺便说一句，像树这样的普通图可以简单地映射到任何关系或非关系数据库。要将分层数据存储到关系数据库中，请看一下Bill+Karwin的这个很棒的演示。还有一些ORM具有存储树的功能。例如，TypeORM支持用于存储分层结构的邻接表和闭合表模式。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|5623963|5623964|+TypeORM用于TypeScript\Javascript开发。Check+popular+ORMs根据您的环境找到一个支持树的树。|blockquote|5623965|5623966|5623967|非关系型数据库的王者是Mongodb。看看这是documentation。来找出它是如何储存树木的。树是最常见的图形类型，它们在任何地方都被使用。任何成熟的DB解决方案都应该有一种处理树的方法。|5623968|entityMap|0|LINK|mutability|MUTABLE|url|https://en.wikipedia.org/wiki/Tree_(graph_theory))|1|https://en.wikipedia.org/wiki/Graph_database#List_of_graph_databases|2|https://www.slideshare.net/billkarwin/models-for-hierarchical-data|3|https://typeorm.io/#/tree-entities|4|https://en.wikipedia.org/wiki/Object-relational_mapping|5|https://docs.mongodb.com/manual/applications/data-models-tree-structures/'^0|0|42|0|48|8|1|69|B|2|7C|7|3|0|0|Y|I|4|0|0|0|N|D|5|0^^$0|@$1|2|3|4|5|6|7|13|8|@]|9|@$A|14|B|15|1|16]|$A|17|B|18|1|19]|$A|1A|B|1B|1|1C]|$A|1D|B|1E|1|1F]]|C|$]]|$1|D|3|-4|5|6|7|1G|8|@]|9|@]|C|$]]|$1|E|3|F|5|G|7|1H|8|@]|9|@$A|1I|B|1J|1|1K]]|C|$]]|$1|H|3|-4|5|6|7|1L|8|@]|9|@]|C|$]]|$1|I|3|-4|5|6|7|1M|8|@]|9|@]|C|$]]|$1|J|3|K|5|6|7|1N|8|@]|9|@$A|1O|B|1P|1|1Q]]|C|$]]|$1|L|3|-4|5|6|7|1R|8|@]|9|@]|C|$]]]|M|$N|$5|O|P|Q|C|$R|S]]|T|$5|O|P|Q|C|$R|U]]|V|$5|O|P|Q|C|$R|W]]|X|$5|O|P|Q|C|$R|Y]]|Z|$5|O|P|Q|C|$R|10]]|11|$5|O|P|Q|C|$R|12]]]]

<a href="https://en.wikipedia.org/wiki/Tree_(graph_theory)" rel="nofollow noreferrer">In mathematics, and, more specifically, in graph theory, a tree is an undirected graph in which any two vertices are connected by exactly one path</a>. So any <a href="https://en.wikipedia.org/wiki/Graph_database#List_of_graph_databases" rel="nofollow noreferrer">graph db</a> will do the job for sure. BTW an ordinary graph like a tree can be simply mapped to any relational or non-relational DB. To store hierarchical data into a relational db take a look at this awesome presentation by <a href="https://www.slideshare.net/billkarwin/models-for-hierarchical-data" rel="nofollow noreferrer">Bill Karwin</a>. There are also ORMs with facilities to store trees. For example <a href="https://typeorm.io/#/tree-entities" rel="nofollow noreferrer">TypeORM</a> supports the Adjacency list and Closure table patterns for storing hierarchical structures.

<blockquote>
 TypeORM is used in TypeScript\Javascript development. <a href="https://en.wikipedia.org/wiki/Object-relational_mapping" rel="nofollow noreferrer">Check popular ORMs</a> to find a one supporting trees based on your environment.
</blockquote>

The king of Non-relational DBs [IMHO] is Mongodb. Check out it's <a href="https://docs.mongodb.com/manual/applications/data-models-tree-structures/&#39;" rel="nofollow noreferrer">documentation</a>. to find out how it stores trees. Trees are the most common kind of graphs and they are used everywhere. Any well-established DB solution should have a way to deal with trees.

blocks|key|5623613|text|这是一个不能回答你的问题。SQLServer+2008！它对于递归查询来说是很棒的。或者，您可以采用老式的方法，将层次结构数据存储在单独的表中，以避免递归。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5623614|我认为关系数据库非常适合于树数据。在查询性能和易用性方面都是如此。有一个警告..。您将插入到一个索引表中，并且可能在每次有人发布帖子时插入到其他几个索引表中。在facebook+caliber论坛上，插入性能可能是一个问题。|5623615|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

Here's a non-answer for you. SQLServer 2008!!!! It's great for recursive queries. Or you can go the old fashioned route and store hierarchy data in a separate table to avoid recursion.

I think relational databases lend themselves very well to tree data. Both in query performance and ease of use. With one caveat.... you will be inserting into an indexed table, and probably several other indexed tables every time someone makes a post. Insert performance could be an issue on a facebook caliber forum.

blocks|key|1667829|text|查看MarkLogic。您可以从网站下载演示副本。它是一个用于非结构化数据的数据库，属于数据库的NoSQL分类。我知道非结构化数据是一个负载很大的术语，但请将其视为不适合RDBMS的行和列的数据(如分层数据)。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1667830|entityMap|0|LINK|mutability|MUTABLE|url|http://www.marklogic.com/^0|2|9|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Check out <a href="http://www.marklogic.com" rel="nofollow">MarkLogic</a>. You can download a demo copy from the website. It is a database for unstructured data and falls under the NoSQL classification of databases. I know unstructured data is a pretty loaded term but just think of it as data that does not fit well in the rows and columns of a RDBMS (like hierarchical data).

blocks|key|5623923|text|刚刚花了一个周末的时间在一个培训课程上，使用MUMUPS+db作为全栈javascript浏览器应用程序开发框架的后端。很棒的东西！我推荐GPL下的流行性胃炎的GT.M发行版。或者试试http://sourceforge.net/projects/mumps/?source=recommended来治疗香草型流行性胃炎。查看ewd.js+js框架的http://robtweed.wordpress.com/和有关MUMPS的更多信息。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|5623924|entityMap|0|LINK|mutability|MUTABLE|url|http://sourceforge.net/projects/mumps/?source=recommended|1|http://robtweed.wordpress.com/^0|2K|1L|0|4V|U|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

Just spent the weekend at a training course using MUMUPS db as a back-end for a full stack javascript browser application development framework. Great stuff! I'd recommend GT.M distro of MUMPS under GPL. Or try <a href="http://sourceforge.net/projects/mumps/?source=recommended" rel="nofollow">http://sourceforge.net/projects/mumps/?source=recommended</a> for vanilla MUMPS. Check out <a href="http://robtweed.wordpress.com/" rel="nofollow">http://robtweed.wordpress.com/</a> for ewd.js js framework and more info on MUMPS.

blocks|key|4206075|text|Amazon+Web+service的简单存储服务(Amazon+Web+Service's+Simple+storage+Service，简称S3)是一种对分层数据提供原生支持的NoSql存储服务。基于路径的键本质上是分层的，并且BLOB值可以使用属性(mime类型，例如application/json、text/csv等)来类型化。S3的优势包括能够扩展到极大的总体容量、版本控制以及几乎无限的并发写入。缺点包括不支持条件写(乐观并发)或一致读(仅用于读后写)，并且不支持引用/关系。它还纯粹是基于使用的，因此需求的广泛变化不需要复杂的扩展基础设施或过度配置的容量。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4206076|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

A NoSql storage service with native support for hierarchical data is Amazon Web Service's Simple Storage Service (AWS S3). The path based keys are hierarchical by nature, and the blob values may be typed using attributes (mime type, e.g. application/json, text/csv, etc.). Advantages of S3 include the ability to scale to both extremely large overall capacity, versioning, as well as nearly infinite concurrent writes. Disadvantages include no support for conditional writes (optimistic concurrency), or consistent reads (only for read-after write) and no support for references/relationships. It is also purely usage based so wide variations in demand do not require complex scaling infrastructure or over-provisioned capacity.

blocks|key|1665209|text|Clicknouse+db显式支持hierarchical+data|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1665210|entityMap|0|LINK|mutability|MUTABLE|url|https://clickhouse.com/docs/en/sql-reference/dictionaries/external-dictionaries/external-dicts-dict-hierarchical/^0|H|H|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Clicknouse db has explicit support for <a href="https://clickhouse.com/docs/en/sql-reference/dictionaries/external-dictionaries/external-dicts-dict-hierarchical/" rel="nofollow noreferrer">hierarchical data</a>

What type of NoSQL database is best suited to store hierarchical data?

Say for example I want to store posts of a forum with a tree structure:

<pre><code>original post
 + re: original post
 + re: original post
 + re2: original post
 + re3: original post
 + re2: original post
</code></pre>

What type of NoSQL database is best suited to store hierarchical data?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

文章

问答

视频

教程

学习中心

腾讯云实验室

直播

竞赛

腾讯云代码分析专区

腾讯iOA零信任安全管理系统专区

腾讯云架构师技术同盟交流圈

腾讯云数据库专区

腾讯云智能顾问专区

腾讯云原生专区

腾讯混元专区

腾讯云TCE专区

腾讯云Lighthouse专区

腾讯云HAI专区

腾讯云Edgeone专区

腾讯云存储专区

腾讯云智能专区

腾讯轻联专区 

腾讯云开发专区

TAPD专区

腾讯轻量云游戏服专区

EdgeOne AI 安全实战专区

腾讯云最具价值专家

腾讯云架构师技术同盟

腾讯云创作之星

腾讯云开发者先锋

腾讯云AI代码助手

云原生构建

TAPD 敏捷项目管理

Cloud Studio

SDK中心

API中心

命令行工具

功能1上新10个字符

功能2描述100个字符功能2描述100个字符功能2描述100个字符功能2描述100个字符功能2描述100个字符功能2描述100个字符功能2描述100个字符功能2描述100个字符功能2描述100个字符。

功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符功能2上新100个字符。

功能5描述100个字符功能5描述100个字符功能5描述100个字符功能5描述100个字符功能5描述100个字符功能5描述100个字符

功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符功能5上新100个字符

功能4上新

文章&问答评论现已支持表情

全新交互，全新视觉，新增快捷键、悬浮工具栏、高亮块等功能并同时优化现有功能，全面提升创作效率和体验

社区富文本编辑器全新改版！诚邀体验～ 

精选全网热门MCP server，让你的AI更好用 🚀

💥开发者 MCP广场重磅上线！

涵盖代码开发、场景应用、自动测试全流程，助你从零构建专属AI助手

一站式MCP教程库，解锁AI应用新玩法

聚焦“写作效率、视觉美观与运行性能”三方面进行全面升级，为您提供更高效、稳定的创作环境

社区富文本&Markdown编辑器全新改版上线，欢迎大家体验!

诚挚邀请您参与本次调研，分享您的真实使用感受与建议。您的反馈至关重要，感谢您的支持与参与！

社区新版编辑器体验调研

哪种类型的NoSQL数据库最适合存储分层数据？举个例子，我想用树形结构存储一个论坛的帖子：original post + re: original post + re: original post   + re2: original post     + re3: original post   + re2: original post

问哪种类型的NoSQL数据库最适合存储分层数据？
EN

回答 13

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问哪种类型的NoSQL数据库最适合存储分层数据？EN

回答 13

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问哪种类型的NoSQL数据库最适合存储分层数据？
EN