Database Decisions: Choosing Between PostgreSQL, MongoDB, and MySQL

数据库决策：如何在 PostgreSQL、MongoDB 和 MySQL 之间进行选择

Database choices are easy to oversimplify. You will hear rules like “use PostgreSQL for serious apps,” “use MongoDB when the schema changes,” or “use MySQL because everyone knows it.” Each statement contains a little truth, but none of them is enough to make a real project decision. 数据库的选择很容易被过度简化。你可能会听到诸如“严肃的应用程序要用 PostgreSQL”、“模式（schema）经常变动时用 MongoDB”或“因为大家都熟悉 MySQL 所以用它”之类的准则。每种说法都有一定的道理，但都不足以作为实际项目决策的依据。

A database is not just where data lives. It shapes how your application handles business rules, reporting, scale, developer workflow, debugging, and future product changes. Once a product has customers, migrations and data cleanup become expensive. Choosing thoughtfully at the start matters. 数据库不仅仅是存储数据的地方。它决定了你的应用程序如何处理业务规则、报表、扩展性、开发工作流、调试以及未来的产品变更。一旦产品拥有了用户，数据迁移和清理的成本就会变得非常高昂。因此，在起步阶段进行深思熟虑的选择至关重要。

At Paradane, we work across custom software, e-commerce, SaaS platforms, internal tools, API integrations, and automation systems. Here is the practical framework we use when deciding between PostgreSQL, MongoDB, and MySQL. 在 Paradane，我们的业务涵盖定制软件、电子商务、SaaS 平台、内部工具、API 集成和自动化系统。以下是我们决定在 PostgreSQL、MongoDB 和 MySQL 之间进行选择时所采用的实用框架。

Start with the shape of the business problem

从业务问题的形态出发

Before comparing databases, define the product’s data shape: Are relationships central to the product? Will reporting and analytics matter? Does the data need strong consistency? Are records document-like and frequently changing? Will non-developers need to inspect or export data? What existing systems must integrate with it? The best database is usually the one that makes the core business rules easiest to express and safest to maintain. 在比较数据库之前，先定义产品的“数据形态”：关系在产品中是否处于核心地位？报表和分析是否重要？数据是否需要强一致性？记录是否像文档一样且频繁变动？非开发人员是否需要查看或导出数据？需要与哪些现有系统集成？最好的数据库通常是那个能让核心业务规则最易于表达且最易于维护的数据库。

PostgreSQL: default choice for relational products

PostgreSQL：关系型产品的首选

PostgreSQL is our default for many applications because it combines relational integrity with enough flexibility for modern product work. It is a strong fit when your app has: users, teams, roles, and permissions; orders, invoices, payments, and subscriptions; inventory, catalogs, and fulfillment workflows; audit logs and compliance requirements; dashboards and reporting queries; complex filtering and search needs. PostgreSQL 是我们许多应用程序的首选，因为它将关系完整性与现代产品开发所需的灵活性结合在了一起。当你的应用包含以下内容时，它非常适用：用户、团队、角色和权限；订单、发票、支付和订阅；库存、目录和履行工作流；审计日志和合规性要求；仪表板和报表查询；复杂的过滤和搜索需求。

The biggest advantage is trust. Constraints, transactions, indexes, and mature SQL behavior help prevent invalid states. For example, if every invoice must belong to a customer, and every invoice number must be unique per account, PostgreSQL can enforce that: 它最大的优势是可靠性。约束、事务、索引和成熟的 SQL 行为有助于防止无效状态。例如，如果每张发票必须归属于一个客户，且每个账户下的发票编号必须唯一，PostgreSQL 可以强制执行：

CREATE TABLE invoices (
  id uuid PRIMARY KEY,
  account_id uuid NOT NULL REFERENCES accounts(id),
  customer_id uuid NOT NULL REFERENCES customers(id),
  invoice_number text NOT NULL,
  total_cents integer NOT NULL CHECK (total_cents >= 0),
  status text NOT NULL CHECK (status IN ('draft', 'sent', 'paid', 'void')),
  UNIQUE (account_id, invoice_number)
);

Application code should still validate data, but the database becomes a final line of defense. That matters in systems touched by API requests, admin panels, background jobs, imports, and webhooks. 应用程序代码当然仍需验证数据，但数据库成为了最后一道防线。这对于涉及 API 请求、管理后台、后台任务、数据导入和 Webhook 的系统尤为重要。

Where PostgreSQL surprises people

PostgreSQL 令人惊喜之处

PostgreSQL is not only a traditional relational database. It also handles JSON data well, supports full-text search, has extensions for geospatial data, and can support queue-like patterns when used carefully. That flexibility means teams often do not need to introduce extra infrastructure early. A SaaS MVP can often go far with PostgreSQL, a good schema, and a few carefully chosen indexes. Use PostgreSQL when you want one reliable core database and expect the product to grow in complexity. PostgreSQL 不仅仅是一个传统的关系型数据库。它还能很好地处理 JSON 数据，支持全文搜索，拥有地理空间数据扩展，并且在谨慎使用时可以支持类似队列的模式。这种灵活性意味着团队通常不需要过早引入额外的基础设施。一个 SaaS 产品的 MVP（最小可行性产品）通常只需 PostgreSQL、良好的模式设计和几个精心挑选的索引就能走得很远。当你需要一个可靠的核心数据库，并预期产品复杂度会不断增加时，请选择 PostgreSQL。

MongoDB: useful for document-heavy and variable data

MongoDB：适用于文档密集型和多变数据

MongoDB is strongest when the natural unit of data is a document and the structure varies meaningfully between records. It can be a good fit for: content management systems with flexible blocks; event ingestion where payloads vary by source; product catalogs with highly variable attributes; prototypes where the model is still being discovered; applications that store nested documents more often than relational entities. 当数据的自然单元是文档，且记录之间的结构差异较大时，MongoDB 的优势最为明显。它非常适合：具有灵活区块的内容管理系统；负载随来源而变化的事件摄入；具有高度可变属性的产品目录；模型尚在探索阶段的原型项目；以及存储嵌套文档多于关系实体的应用程序。

A product catalog is a common example. A furniture item, gemstone, software license, and clothing SKU may share some fields but differ heavily in attributes. A document model can make that easier to represent. 产品目录就是一个常见的例子。家具、宝石、软件许可证和服装 SKU 可能共享一些字段，但在属性上却大相径庭。文档模型可以使这种表示变得更容易。

{
  "name": "Ceylon Blue Sapphire",
  "category": "gemstone",
  "attributes": {
    "carat": 2.1,
    "origin": "Sri Lanka",
    "cut": "oval",
    "certification": "GIA"
  }
}

Trying to force every possible attribute into relational columns too early can create a messy schema. MongoDB can reduce friction when the product genuinely needs flexible documents. 过早地尝试将所有可能的属性强行塞入关系型列中，会导致模式变得混乱。当产品确实需要灵活的文档结构时，MongoDB 可以减少这种摩擦。

MongoDB tradeoffs

MongoDB 的权衡

The tradeoff is that flexibility moves responsibility into application code and team discipline. If every document can look different, your code must handle that reality. Reporting can also become harder when the business asks questions across many fields and relationships. MongoDB is not a shortcut around data modeling. It still needs indexes, validation rules, migration strategy, and conventions. Without those, the database can become a drawer full of inconsistent JSON. Use MongoDB when document flexibility is a real product requirement, not because schema design feels inconvenient. 其代价是，灵活性将责任转移到了应用程序代码和团队规范上。如果每个文档看起来都可能不同，你的代码就必须处理这种现实。当业务需要在多个字段和关系之间进行查询时，报表生成也会变得更加困难。MongoDB 并不是绕过数据建模的捷径。它仍然需要索引、验证规则、迁移策略和约定。如果没有这些，数据库最终可能变成一个装满不一致 JSON 数据的抽屉。只有当文档的灵活性是真正的产品需求时才使用 MongoDB，而不是因为觉得模式设计麻烦。

MySQL: mature, common, and still a strong option

MySQL：成熟、通用且依然强大的选择

MySQL remains a good choice for many web applications. It is widely supported, familiar to many developers, and deeply embedded in hosting platforms, CMS ecosystems, and e-commerce tooling. It is often a practical fit when: the client already runs MySQL; the app integrates closely with WordPress, WooCommerce, Magento, or legacy PHP systems; the team has strong MySQL operational experience; hosting constraints favor MySQL; the data model is relational but not unusually complex. 对于许多 Web 应用程序来说，MySQL 仍然是一个不错的选择。它得到广泛支持，为许多开发人员所熟悉，并深度嵌入在托管平台、CMS 生态系统和电子商务工具中。在以下情况下，它通常是一个实用的选择：客户已经在运行 MySQL；应用程序与 WordPress、WooCommerce、Magento 或遗留的 PHP 系统紧密集成；团队拥有丰富的 MySQL 运维经验；托管环境限制倾向于 MySQL；数据模型是关系型的但并不特别复杂。

For many business websites and operational systems, MySQL is perfectly capable. The question is not whether it can work. The question is whether it gives your project the best long-term ergonomics. 对于许多商业网站和运营系统而言，MySQL 完全能够胜任。问题不在于它是否能用，而在于它是否能为你的项目提供最佳的长期开发体验。

MySQL tradeoffs

MySQL 的权衡

Compared with PostgreSQL, MySQL can feel less expressive for certain advanced constraints, JSON workflows, and analytical queries. That does not make it bad. It means teams should be honest about project needs. If a client has a WooCommerce store and needs custom reporting, integrations, or backend automation, MySQL may already be part of the environment. In that case, building around the existing database may be more valuable than introducing a new one. Use MySQL when… 与 PostgreSQL 相比，MySQL 在某些高级约束、JSON 工作流和分析查询方面可能显得表达能力不足。但这并不意味着它不好，而是意味着团队应该诚实地评估项目需求。如果客户拥有一个 WooCommerce 商店，并且需要自定义报表、集成或后端自动化，那么 MySQL 可能已经是环境的一部分了。在这种情况下，围绕现有数据库进行构建可能比引入一个新的数据库更有价值。请在以下情况使用 MySQL……