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## Background When storing a segment of serialized data of uncertain length in a database, many people design the field as `VARCHAR(2000)` in the table schema. But if the length is uncertain, why not use the `TEXT` type instead? Some say: **TEXT affects query performance.** Is that really the reason? This article will explore that: ## What is TEXT `TEXT` is a variable-length data type in MySQL, including `TINYTEXT`, `TEXT`, `MEDIUMTEXT`, and `LONGTEXT`. They are typically used to store large amounts of textual data, with the following storage limits: * `TINYTEXT`: 0 - 255 bytes * `TEXT`: 0 - 65,535 bytes * `MEDIUMTEXT`: 0 - 16,777,215 bytes * `LONGTEXT`: 0 - 4,294,967,295 bytes ## How TEXT is Stored Each `BLOB` or `TEXT` value is represented internally by a separately allocated object, whereas other data types have storage space allocated once per column when the table is opened. When storing string-type data, InnoDB encodes fixed-length fields of 768 bytes or more as variable-length fields and stores them in **overflow pages**. Data smaller than 768 bytes is stored directly in the data row. Therefore, when using other string types, avoid storing data that is 768 bytes or larger. ## Limitations of TEXT * `TEXT` cannot have a default value. * When indexing a `TEXT` field, a **prefix length** must be specified. * When comparing index entries, trailing spaces are padded. If a unique index is required, this can lead to duplicate key errors. * `TEXT` fields may be particularly long. When sorting, only the first `max_sort_length` bytes (default is 1024) are used. This value can be adjusted by modifying the variable: -- View max_sort_length SELECT @@max_sort_length; -- Set max_sort_length SET max_sort_length = 2048; * When processed with temporary tables, the server will use tables on disk rather than in memory, because the `MEMORY` storage engine does not support `TEXT` type. * The size of a `TEXT` object is determined by its type, but the actual transferable maximum size is limited by the available content and communication buffer size. This can be adjusted by changing the `max_allowed_packet` variable: -- View max_allowed_packet SELECT @@max_allowed_packet; -- Set max_allowed_packet SET max_allowed_packet = 67108864; ## Conclusion `TEXT` can be used to store large amounts of textual data. However, for several reasons, it is **not recommended** to use `TEXT`: ### Performance Issues * `TEXT` is represented internally as a separately allocated object, requiring **additional operations and resource consumption** during storage and retrieval. * If a `TEXT` field is especially large, **reading it can increase memory pressure** , impacting overall system performance. * The `MEMORY` storage engine does **not support`TEXT`**, so when temporary tables are used, data from `TEXT` fields will be read from disk rather than directly from memory. ### Indexing Limitations Indexes can improve query performance, but indexing `TEXT` fields comes with certain **restrictions and complexity** : * When used as a **unique index** , it may result in duplicate key errors. * Creating **full-text indexes** requires additional computation and space to maintain. If the `TEXT` field is too large, it may negatively impact performance. Therefore, it's advisable to **avoid using the`TEXT` type** in table schema design. If it must be used, consider the following approaches: * **Separate`TEXT` fields into independent tables**, linking to the main table via primary key. * Avoid reading `TEXT` fields unless necessary — for example, **do not use`SELECT *`**. * For large fields, **consider storing them in OSS** (Object Storage Service). ### We are Leapcell, your top choice for hosting backend projects. Leapcell is the Next-Gen Serverless Platform for Web Hosting, Async Tasks, and Redis: **Multi-Language Support** * Develop with Node.js, Python, Go, or Rust. **Deploy unlimited projects for free** * pay only for usage — no requests, no charges. **Unbeatable Cost Efficiency** * Pay-as-you-go with no idle charges. * Example: $25 supports 6.94M requests at a 60ms average response time. **Streamlined Developer Experience** * Intuitive UI for effortless setup. * Fully automated CI/CD pipelines and GitOps integration. * Real-time metrics and logging for actionable insights. **Effortless Scalability and High Performance** * Auto-scaling to handle high concurrency with ease. * Zero operational overhead — just focus on building. Explore more in the Documentation! Follow us on X: @LeapcellHQ Read on our blog