docs: improve FAQ

docs/user-guide/concepts/features-that-you-concern.md

@@ -66,10 +66,14 @@ Please read the performance benchmark reports:
 
 Yes. Please refer to [disaster recovery](/user-guide/deployments-administration/disaster-recovery/overview.md).
 
-## Does GeptimeDB has geospatial index?
+## Does GreptimeDB has geospatial index?
 
 Yes. We offer [built-in functions](/reference/sql/functions/geo.md) for Geohash, H3 and S2 index.
 
 ## Any JSON support?
 
 See [JSON functions](/reference/sql/functions/overview.md#json-functions).
+
+## More Questions?
+
+For more comprehensive answers to frequently asked questions about GreptimeDB, including deployment options, migration guides, performance comparisons, and best practices, please visit our [FAQ page](/faq-and-others/faq.md).

docs/user-guide/concepts/overview.md

@@ -11,6 +11,7 @@ description: Provides an overview of GreptimeDB, including its features, data mo
 - [Storage Location](./storage-location.md): This document describes the storage location of GreptimeDB, including local disk, HDFS, and cloud object storage such as S3, Azure Blob Storage, etc.
 - [Key Concepts](./key-concepts.md): This document describes the key concepts of GreptimeDB, including table, time index, table region and data types.
 - [Features that You Concern](./features-that-you-concern.md): Describes some features that may be concerned about a unified metrics, logs & events database.
+- [Frequently Asked Questions](/faq-and-others/faq.md): Comprehensive FAQ covering common questions about GreptimeDB's capabilities, deployment, and usage.
 
 ## Read More
 

docs/user-guide/concepts/why-greptimedb.md

@@ -25,7 +25,7 @@ GreptimeDB leverages cloud object storage (like AWS S3 and Azure Blob Storage et
 
 ## High Performance
 
-As for performance optimization, GreptimeDB utilizes different techniques such as LSM Tree, data sharding, and kafka-based WAL design, to handle large workloads of observability data ingestion.
+As for performance optimization, GreptimeDB utilizes different techniques such as LSM Tree, data sharding, and flexible WAL options (local disk or distributed services like Kafka), to handle large workloads of observability data ingestion.
 
 GreptimeDB is written in pure Rust for superior performance and reliability. The powerful and fast query engine is powered by vectorized execution and distributed parallel processing (thanks to [Apache DataFusion](https://datafusion.apache.org/)), and combined with [indexing capabilities](/user-guide/manage-data/data-index.md) such as inverted index, skipping index, and full-text index. GreptimeDB combines smart indexing and Massively Parallel Processing (MPP) to boost pruning and filtering.
 
@@ -75,7 +75,6 @@ GreptimeDB supports multiple data ingestion protocols, making integration with e
 For data querying, GreptimeDB provides:
 - **SQL**: For real-time queries, analytics, and database management
 - **PromQL**: Native support for real-time metrics querying and Grafana integration
-- **Python** *(Planned)*: For in-database UDFs and DataFrame operations
 
 GreptimeDB integrates seamlessly with your observability stack while maintaining high performance and flexibility.
 

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/features-that-you-concern.md

@@ -65,12 +65,16 @@ GreptimeDB 在 [ClickHouse 的 JSONBench 测试中 Cold Run 斩获第一](https:
 
 有的，请参阅[灾难恢复文档](/user-guide/deployments-administration/disaster-recovery/overview.md)。
 
-## GeptimeDB 有地理空间索引吗？
+## GreptimeDB 有地理空间索引吗？
 
 我们提供 [内置函数](/reference/sql/functions/geo.md) 支持 Geohash, H3 and S2 索
 引。
 
 
-## GeptimeDB 支持 JSON 数据吗？
+## GreptimeDB 支持 JSON 数据吗？
 
 我们提供 [内置函数](/reference/sql/functions/overview.md#json-functions) 支持访问 JSON 数据类型。
+
+## 更多问题？
+
+有关 GreptimeDB 的更多常见问题解答，包括部署选项、迁移指南、性能对比和最佳实践等，请访问我们的[常见问题页面](/faq-and-others/faq.md)。

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/overview.md

@@ -11,6 +11,7 @@ description: 概述 GreptimeDB 的特点和优势，并提供相关文档链接
 - [存储位置](./storage-location.md)：介绍了 GreptimeDB 的存储位置，包括本地磁盘、HDFS、AWS S3 和阿里云 OSS 等云对象存储。
 - [核心概念](./key-concepts.md)：介绍了 GreptimeDB 的核心概念，包括表、时间索引约束、表 Region 和数据类型等。
 - [关键特性](./features-that-you-concern.md): 介绍了 TSDB 用户较为关心的指标（metrics）、日志（logs）和事件（events）数据库的特性。
+- [常见问题](/faq-and-others/faq.md): 全面的 FAQ，涵盖关于 GreptimeDB 能力、部署和使用的常见问题。
 
 ## 阅读更多
 

i18n/zh/docusaurus-plugin-content-docs/current/user-guide/concepts/why-greptimedb.md

@@ -25,7 +25,7 @@ GreptimeDB 采用云对象存储（如 AWS S3、阿里云 OSS 和 Azure Blob Sto
 
 ## 高性能
 
-在性能优化方面，GreptimeDB 运用了多种技术，如 LSM Tree、数据分片和基于 Kafka 的 WAL 设计，以处理大规模可观测数据的写入。
+在性能优化方面，GreptimeDB 运用了多种技术，如 LSM Tree、数据分片和灵活的 WAL 选项（本地磁盘或 Kafka 等分布式服务），以处理大规模可观测数据的写入。
 
 GreptimeDB 使用纯 Rust 编写，具有卓越的性能和可靠性。强大而快速的查询引擎由向量化执行和分布式并行处理（感谢 [Apache DataFusion](https://datafusion.apache.org/)）驱动，并结合了丰富的[索引选项](/user-guide/manage-data/data-index.md)，例如倒排索引、调数索引和全文索引等。GreptimeDB将智能索引和大规模并行处理 (MPP) 结合在一起，以提升查询过程中数据剪枝和过滤的效率。
 
@@ -76,7 +76,6 @@ GreptimeDB 支持多种数据摄入协议，从而实现与现有可观测性技
 在数据查询方面，GreptimeDB 提供：
 - **SQL**：用于实时查询、复杂分析和数据库管理
 - **PromQL**：原生支持实时指标查询和 Grafana 集成
-- **Python**：（计划中）支持数据科学场景的数据库内 UDF 和 DataFrame 操作
 
 GreptimeDB 与您的现有可观测性技术栈无缝集成，同时保持高性能和灵活性。