Introduction
Timeplus是一个简单、强大且经济的流处理平台。
Timeplus 提供强大的端到端功能，帮助数据团队快速、直观地处理流和历史数据，各种规模和行业的组织都可以访问。 它使数据工程师和平台工程师能够使用 SQL 解锁流数据价值。
它有不同的可用方式：
- Timeplus Proton: the core engine open-sourced at GitHub under Apache 2.0 License. 它是一个快速而轻量级的流式SQL引擎。
- Timeplus Enterprise: the production-ready commercial product, with 2 deployment options:
- Cloud: a fully-managed unified platform for streaming and historical data processing.
- Self-hosted: same feature sets as Timeplus Cloud, able to run and scale everywhere, from edge to your data center. Customize according to your configuration needs.
Timeplus allows for easy connection to diverse data sources (such as Apache Kafka, Confluent Cloud, Redpanda, NATS, Web Socket/SSE, CSV file upload, and more), explore streaming patterns via SQL queries, send real-time insights and alerts to other systems or individuals, and create dashboards and visualizations.
Still curious about the benefits of using Timeplus? Check out the showcases to see how Timeplus customers use our unified streaming and historical processing platform.
开始使用 Timeplus
快速入门
Follow along with step-by-step instructions for running Timeplus Enterprise on your laptop and loading sample IoT, user login, or DevOps data.
Get started →
进入流处理和分析领域
采集数据 →
将 Timeplus 连接到 Apache Kafka、Apache Pulsar、Confluent Cloud，或使用 REST API、SDK 等进行推送。
编写 SQL 查询 →
使用转换、联接、聚合、窗口处理、子流等函数创建长时间运行的查询。
可视化数据 →
查看任何查询的实时结果，创建自定义仪表板以讲述数据故事，或与外部 BI 系统集成。
核心概念和功能
Streams →
Append-only streams, mutable streams, external streams to read or write data from other systems.
Materialized Views →
Long-running streaming SQL in background after creation. The results can be written to internal storage or external systems for ETL or alerting.
Functions →
Thousand of built-in SQL functions are available in Timeplus. You can also define own functions (UDF) with JavaScript, Python,or any other languages.