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Reduce marketing msg in intro page and fix link to handbook. (#424)
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docs/index.md

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# Welcome to CrateDB
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CrateDB is a **distributed SQL database** designed for **real-time analytics
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and search** at scale. Whether you are working with time series data, full-text
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CrateDB is a **distributed SQL database** designed for **real-time analytics,
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search and AI** at scale. Whether you are working with time series data, full-text
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search, or large volumes of structured and semi-structured data, CrateDB gives
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you the **power of SQL**, the **scalability of NoSQL**, and the **flexibility
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of a modern data platform**.
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:::::{grid}
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See our [Product overview] to learn more about high-level features and use cases.
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:class: rubric-slimmer
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:columns: 6
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:::{rubric} Why CrateDB?
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:::
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CrateDB was built for speed, scale, and simplicity:
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* **Real-time performance:** Query millions of records per second with sub-second response times.
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* **AI/ML-ready:** Store and serve data for modern AI pipelines.
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* **Search + SQL**: Combine full-text search with rich SQL queries.
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* **Geospatial & time series**: Native support for IoT, sensor data, and location-based use cases.
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* **Horizontal scalability**: Add nodes effortlessly to handle more data and users.
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* **Resilient and fault-tolerant**: Built-in replication and recovery.
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::::
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:class: rubric-slimmer
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:::{rubric} What Can You Build?
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:::
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CrateDB is used across industries to power:
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* Real-time **dashboards and analytics**
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* Hybrid **search and retrieval experiences**
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* Large-scale **IoT telemetry and analytics**
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* Complex **geospatial applications**
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* **AI-powered features** embedded in your apps
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* **Industrial IoT** data backends
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::::
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:::::
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:::{rubric} Benefits and Features
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:::
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Whether you are a developer,
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database administrator, or just starting your journey with CrateDB, our
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documentation provides the information and knowledge needed to build
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real-time analytics and hybrid search applications that leverage CrateDB's
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unique features.
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* In a unified data platform, CrateDB lets you analyze relational, JSON,
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time series, geospatial, full-text, and vector data in a single system,
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eliminating the need for multiple databases.
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* The fully distributed SQL query engine, built on top of Apache Lucene,
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and inheriting technologies from Elasticsearch/OpenSearch, provides performant
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aggregations and advanced SQL features like JOINs and CTEs on large datasets
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of semi-structured data.
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* Real-time indexing automatically indexes all columns, including nested
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structures, as data is ingested, eliminating the need to worry about
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indexing strategy.
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* The flexible data schema dynamically adapts based on the data you ingest,
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offering seamless integration and instant readiness for analysis.
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* Columnar storage enables fast query and aggregation performance.
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* PostgreSQL wire protocol compatibility and an HTTP interface provide versatile
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integration capabilities.
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* AI-ready: The vector store subsystem integrates well
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with an extensive third-party ecosystem of AI/ML frameworks for advanced data
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analysis and data-driven decisions.
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This documentation is about helping you get started, explore in practice, and
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operate in details.
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## Get Started
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:::{grid-item-card}
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:link: index
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:link: handbook
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:link-type: ref
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:link-alt: The CrateDB Guide
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:link-alt: The CrateDB Handbook
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:class-header: sd-text-center sd-fs-5 sd-align-minor-center sd-font-weight-bold sd-text-capitalize
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:class-body: sd-text-center sd-fs-5
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:class-footer: text-smaller
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The CrateDB Guide
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The CrateDB Handbook
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^^^
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{material-outlined}`hiking;3.5em`
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Don't miss the relevant [CrateDB customer stories].
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::::
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[Product overview]: https://cratedb.com/database
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[CrateDB customer stories]: https://www.youtube.com/playlist?list=PLDZqzXOGoWUJrAF_lVx9U6BzAGG9xYz_v
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[HTTP protocol]: https://en.wikipedia.org/wiki/HTTP
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[JDBC]: https://en.wikipedia.org/wiki/Java_Database_Connectivity

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