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@@ -3,78 +3,30 @@ title: Databend Community
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Databend Community Edition is the open-source version of Databend, released under the **Apache 2.0 license** for free commercial and non-commercial use. It provides the same core analytics engine as [Databend Enterprise](/guides/products/dee/) and [Databend Cloud](/guides/products/dc/), but without enterprise-specific features.
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Databend is an open-source, elastic, and workload-aware cloud data warehouse built in Rust, offering a cost-effective alternative to Snowflake. It's designed for complex analysis of the world's largest datasets.
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## Core Features
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<TabsgroupId="whydatabend">
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<TabItemvalue="Performance"label="Performance">
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-**High-performance SQL processing** with vectorized execution
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-**Multiple data types**: JSON, ARRAY, MAP, VARIANT
-**Multiple data formats**: CSV, JSON, Parquet, ORC, and more
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-**Self-hosted deployment** on your infrastructure
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-**Object storage support** for major cloud platforms
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- Blazing-fast data analytics on object storage.
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- Leverages data-level parallelism and instruction-level parallelism technologies for [optimal performance](https://benchmark.clickhouse.com/).
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- No indexes to build, no manual tuning, and no need to figure out partitions or shard data.
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## Enterprise Features
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For advanced capabilities, consider upgrading to [Databend Enterprise](/guides/products/dee/) or [Databend Cloud](/guides/products/dc/), which include:
- Supports various object storage platforms. Click [here](../10-deploy/01-deploy/00-understanding-deployment-modes.md#supported-object-storage) to see a full list of supported platforms.
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- Allows instant elasticity, enabling users to scale up or down based on their application needs.
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Databend's high-level architecture is composed of a `meta-service layer`, a `query layer`, and a `storage layer`.
Databend efficiently supports multiple tenants through its meta-service layer, which plays a crucial role in the system:
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-**Metadata Management**: Handles metadata for databases, tables, clusters, transactions, and more.
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-**Security**: Manages user authentication and authorization for a secure environment.
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Discover more about the meta-service layer in the [meta](https://github.com/databendlabs/databend/tree/main/src/meta) on GitHub.
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<TabItemvalue="Query Layer"label="Query Layer">
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The query layer in Databend handles query computations and is composed of multiple clusters, each containing several nodes.
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Each node, a core unit in the query layer, consists of:
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-**Planner**: Develops execution plans for SQL statements using elements from [relational algebra](https://en.wikipedia.org/wiki/Relational_algebra), incorporating operators like Projection, Filter, and Limit.
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-**Optimizer**: A rule-based optimizer applies predefined rules, such as "predicate pushdown" and "pruning of unused columns", for optimal query execution.
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-**Processors**: Constructs a query execution pipeline based on planner instructions, following a Pull&Push approach. Processors are interconnected, forming a pipeline that can be distributed across nodes for enhanced performance.
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Discover more about the query layer in the [query](https://github.com/databendlabs/databend/tree/main/src/query) directory on GitHub.
**Databend** is an open-source, serverless, cloud-native data lakehouse built on object storage with a decoupled storage and compute architecture. It delivers exceptional performance and rapid elasticity, aiming to be the open-source alternative to **Snowflake**.
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**Databend** is the next-generation cloud **[Data+AI] Analytics** platform for structured, semi-structured & unstructured multimodal data.
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As the **open-source alternative to Snowflake** with **near 100% SQL compatibility** and native AI capabilities, trusted by world-class enterprises managing **800+ petabytes** and **100+ million queries daily**.
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<DocsOverview />
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**Here are some entries you might want to learn about**
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**Getting Started**
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-**[SQL Reference](/sql)**: Your swift-access guide for Databend essentials!
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-**[Connect to Databend](/guides/sql-clients)**: Connect with various SQL clients and programming languages.
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**Data Processing**
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-**[Data Loading](/guides/load-data)**: Import data from various sources into Databend.
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-**[Data Unloading](/guides/unload-data)**: Export data from Databend to different formats.
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-**[External Functions](/guides/query/external-function)**: Extend Databend's capabilities with custom functions.
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-**[Semi-Structured Data](/sql/sql-functions/semi-structured-functions)**: Process JSON, arrays, and nested data with VARIANT type.
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**AI & Advanced Analytics**
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-**[Databend AI and ML](/guides/ai-functions)**: Leverage AI capabilities in your data processing.
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-**[Data Management](/guides/data-management)**: Manage your data lifecycle effectively.
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-**[Data Lakehouse](/guides/access-data-lake)**: Seamless integration with Hive, Iceberg, and Delta Lake.
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-**[Vector Functions](/sql/sql-functions/vector-functions)**: Vector similarity and distance calculations for ML workloads.
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-**[Full-Text Search](/guides/performance/fulltext-index)**: Advanced text search and relevance scoring.
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**Performance & Scale**
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-**[Performance Optimization](/guides/performance)**: Enhance query performance with various strategies.
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-**[Benchmarks](/guides/benchmark)**: Compare Databend performance with other data warehouses.
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-**[Data Lakehouse](/guides/access-data-lake)**: Seamless integration with Hive, Iceberg, and Delta Lake.
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