A very common reason is a wrong site baseUrl configuration.\n

Current configured baseUrl = / (default value)\n

We suggest trying baseUrl = \n\n',document.body.prepend(n);var e=document.getElementById("__docusaurus-base-url-issue-banner-suggestion-container"),s=window.location.pathname,o="/"===s.substr(-1)?s:s+"/";e.innerHTML=o}

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Mid-to-large enterprises using it
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Apache Doris Up to 34x Faster Than ClickHouse in Real-Time Updates
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Apache Doris Up to 34x Faster Than ClickHouse in Real-Time Updates

We benchmarked Apache Doris against ClickHouse on ClickBench and SSB (Star Schema Benchmark), under fair resource allocations in each product's cloud services. Results: Apache Doris is 18-34x faster than ClickHouse in SSB and 2.5-4.6x faster than ClickHouse in ClickBench.

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From OneLake to Insights: Building Modern Analytics with Apache Doris and Microsoft Fabric
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From OneLake to Insights: Building Modern Analytics with Apache Doris and Microsoft Fabric

Connect Apache Doris to Microsoft Fabric’s OneLake, the unified data lake behind Fabric. See how to set up data and authentication in Fabric, creating an Iceberg REST Catalog in Doris, and query OneLake tables without data movement.

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Apache Doris Tops JSONBench in Cold Queries and Data Quality
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Apache Doris Tops JSONBench in Cold Queries and Data Quality

Apache Doris has topped the latest JSONBench benchmark. Apache Doris ranks first in cold query performance and data quality, and ranks second in hot queries.

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Apache Doris Achieves 70% Better Price-Performance on ARM-based AWS Graviton
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Apache Doris Achieves 70% Better Price-Performance on ARM-based AWS Graviton

We benchmarked Apache Doris on ARM-based AWS Graviton against x86 instances across five industry-standard OLAP tests (ClickBench, SSB 100G, SSB-Flat, TPC-H, and TPC-DS), and found Doris running on ARM-based Graviton consistently delivered 54%–70% higher price-performance.

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What is Apache Doris

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Core capabilities

Real-time ingestion and storage
Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation.
Lightning-fast query
Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine.
Federated querying
Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL.
Semi-structured data
Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches.
Elastic architecture
Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.
Open ecosystem
Compatible with MySQL protocol and ANSI SQL, easily integrated with BI tools. Provide open data API to be accessible for external compute engines like Spark, Flink and ML/AI.

Unified data warehouse

for various analytics use cases

From traditional batch reporting to real-time reporting and dashboards. From internal-facing analytics like traditional BI to customer-facing analytics. From decision support analytics to algorithm-driven real-time decision-making.
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