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From ClickHouse to Apache Doris: Powering Trillion-Log-Scale Analytics at a Leading Music Streaming Service
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From ClickHouse to Apache Doris: Powering Trillion-Log-Scale Analytics at a Leading Music Streaming Service

A major music streaming platform successfully migrated its massive 2PB log analytics from ClickHouse to Apache Doris, achieving up to 7x faster searches, 30% lower P99 query latency, 2.5x higher concurrency, and significant operational savings.

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From Elasticsearch to Apache Doris: How a Leading Payment Platform Upgraded its Financial Security Analytics, Boosting Queries by 56x
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From Elasticsearch to Apache Doris: How a Leading Payment Platform Upgraded its Financial Security Analytics, Boosting Queries by 56x

A leading payment platform, handling over 600 million daily security events, replaced its Elasticsearch and Hudi stack with Apache Doris. This move achieved up to 56x faster queries, 50% lower storage costs, and 58% higher write throughput, while simplifying architecture and boosting developer efficiency.

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Building Real-Time Lakehouse with Apache Doris: A Practical Guide
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Building Real-Time Lakehouse with Apache Doris: A Practical Guide

The Lakehouse is a data management paradigm that combines the advantages of data lakes and data warehouses. Apache Doris advances this concept with its core philosophies of "Boundless Data, Seamless Lakehouse." This article takes a deeper dive into its typical application scenarios to help readers better understand and apply its capabilities.

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EMQX now supports real-time data ingestion into Apache Doris for efficient IoT analytics
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EMQX now supports real-time data ingestion into Apache Doris for efficient IoT analytics

Apache Doris data integration is an out-of-the-box feature in EMQX, which enables complex business development through simple configuration. In a typical IoT application, EMQX, as the IoT platform, is responsible for device connection and transmitting messages. Apache Doris, as the data storage platform, is responsible for storing device status and metadata, as well as message data storage and data analysis. Using EMQX and Apache Doris, users can build high-performance, reliable, and scalable IoT applications that deliver an end-to-end solution from data acquisition through analytics to actionable intelligence.

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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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