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How ByteDance Solved Billion-Scale Vector Search Problem with Apache Doris 4.0
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How ByteDance Solved Billion-Scale Vector Search Problem with Apache Doris 4.0

With Apache Doris 4.0 and its hybrid search capabilities, ByteDance built a search system handling 1 billion+ vectors, achieving accuracy, low latency, and cost-efficiency in infra costs.

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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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Fast JSON Analytics in Apache Doris: 100x Faster Than PostgreSQL and MongoDB
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Fast JSON Analytics in Apache Doris: 100x Faster Than PostgreSQL and MongoDB

Apache Doris uses the VARIANT data type to deliver flexible, high-performance JSON handling, thanks to features like dynamic subcolumns, sparse columns, schema templates, lazy materialization, and path-based indexing.

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Deploying Apache Doris with MinIO: Analytics with Storage-Compute Separation
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Deploying Apache Doris with MinIO: Analytics with Storage-Compute Separation

In the Apache Doris + MinIO architecture, Apache Doris handles compute, MinIO handles storage, and the result is a modern analytics architecture that’s fast, scalable, cost-efficient, and separates compute from storage.

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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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