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Apache Doris for log and time series data analysis in NetEase, why not Elasticsearch and InfluxDB?
Best Practice

Apache Doris for log and time series data analysis in NetEase, why not Elasticsearch and InfluxDB?

NetEase has replaced Elasticsearch and InfluxDB with Apache Doris in its monitoring and time series data analysis platforms, respectively, achieving 11X query performance and saving 70% of resources.

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Apache Doris version 2.1.3 just released
Release Note

Apache Doris version 2.1.3 just released

This version has updated several improvements, including writing data back to Hive, materialized view, permission management and bug fixes. It further enhances the performance and stability of the system.

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Multi-tenant workload isolation: a better balance between isolation and utilization
Tech Sharing

Multi-tenant workload isolation: a better balance between isolation and utilization

Apache Doris supports workload isolation based on Resource Tag and Workload Group. It provides solutions for different tradeoffs among the level of isolation, resource utilization, and stable performance.

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From Presto, Trino, ClickHouse, and Hive to Apache Doris: SQL convertor for easy migration
Tech Sharing

From Presto, Trino, ClickHouse, and Hive to Apache Doris: SQL convertor for easy migration

Users can execute queries with their old SQL syntaxes directly in Doris or batch convert their existing SQL statements on the visual SQL conversion interface.

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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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