The 2025 Apache Doris & VeloDB Retrospective

Happy New Year, Data Builders!

This past year, we've pushed the boundaries of what's possible. We've seen the Apache Doris community double in size, while VeloDB has helped a wide range of organizations bridge the gap between open-source power and enterprise-grade reliability. Join us as we recap the highlights of this remarkable year.

Unprecedented Speed

Apache Doris Tops JSONBench in Cold Queries and Data Quality

Apache Doris ranked first in cold queries in the latest JSONBench test. It is about 2x faster than Elasticsearch, 160x faster than MongoDB, and over 1,000× faster than PostgreSQL in cold queries.

Apache Doris Tops RTABench, 6x Faster Than ClickHouse, 30x Faster Than PostgreSQL

RTABench (Real-Time Analytics Benchmark) is specifically designed for real-time analytics, offering a more realistic evaluation of database performance than traditional benchmarks. In standardized tests, Doris delivered up to 6 times the performance of ClickHouse, 30 times that of PostgreSQL, and 100 times that of MongoDB.

The Ultimate OLAP Showdown: Apache Doris vs. ClickHouse vs. Snowflake

In large-scale benchmarks spanning both straightforward JOINs and production-grade TPC-H/TPC-DS workloads, Apache Doris consistently delivers significantly faster performance. And on top of that, Apache Doris requires just 10%-20% of the cost of Snowflake or ClickHouse for OLAP workloads.

Fueling the AI Frontier

Apache Doris 4.0: Native Hybrid Search for AI Workloads

Apache Doris combines vector search, full-text search, and structured analytics into a single SQL engine, offering a hybrid search and anlytical processing infrastructure solution for AI-related workloads.

VeloDB: A Production-Ready Real-Time HSAP Database

VeloDB eliminates the need for fragmented subsystems by unifying full-text and vector-based semantic search with complex analytical operators, all within a single columnar storage layer and vectorized execution engine. Whether you are managing AI observability logs, powering CRM analytics, or building context-rich Generative AI applications, VeloDB's intelligent query planner produces a single, optimized execution plan for even the most demanding hybrid workloads.

Proven Across Every Spectrum

Web3

Why Ave.ai chose VeloDB over ClickHouse, Snowflake for Web3 Analytics for 10M+ Users

Key results: a consistent write throughput of 5,000 records per second, stable query traffic with P99 latency consistently around 1 second

More reads on Apache Doris / VeloDB for Web3 Analytics:

Global Tech Giant

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

Key results:

400ms latency (7× faster than pure vector search)
500GB memory (20× less than pure HNSW indexing)
89% accuracy (+7 points over pure keyword or vector alone)
Single server deployment (vs 20-30 servers for sharded vector search)

Leading AI Company Revamped Observability: 10x Faster Queries & 83% Cost Savings with Apache Doris

Key results:

10x faster query performance
Storage size reduced to 1/6th of Elasticsearch (approx. 83% savings)
Efficient handling of 10TB / 60 billion logs daily
Flexible JSON handling with Doris's VARIANT data type

Apache Doris 2026 Roadmap

Building on 2025's achievements in vector search and indexing capabilities, Apache Doris continues to deepen its AI support in 2026. The Apache Doris 2026 Roadmap focuses on advancing AI & Hybrid Search capabilities while enhancing query performance, storage efficiency, and data lake integration.

AI & Hybrid Search Innovation:

Scale vector index to support 10 billion vectors per table with disk-based ANN
Enhance full-text search with query expressions, scoring, and multi-index support
Extend hybrid search to Iceberg for unified analytics

Core Enhancements:

Query engine optimization for complex data types and ETL processing
Storage improvements for ultra-large tablets and compute-storage separation
Data lake integration with Iceberg V3 and Paimon support

VeloDB Product Updates

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Events

Jan 22, Apache Iceberg Meetup @Singapore

Revisit the slides

Matt, a PMC member of Apache Doris, provided a deep dive into Iceberg’s role as the open lakehouse standard and the critical need for modern data platforms to handle multi-modal data and diverse query patterns. The highlight of the talk was how Apache Doris acts as a unified powerhouse for hybrid search and real-time analytics. Matt explained how Doris solves today's most pressing data challenges through its:

High-performance core: Vectorized execution engine and native Parquet reader.
Advanced optimization: Multi-level caching and a smart scheduler.
Efficiency at scale: The use of materialized views to accelerate complex queries.

He also shared several performance benchmarks that demonstrate how these features translate into massive speed gains for real-world workloads.

Jan 27, Apache Polaris™ (incubating) Meetup Bay Area

This meetup brings together industry experts, from Kevin Shen's insights on accelerating analytics with VeloDB and Apache Doris, to Weimo Liu's demonstration of running real-time graph analytics without complex ETL. You'll also gain a technical deep dive into Polaris Events for advanced auditing and automation with Adnan Hemani, and discover how Jack Ye is bridging the gap between AI-native storage and structured data through the Lance ecosystem.

Jan 29, Virtual

Watch Replay: Lower Observability Costs with VeloDB, OpenTelemetry, and Grafana

Observability costs have surged with the rise of microservices and are accelerating further as AI-generated events place increasing pressure on existing systems, sometimes making observability more expensive than running the application itself. While tools like OpenTelemetry and Grafana have improved data collection and visualization, storage costs remain a major challenge. We'll explore how VeloDB reduces observability storage costs while remaining fully interoperable with the open ecosystem, and share real-world adoption stories and the value achieved by users.

Feb 11, Hong Kong

The New Era of Web3 Data: An AWS | NineData | VeloDB Joint Technical Salon

During Consensus 2026, AWS, in collaboration with NineData and VeloDB, will co-host an in-depth technical salon focused on the core infrastructure of Web3. As the Web3 industry continues to evolve rapidly, building a stable, compliant, and scalable data foundation has become critical to long-term success. This event will bring together industry experts to explore how AI is reshaping database management, how on-chain data can be transformed into real-time growth insights, and how Web3 companies can address security and compliance challenges amid increasingly stringent global regulations.

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