VeloDB (Powered by Apache Doris)

Fastest Analytics & Search Database in the AI Era

GitHub:

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Join us in San Francisco on June 23 for an evening with @redpandadata and @datastrato on building the real-time data stack for AI agents.

- Streaming ingestion
- Metadata Management
- Real-time analytics and hybrid search

👉 Register: https://t.co/52To1gmR21

#agents

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

#Iceberg is evolving from just a table format to a key data foundation for real-time analytics, lakehouse, and AI.

Join us for a webinar on running Iceberg in real production scenario. Lessons from Lucid Motors.

👉RSVP: https://t.co/YSyWJQptu5

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Apache Doris 4.1 adds Iceberg V3 support:
- Read
- Write (including UPDATE, DELETE, MERGE INTO)
- DDL
- Table maintenance
- Diagnose

This update Doris can now covers the full Iceberg operational lifecycle.

🔗https://t.co/acykXpABfH

#Iceberg

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Come meet us at PGday Boston! Let's chat about PG + OLAP architecture.

We offer native CDC sync from Postgres WAL, real time, no middleware to manage.

Postgres stays as the transactional source of truth, and Doris can handles the analytical side.

🔗https://t.co/cPBnp5cZ9c

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

We built AgentLogsBench for AI agent observability

The benchmark test how databases handle four core access patterns of AI agent observability

Combined score:
Doris: 1.28x
Elasticsearch: 3.11x
ClickHouse: 11.91x
DuckDB: 73.48x
Postgres: 439.55x

🔗https://t.co/HHJSEnpZQf

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Running a RAG demo is very different from deploying a retrieval system for production

Apache Doris has helped firms like ByteDance to build production-ready retrieval system

Three key decisions:
- Chunk Shape
- Embedding Strategy
- Vector Index

🔗https://t.co/nM3CjJ6HW2

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

We have upgraded the Spill to Disk feature in Apache Doris 4.1, addressing OOM (out of memory) issues

1️⃣ Full operator coverage: Hash Join, Aggregation, and Sort operators all support Spill to Disk.

2️⃣ Recursive spill

3️⃣ Dynamic triggers

🔗https://t.co/WbHT4Y5i2U

[DataEngBytes Conferences @dataengbytes]

Sydney data engineers 👋
Special meetup with @VeloDB_IO — Thu 11 June, 5:30pm @ Stone & Chalk, Tech Central
Two talks on real-time analytics for AI systems + live demo
Free. Food provided. Great people.
RSVP 👇

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Testing Apache Doris, ClickHouse, Elasticsearch, and PostgreSQL in wide #JSON workloads

Setup:
- 10K JSON paths, no fixed schema
- Each row fills 100 random keys (1% sparsity)
- 100M rows, 160 GB, ingested across 1,000 files
- 16 cores, 64 GB RAM, SSD

🔗https://t.co/QrPhfeXpSL

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Last Call 📣: This May 18-19, the VeloDB team'll be at AI & Big Data Expo North America.

If your team is evaluating AI data infra or looking to consolidate search and analytics stack, find us at Booth 252.

📍 San Jose McEnery Convention Center, CA
🎟️https://t.co/LYq4v9y8YJ

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Come join us in San Francisco on May 20 to build a data layer that can keep up with the real-time, high-concurrent, and multimodal demands of enterprise agents.

Partner @puppyquery and @cocoindex_io

📅 Wed, May 20, 5:30 – 7:30 PM
📍 Trellis Cafe, SF
🎟️ https://t.co/kIy3n3nXg6

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

VeloDB supports lakehouse analytics natively, querying and write data for Iceberg table (V2/V3) directly on object storage, without moving data.

See how VeloDB performs in lakeshoue queries:
🔗 Full benchmarks + technical breakdown: https://t.co/Od22itw0u0

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Come join us in Bengaluru this Saturday for Lakehouse at Scale: Apache Doris × OLake @_olake

- Apache Doris powers AI agents with hybrid search
- Iceberg table maintenance at CDC scale

📅Saturday, May 9, 11:00 AM
📍 Hustlehub Tech Park, Bengaluru
🎟️ https://t.co/kTJMxfcEMa

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Check out @khameshra's demo for setting up an Iceberg lakehouse with Apache Doris in 15 minutes.

The stack:
PostgreSQL → @_olake (CDC) → Apache Iceberg on Object Storage → Apache Doris (Query Engine)

🔗 Full walkthrough: https://t.co/EDagt0vcam

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Apache Doris 4.1 is here

🚀New Feature Highlights:
1. New IVF and IVF_ON_DISK indexes for Vector Search

2. Better Full-Text Search: BM25 scoring

3. Supporting Long-Context #AI: 100MB JSON storage

4. Unified Lakehouse: Iceberg V2/V3 read and write

🔗https://t.co/NIu5UqzYVb

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Join us and Supermetal for a webinar to build a real-time analytics stack with lean, affordable real-time CDC.

👉 RSVP: https://t.co/ZUpcPEHFYm

Supermetal offers real-time CDC as a single Rust binary. Pair it with VeloDB to get continuous ingestion and sub-second queries.

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

We built a Snowflake alternative on #AWS

Results for a team that migrated from Snowflake to the alternative:
- 80% cost reduction
- Ingestion latency down 5-10 minutes to 1-2 seconds
- 90x query performance boost on 475M row scans: 90x improvement

🔗https://t.co/OmJJCHWOWH

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

We helped ZTO Express run real-time analytics in a demanding situation: 500 million record updates per day, on a single 4.5-billion-row table with 200+ columns.

ZTO is one of Asia's largest express delivery firms, handling 35 billion packages a year

🔗https://t.co/AuBLrQzFqk

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Apache Doris can be at the center of an open observability system. It works well with other ingestion and visualization tools.

Ingestion:
- ELK: FileBeat, LogStash
- OpenTelemetry
- Kafka

Visualization:
- Grafana
- Kibana

🔗 https://t.co/EWimGXLYvp

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

Introducing native CDC from #PostgreSQL and MySQL to VeloDB Cloud

VeloDB Cloud now connects directly to PostgreSQL WAL and MySQL Binlog, no need for traditional CDC pipeline like Debezium + Kafka + Flink + custom connectors.

🔗https://t.co/C5ChveSRrf