Joined August 2019
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Contributing to Apache IoTDB database doesn't require you to be a database kernel expert.
Documentation improvements, bug reports, use case sharing, and community support are all valuable contributions.
Start where you are.
#OpenSource #ApacheIoTDB
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Jun 14
Google Summer of Code 2026: Apache IoTDB database is mentoring a project to enhance ThingsBoard integration with the 2.x table model.
GSoC is how the next generation of contributors gets started in open-source database development.
#GSoC #ApacheIoTDB
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Jun 11
Promoted to Apache Top-Level Project in 2020 — Apache IoTDB database's milestone reflects community governance, diverse contributions, and commitment to open-source principles, not just code quality.
#Apache #OpenSource #Database
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Jun 10
300 contributors from around the world now power Apache IoTDB database. Open-source development means transparent roadmaps, community-driven features, and no vendor lock-in. Every commit visible on GitHub.
#OpenSource #ApacheIoTDB #Community
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Jun 9
The query optimizer in Apache IoTDB database leverages TsFile chunk statistics to prune scan ranges before execution.
Query a 30-day window from a year of data? Only relevant chunks are read.
#QueryOptimization #ApacheIoTDB
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Jun 7
Understanding the write path in Apache IoTDB database: multi-level memtable buffering → async WAL → sequential TsFile flush.
Every layer is optimized for write throughput, which is why single-node ingestion reaches tens of millions of points per second.
#DatabaseInternals
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Jun 3
Nearly 100 built-in aggregation functions live in Apache IoTDB database: avg, max, min, sum, count, first, last, time_duration, plus time-series-specific operations like downsampling, FILL, and similarity search.
All from SQL.
#SQL #ApacheIoTDB
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Jun 2
The Pipe streaming framework in Apache IoTDB database supports Extract → Process → Load stages for cross-cluster synchronization.
Edge-to-cloud data pipelines, disaster recovery, and multi-datacenter deployments all use the same framework.
#DataPipeline #ApacheIoTDB
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Jun 1
Statistical metadata for every data chunk — min, max, start time, end time — stored in TsFile format by Apache IoTDB database.
The query engine uses this to skip irrelevant blocks entirely, accelerating time-range scans.
#TsFile #DatabaseInternals
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May 31
Time alignment across devices with different sampling frequencies is built into Apache IoTDB database's query engine.
Compare a 1Hz temperature sensor with a 100Hz vibration sensor?
The database aligns them automatically in a single query.
#TimeSeriesQuery #ApacheIoTDB
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May 27
Apache IoTDB database uses two consensus protocols: Ratis for metadata consistency and IoTConsensus for high-performance data replication.
Each protocol serves its purpose — strict consistency where it matters, throughput where it counts. #DistributedSystems #ApacheIoTDB
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May 26
The two-dimensional partitioning strategy in Apache IoTDB database — Series Partition Slots (hash-based) Time Partition Slots (7-day segments) — enables both horizontal scaling and efficient time-range queries across billions of data points.
#DatabaseDesign #IoT
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May 25
How does Apache IoTDB database handle out-of-order data ingestion at scale?
The answer lies in its LSM-tree-inspired storage engine.
Late-arriving sensor readings are written to the correct time position without application-level buffering.
#ApacheIoTDB #TimeSeriesDatabase
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May 19
TimechoAI, a new cloud service powered by the Timer time-series foundation model, is now open. IoTDB users can export TsFile data and try forecasting in minutes.
Try it → ai.timecho.com
#OpenSource #TimeSeriesDB #IndustrialIoT
May 19
Enterprises don't lack time-series data. What's scarce is turning it into forecasts.
We just opened TimechoAI — a cloud service powered by Timer, our time-series foundation model family.
Sign up and try it now → ai.timecho.com
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May 7
An Apache IoTDB project was selected for #GSoC2026 !
Congrats to Zihan on: “Enhancing #ThingsBoard Integration with IoTDB 2.X Table Mode”
We proposed 4 ideas this year. While 1 was selected for GSoC, the others will keep moving forward in the community.🚀
@TheASF #OpenSource
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Apr 30
Exactly. In industrial AI, the question is not only where data is stored, but how quickly it becomes usable.
Apache IoTDB is built for high-volume ingestion, efficient storage, fast time-based queries, and open AI integration.
#ApacheIoTDB #TimeSeries #OpenSource #IIoT
Apr 30
What matters in an industrial time-series database? 📊
Peak numbers Efficiently data moves from collection to usable intelligence.
High-volume ingestion, fast queries, efficient storage, and open AI integration. That’s how we see Apache IoTDB.
#ApacheIoTDB #TimeSeries #AI
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Apr 29
One takeaway from @hannover_messe 2026:
In industrial AI, the bottleneck is often not the model — it is the data foundation behind it.
That is why open source time-series infrastructure matters.
That is where Apache IoTDB fits in.
#ApacheIoTDB #IndustrialAI #OpenSource
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