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Comparison · Analytics
Apache TsFile vs Marquez
A side-by-side editorial comparison of Apache TsFile and Marquez — release velocity, themes, recent moves, and the top alternatives to consider.
Apache TsFile vs Marquez: at a glance
What is Apache TsFile?
TsFile is quietly rebuilding itself as an Arrow-speaking interchange format
Apache TsFile is the columnar time-series file format underlying IoTDB, maintained as three parallel implementations in Java, C++ and Python. Recent releases have concentrated on the C++ and Python ends: SIMD paths and parallel reads in 2.4.0, an Arrow-compatible result path from C++ through to Python DataFrames in 2.3.0, and conversion scripts from CSV, Parquet and Arrow into TsFile in 2.3.1. The Java side gets steadier, smaller work — serialized-size calculation, schema modification during writes, encryption configuration.
What is Marquez?
Marquez spent 2024 turning a lineage store into a UI, then stopped releasing
Marquez is the reference metadata server for OpenLineage, and this window captures a concentrated push on its web interface: a column-lineage page and redesigned lineage graph in 0.45.0, data quality and job status displays in 0.47.0, and a data observability dashboard in 0.50.0 showing event stats over 24-hour and 7-day windows with per-source, per-dataset and per-job views. The API side moved in step — job tagging, dataset schema versions, paging on jobs and dataset versions, job-to-job lineage, richer metrics labels. One contributor accounts for nearly all the web work in these entries. Note that the 0.45 through 0.49 releases were all stamped within three minutes of each other and in reverse version order, so publication timestamps here do not reflect release order.
Apache TsFile vs Marquez: editorial side-by-side
Apache TsFile
2.5ANALYTICS
TsFile is quietly rebuilding itself as an Arrow-speaking interchange format
◆ Current state
Apache TsFile is the columnar time-series file format underlying IoTDB, maintained as three parallel implementations in Java, C++ and Python. Recent releases have concentrated on the C++ and Python ends: SIMD paths and parallel reads in 2.4.0, an Arrow-compatible result path from C++ through to Python DataFrames in 2.3.0, and conversion scripts from CSV, Parquet and Arrow into TsFile in 2.3.1. The Java side gets steadier, smaller work — serialized-size calculation, schema modification during writes, encryption configuration.
◆ Where it's heading
The centre of gravity has moved from format features to ecosystem reach. Arrow-backed DataFrames and format converters are not about storing time series better; they are about making TsFile readable by the Python analytics stack without a translation layer, which is the gap that keeps a specialized format confined to its own database. The C++ performance work in 2.4.0 serves the same end, since the Python bindings sit on top of it. Version numbering runs on two lines at once, with 1.1.x backports still shipping alongside the 2.x series.
◆ Prediction
Given the direction of the Arrow work, the Python interface is the most likely target for further capability rather than the Java one. The notes do not indicate when the 1.1 maintenance line ends.
Marquez
0.0ANALYTICS
Marquez spent 2024 turning a lineage store into a UI, then stopped releasing
◆ Current state
Marquez is the reference metadata server for OpenLineage, and this window captures a concentrated push on its web interface: a column-lineage page and redesigned lineage graph in 0.45.0, data quality and job status displays in 0.47.0, and a data observability dashboard in 0.50.0 showing event stats over 24-hour and 7-day windows with per-source, per-dataset and per-job views. The API side moved in step — job tagging, dataset schema versions, paging on jobs and dataset versions, job-to-job lineage, richer metrics labels. One contributor accounts for nearly all the web work in these entries. Note that the 0.45 through 0.49 releases were all stamped within three minutes of each other and in reverse version order, so publication timestamps here do not reflect release order.
◆ Where it's heading
The arc is a backend project growing a front end: lineage data that existed in the API was progressively given pages, panels and paging, and by 0.50.0 the framing had shifted from lineage graph to observability dashboard. Tagging deepened in the same period, moving from dataset tags to field-level tags to job tags. That arc stops abruptly — 0.50.0 in October 2024 is the last entry, with nothing published in the roughly two years since.
◆ Prediction
The entries give no roadmap signal past 0.50.0, and the job-to-job lineage change was explicitly framed as a prompt for a wider parent/child hierarchy discussion that no later release picks up, so that hierarchy work is best read as unfinished rather than planned.
Alternatives to Apache TsFile and Marquez
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Apache TsFile or Marquez.
OpenDataDiscovery
Four ODD Platform releases in two weeks, and not one of them changes the product
Apache Baremaps
Baremaps got geoparquet and hillshading, then went quiet for eighteen months in incubation
Deequ
Deequ ships GitHub tags whose release notes are one commit message long
Amundsen
Amundsen's last release was a config flag, and the feed has been silent for two years
OpenHouse
LinkedIn's Iceberg control plane, shipping one pull request per release.
See all Apache TsFile alternatives → · See all Marquez alternatives →
Recent activity from Apache TsFile and Marquez
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 19d agoApache TsFileSIMD and parallel read paths in Apache TsFile 2.4.0
- 2mo agoApache TsFileCSV, Parquet and Arrow conversion scripts for TsFile 2.3.1
- 3mo agoApache TsFileArrow-backed DataFrames and paginated reads in TsFile 2.3.0
- 3mo agoApache TsFileWrite-time schema changes and read/write encryption in TsFile 2.2.1
- 7mo agoApache TsFilePython text types and C++ tag filtering in TsFile 2.2.0
- 7mo agoApache TsFileBackport maintenance on the TsFile 1.1 line
- 1y agoMarquezMarquez 0.50.0 adds a data observability dashboard
- 2y agoMarquezMarquez 0.45.0 ships a column lineage page and redesigned graph
- 2y agoMarquezMarquez 0.46.0 cleans up the UI and fixes streaming terminal events
- 2y agoMarquezMarquez 0.47.0 adds data quality and job status views, job tagging
- 2y agoMarquezMarquez 0.49.0 adds job-to-job lineage to the API
- 2y agoMarquezMarquez 0.48.0 adds paging and dataset schema versions
Frequently asked questions
What is the difference between Apache TsFile and Marquez?
They serve adjacent needs but don't currently overlap on shipped themes. Apache TsFile is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Apache TsFile better than Marquez?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache TsFile is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to Apache TsFile?
Top Apache TsFile alternatives in Analytics are ranked by recent ship velocity. Browse the "Apache TsFile alternatives" section above for the current picks, or visit /alternatives/apache-tsfile for the full list with editorial commentary on each.
What are the best alternatives to Marquez?
Top Marquez alternatives in Analytics are ranked by recent ship velocity. Browse the "Marquez alternatives" section above for the current picks, or visit /alternatives/marquez for the full list with editorial commentary on each.