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Comparison · Analytics
Apache TsFile vs modeltime
A side-by-side editorial comparison of Apache TsFile and modeltime — release velocity, themes, recent moves, and the top alternatives to consider.
Apache TsFile vs modeltime: 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 modeltime?
modeltime built conformal intervals in, then went quiet on features.
modeltime is at 1.3.3, a single change making the package robust to xgboost version shifts. The feature weight sits in 1.3.2, which added a future-based parallel backend, the maape() accuracy metric and dials helpers for ADAM engine tuning, and further back in the 1.2.8 and 1.3.0 pair that introduced conformal prediction intervals and then carried them through the nested forecasting workflow.
Apache TsFile vs modeltime: 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.
modeltime
0.0ANALYTICS
modeltime built conformal intervals in, then went quiet on features.
◆ Current state
modeltime is at 1.3.3, a single change making the package robust to xgboost version shifts. The feature weight sits in 1.3.2, which added a future-based parallel backend, the maape() accuracy metric and dials helpers for ADAM engine tuning, and further back in the 1.2.8 and 1.3.0 pair that introduced conformal prediction intervals and then carried them through the nested forecasting workflow.
◆ Where it's heading
The arc runs from uncertainty quantification to execution. Conformal intervals arrived first and were then threaded through nested fitting, refitting and the printed forecast tables so users can see which confidence method produced an interval. The later work moves down a layer to how forecasts are computed — a portable future backend replacing foreach tuning — rather than what they express.
◆ Prediction
With only an xgboost compatibility fix since the 1.3.2 feature release, the entries do not support a confident prediction about what comes next beyond continued dependency maintenance.
Alternatives to Apache TsFile and modeltime
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 modeltime.
performance
performance keeps adding ways to check a model you have already fitted.
cmdstanpy
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all Apache TsFile alternatives → · See all modeltime alternatives →
Recent activity from Apache TsFile and modeltime
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d 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
- 7mo agomodeltimeRobustness to xgboost version changes
- 11mo agomodeltimefuture parallel backend, maape() metric and ADAM tuning helpers
- 2y agomodeltimeConformal intervals reach the nested forecasting workflow
- 2y agomodeltimeConformal prediction intervals introduced
- 3y agomodeltimeFixes the Smooth es() model
- 3y agomodeltimeFixes failing developer-tools tests
Frequently asked questions
What is the difference between Apache TsFile and modeltime?
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 modeltime?
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 modeltime?
Top modeltime alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime alternatives" section above for the current picks, or visit /alternatives/modeltime for the full list with editorial commentary on each.