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Comparison · Analytics
performance vs Parseable
A side-by-side editorial comparison of performance and Parseable — release velocity, themes, recent moves, and the top alternatives to consider.
performance vs Parseable: at a glance
What is performance?
performance keeps adding ways to check a model you have already fitted.
performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.
What is Parseable?
Parseable's 3.0 turns a log store into a logs, metrics, traces and APM console.
Parseable has spent the 2.9 line hardening a multi-tenant ingestion engine — API keys, OAuth sync, tenant quotas, credential masking, and a run of injection and path-traversal fixes contributed from outside the core team. Version 3.0.0 collects that groundwork into a platform release: PromQL-based alerts, dashboard templates, dataset tagging, trace and ingestion endpoints, service maps and APM in the Prism UI, and a custom-provider option in the LLM flow. The ingestion story also changed shape, with fluent-bit dropped from the scripts in favour of an OpenTelemetry collector.
performance vs Parseable: editorial side-by-side
performance
0.0ANALYTICS
performance keeps adding ways to check a model you have already fitted.
◆ Current state
performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.
◆ Where it's heading
Two consistent habits. Diagnostics keep gaining arguments to narrow what is examined — ppc_range, x_limits, maximum_dots, show_ci — which reads as a package being used on models large and awkward enough that the defaults stopped working. And simulated residuals via DHARMa keep displacing standard ones as the basis for the checks themselves.
◆ Prediction
With check_priors() newly added and Bayesian predictive checks now routed through modelbased, the next release most likely extends the Bayesian diagnostic set rather than reworking the frequentist checks.
Parseable
6.3ANALYTICS
Parseable's 3.0 turns a log store into a logs, metrics, traces and APM console.
◆ Current state
Parseable has spent the 2.9 line hardening a multi-tenant ingestion engine — API keys, OAuth sync, tenant quotas, credential masking, and a run of injection and path-traversal fixes contributed from outside the core team. Version 3.0.0 collects that groundwork into a platform release: PromQL-based alerts, dashboard templates, dataset tagging, trace and ingestion endpoints, service maps and APM in the Prism UI, and a custom-provider option in the LLM flow. The ingestion story also changed shape, with fluent-bit dropped from the scripts in favour of an OpenTelemetry collector.
◆ Where it's heading
The direction is consolidation: rather than being the cheap object-store log backend that something else queries, Parseable is absorbing the query, alerting and dashboard layers that normally sit above it. PromQL support is the clearest tell — it targets teams whose alert rules are already written for a Prometheus-shaped world. Performance work is tracking that ambition too, with zstd manifests, configurable concurrent object-store calls and faster field-stats sitting alongside the feature list.
◆ Prediction
The next releases most likely fill in the metrics side to match the logs side — deeper PromQL coverage and more dashboard and alert templates — while the 3.0 UI migrations settle through point releases. Whether the LLM provider hook grows into anything beyond configuration isn't visible from these entries.
Alternatives to performance and Parseable
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 performance or Parseable.
modeltime
modeltime built conformal intervals in, then went quiet on features.
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 performance alternatives → · See all Parseable alternatives →
Recent activity from performance and Parseable
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoParseableParseable 3.0 adds PromQL alerts, APM and dashboard templates ⚡
- 21d agoParseableRelease v2.9.5
- 1mo agoParseableBugfix release v2.9.4
- 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
- 1mo agoParseableFeature release v2.9.3
- 1mo agoParseableFeature release v2.9.2
- 1mo agoParseableBug fix release v2.9.1
- 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
- 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
- 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
- 10mo agoperformanceFixes CRAN checks after an rstanarm update
- 11mo agoperformancetinytable output format in display()
Frequently asked questions
What is the difference between performance and Parseable?
They serve adjacent needs but don't currently overlap on shipped themes. Parseable is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 performance better than Parseable?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Parseable is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 performance?
Top performance alternatives in Analytics are ranked by recent ship velocity. Browse the "performance alternatives" section above for the current picks, or visit /alternatives/easystats-performance for the full list with editorial commentary on each.
What are the best alternatives to Parseable?
Top Parseable alternatives in Analytics are ranked by recent ship velocity. Browse the "Parseable alternatives" section above for the current picks, or visit /alternatives/parseable for the full list with editorial commentary on each.