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Comparison · Analytics

Apache Pinot vs Tinylytics

A side-by-side editorial comparison of Apache Pinot and Tinylytics — release velocity, themes, recent moves, and the top alternatives to consider.

Apache Pinot vs Tinylytics: at a glance

FeatureApache PinotTinylytics
SectorInfra & APIs, AnalyticsAnalytics
Velocity score6.35.0
Sparks · 30d10
Top themesreal-time-olap, sql-ddl, vector-search, materialized-viewsweb-analytics, data-quality, seo-audit, mcp
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is Apache Pinot?

Pinot 1.6 adds SQL DDL and vector backends, and now needs Java 25 to run its services.

1.6.0 on 29 October lets operators manage tables through CREATE, DROP and SHOW statements, gives materialized views DDL and single-stage query rewrite, and adds GROUPING SETS, ROLLUP and CUBE to both query engines. Vector search gains IVF_FLAT, IVF_PQ and IVF_ON_DISK backends alongside HNSW. The release also removes legacy pieces: native text and FST indexes, Spark 2 and Presto integrations, and APIs deprecated through 1.3.0.

Read the full Apache Pinot trajectory →

What is Tinylytics?

Tinylytics is cleaning its numbers and adding an AI-ranked SEO audit for Ultra customers

Tinylytics shipped a simpler embed script, moved widget setup into Settings, and now excludes hits from cloud hosting networks and Tor, after filtering a Singapore bot source in September that accounted for around 95% of traffic from that country. On Ultra, a new SEO audit has an AI model rank findings into a fix list, with weekly re-checks. Form tracking, Named Goals, stat cards, and timestamped hit imports fill out the period.

Read the full Tinylytics trajectory →

Apache Pinot vs Tinylytics: editorial side-by-side

Apache Pinot logo
Apache Pinot
INFRA · APISANALYTICS
6.3

Pinot 1.6 adds SQL DDL and vector backends, and now needs Java 25 to run its services.

◆ Current state

1.6.0 on 29 October lets operators manage tables through CREATE, DROP and SHOW statements, gives materialized views DDL and single-stage query rewrite, and adds GROUPING SETS, ROLLUP and CUBE to both query engines. Vector search gains IVF_FLAT, IVF_PQ and IVF_ON_DISK backends alongside HNSW. The release also removes legacy pieces: native text and FST indexes, Spark 2 and Presto integrations, and APIs deprecated through 1.3.0.

◆ Where it's heading

Pinot is moving toward being operated like a SQL database. The multi-stage engine's SQL coverage has grown release by release, and table lifecycle now joins it, while vector backends pull retrieval workloads into the same store. The upgrade cost is real: Java 25 for services, Scala 2.13 for Spark artifacts, and mixed-version limits around SMART aggregation. Federation, the headline of 1.5, doesn't feature in the 1.6 highlights.

◆ Prediction

Expect materialized-view rewrite to reach the multi-stage engine, since it is single-stage only today. A security patch on 1.6 would match what followed 1.5.0.

T
Tinylytics
ANALYTICS
5.0

Tinylytics is cleaning its numbers and adding an AI-ranked SEO audit for Ultra customers

◆ Current state

Tinylytics shipped a simpler embed script, moved widget setup into Settings, and now excludes hits from cloud hosting networks and Tor, after filtering a Singapore bot source in September that accounted for around 95% of traffic from that country. On Ultra, a new SEO audit has an AI model rank findings into a fix list, with weekly re-checks. Form tracking, Named Goals, stat cards, and timestamped hit imports fill out the period.

◆ Where it's heading

Three lines are running together: data quality, tools that say what to do next, and agent access. Each filtering change makes the numbers more defensible, the SEO audit moves the product from reporting toward recommending, and the MCP and API keep gaining tools with most releases. The old-hit import, with its original timestamps, also courts users switching from other analytics tools.

◆ Prediction

Expect more audit-style features on Ultra and MCP tools that follow each new dashboard surface, as content issues and widget settings just did. Further traffic filtering is likely, given how often it has come up since September.

Apache Pinot alternatives

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Tap any card for the full editorial trajectory or compare directly with Apache Pinot.

See all Apache Pinot alternatives →

Tinylytics alternatives

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Tap any card for the full editorial trajectory or compare directly with Tinylytics.

See all Tinylytics alternatives →

Recent activity from Apache Pinot and Tinylytics

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 4d agoApache PinotPinot 1.6.0: SQL DDL, IVF vector search, Java 25 requirement ⚡
  2. 5d agoTinylyticsA simpler embed script, cleaner stats and archiving that keeps your history
  3. 10d agoApache PinotPinot 1.6.0 rc1 tag, no release notes
  4. 12d agoTinylyticsAn SEO audit with a ranked fix list, page names, and imports that keep their dates
  5. 16d agoApache PinotPinot 1.6.0 RC0: first candidate with the 1.6 highlights
  6. 17d agoTinylyticsAutomatic form tracking, a Direct row in Referrers, and more countries in email reports
  7. 26d agoTinylyticsStat cards, new widget looks, Developer mode, and achievements
  8. 1mo agoTinylyticsCleaner stats: Singapore bot traffic is now filtered out
  9. 1mo agoTinylyticsNamed Goals, Rebuilt Docs, and a Bigger MCP Toolbox
  10. 4mo agoApache PinotApache Pinot 1.5.1
  11. 6mo agoApache PinotApache Pinot Release 1.5.0 ⚡
  12. 1y agoApache PinotApache Pinot Release 1.4.0

Frequently asked questions

What is the difference between Apache Pinot and Tinylytics?

They serve adjacent needs but don't currently overlap on shipped themes. Apache Pinot is currently shipping more aggressively (velocity 6.3 vs 5.0), 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 Apache Pinot better than Tinylytics?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache Pinot is currently shipping more aggressively (velocity 6.3 vs 5.0), 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 Apache Pinot?

Top Apache Pinot alternatives in Analytics are ranked by recent ship velocity. Browse the "Apache Pinot alternatives" section above for the current picks, or visit /alternatives/apache-pinot for the full list with editorial commentary on each.

What are the best alternatives to Tinylytics?

Top Tinylytics alternatives in Analytics are ranked by recent ship velocity. Browse the "Tinylytics alternatives" section above for the current picks, or visit /alternatives/tinylytics for the full list with editorial commentary on each.