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Apache Pinot vs Countly

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

Apache Pinot vs Countly: at a glance

FeatureApache PinotCountly
SectorInfra & APIs, AnalyticsAnalytics
Velocity score6.35.0
Sparks · 30d10
Top themesreal-time-olap, sql-ddl, vector-search, materialized-viewsanalytics, security, self-hosted, lts
Last editorial update4h ago1h 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 Countly?

Countly's two LTS lines now get the same security fixes within a week of each other.

Countly ships security patches on two LTS lines, 25.03 and 24.05. In late October 25.03.56 moved the Docker images to Node.js 24.22.1 for a Brotli CVE and brought Python 3.12.15 to the A/B testing stack; 25.03.58 tightened tokens: app-restricted tokens must state their permissions, password changes revoke a member's tokens, and single-use tokens hold under concurrent requests. 24.05.55 then brought those same fixes to the older line, including the isolated-vm sandbox for custom hook code that 25.03 adopted in August.

Read the full Countly trajectory →

Apache Pinot vs Countly: 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.

C
Countly
ANALYTICS
5.0

Countly's two LTS lines now get the same security fixes within a week of each other.

◆ Current state

Countly ships security patches on two LTS lines, 25.03 and 24.05. In late October 25.03.56 moved the Docker images to Node.js 24.22.1 for a Brotli CVE and brought Python 3.12.15 to the A/B testing stack; 25.03.58 tightened tokens: app-restricted tokens must state their permissions, password changes revoke a member's tokens, and single-use tokens hold under concurrent requests. 24.05.55 then brought those same fixes to the older line, including the isolated-vm sandbox for custom hook code that 25.03 adopted in August.

◆ Where it's heading

The work is about access control and supply chain, not new analytics features. Tokens, sessions and login counting are being tightened release by release, and the 24.05 line is being pulled up to the 25.03 runtime (Node.js 22 for custom code, Python 3.12 with CmdStanPy for A/B testing) instead of being left on older stacks. Feature work shows up only in small items such as explicitly named databases and a licence payment-overdue banner.

◆ Prediction

Expect more paired patches as token and session hardening continues on both lines. The entries don't say how long 24.05 will keep receiving backports.

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 →

Countly alternatives

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

See all Countly alternatives →

Recent activity from Apache Pinot and Countly

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

  1. 2d agoCountlyCountly Version 24.05.55
  2. 4d agoApache PinotPinot 1.6.0: SQL DDL, IVF vector search, Java 25 requirement ⚡
  3. 5d agoCountlyCountly Version 25.03.58
  4. 7d agoCountlyCountly Version 25.03.57-LTS
  5. 9d agoCountlyCountly Version 25.03.56-LTS
  6. 10d agoApache PinotPinot 1.6.0 rc1 tag, no release notes
  7. 16d agoApache PinotPinot 1.6.0 RC0: first candidate with the 1.6 highlights
  8. 20d agoCountlyCountly Version 25.03.55
  9. 1mo agoCountlyCountly Version 24.05.54
  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 Countly?

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 Countly?

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 Countly?

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