Lima
Lima 2.3 nears release, with a Windows path that drops QEMU and a new TUI
A side-by-side editorial comparison of Apache Pinot and Dagger — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Dagger now runs the engines for you and reports CI per test, not per job.
Dagger's recent changelog holds two product moves. Cloud Engines, in September, are hosted engines with scale-out, distributed cache and observability, billed only for resources used, with Dagger claiming repeat work costs 5× less. Test-native CI, in October, tracks individual tests, so a failure names the test and only that test is run again. Around them sit cache and plumbing changes, including COPY steps that depend only on the files they copy and SSH-mounted remote filesystems.
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.
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.
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.
Dagger's recent changelog holds two product moves. Cloud Engines, in September, are hosted engines with scale-out, distributed cache and observability, billed only for resources used, with Dagger claiming repeat work costs 5× less. Test-native CI, in October, tracks individual tests, so a failure names the test and only that test is run again. Around them sit cache and plumbing changes, including COPY steps that depend only on the files they copy and SSH-mounted remote filesystems.
Both moves rest on the same idea: treat the pipeline as a graph Dagger can see into, then avoid repeating work. A layer cache that survives unrelated file changes, per-test reruns and a distributed cache all reduce what a run must redo. Cloud Engines turn that saving into something sold, the one metered offering in these entries.
Expect Test-native CI and Cloud Engines to converge, with per-test reruns offered through hosted engines. That link is inferred from the two launches; the entries neither state it nor give pricing detail.
Other Infra & APIs 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 Pinot or Dagger.
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See all Apache Pinot alternatives → · See all Dagger alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Apache Pinot is currently shipping more aggressively (velocity 6.3 vs 2.5), 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Apache Pinot is currently shipping more aggressively (velocity 6.3 vs 2.5), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top Apache Pinot alternatives in Infra & APIs 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.
Top Dagger alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Dagger alternatives" section above for the current picks, or visit /alternatives/dagger for the full list with editorial commentary on each.