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Log management · October 2026 Edition

Elastic Stack vs OpenObserve

Zero of fourteen models named Elastic Stack first on the direct prompt; zero named OpenObserve. Elastic Stack was named by fourteen of the fourteen models and OpenObserve by ten and Elastic Stack carries 54 labels and OpenObserve 16, so the shares are not directly comparable.

Elastic Stack

criticized challenger

Named in five categories this edition.

OpenObserve

accepted challenger

Named in seven categories this edition.

First-choice share6%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate30%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#6A position in a field of 12; printed, not drawn.
Labels5416A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Elastic Stack reading right to left. Rank and label count are printed, not drawn.Datadog Log Management was named alongside these two in eleven of the fourteen direct answers. Datadog Log Management vs Elastic Stack · Datadog Log Management vs OpenObserve · Graylog vs Elastic Stack

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the log management page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Elastic StackFirst choices, of fourteen modelsOpenObserve
Direct001 against Elastic Stack
Paraphrase102 against Elastic Stack
Comparative00
Budget-constrained116 against Elastic Stack
Scale-constrained101 against Elastic Stack
Negative005 against Elastic Stack
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Elastic Stack and OpenObserve stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Elastic Stack OpenObserve first choice named as an alternative argued againstblank: not namedEach cell is one answer, Elastic Stack on the left and OpenObserve on the right.

The direct prompt

The plain question, one answer per model, grouped by where Elastic Stack and OpenObserve stood in it.

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniDatadog Log Management alternatives: Elastic Stack, Microsoft Sentinel, New Relic Logs
Gemini 3.5 FlashBetter Stack alternatives: Axiom, Grafana Cloud, New Relic Logs, OpenObserve, Sumo Logic
Grok 4.1 FastDatadog Log Management alternatives: Elastic Stack, Graylog, Sumo Logic
Qwen 3.7 FlashDatadog Log Management alternatives: Coralogix, Elastic Stack, Grafana Loki, Sentry
GLM 4.7 FlashXDatadog Log Management alternatives: Elastic Stack, SolarWinds Loggly, Splunk
GPT-6 LunaBetter Stack alternatives: Datadog Log Management, Elastic Stack, Grafana Cloud, Sumo Logic

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice
Perplexity SonarDatadog Log Management alternatives: Coralogix, Graylog, Logit.io, ManageEngine EventLog Analyzer, New Relic Logs
Mistral SmallDatadog Log Management, Graylog alternatives: Logmanager, New Relic Logs
DeepSeek V4 FlashDatadog Log Management, Graylog alternatives: Grafana Loki, Middle ware, Sumo Logic
Llama 4 MaverickDatadog Log Management alternatives: LogicMonitor, New Relic Logs, SigNoz
Kimi K2Graylog alternatives: Better Stack, Grafana Loki, Logz.io, SigNoz
MiniMax M2.5Graylog alternatives: Datadog Log Management, Sumo Logic
Muse Glimmer 30BDatadog Log Management alternatives: Graylog, ManageEngine Log360

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Elastic Stack leads by three points.
Elastic Stack3%#7 of 11
OpenObserve0%#10 of 11
The full small business standing →
Mid-marketThe figures above
Elastic Stack leads by four points.
Elastic Stack6%#5 of 12
OpenObserve2%#6 of 12
The full mid-market standing →
Enterprise
Elastic Stack leads by two points.
Elastic Stack4%#3 of 10
OpenObserve2%#– of 10
The full enterprise standing →

What the models said about Elastic Stack

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“The Trap to Avoid: The "Free" ELK Stack (Elasticsearch)... This is often a financial mistake for small companies.” Gemini 3.5 Flash · budget prompt · hard negative
“Avoid spending money on a tool that requires a full-time engineer just to keep the lights on (like raw ELK).” GLM 4.7 FlashX · negative prompt · hard negative
“Verdict: Avoid self-hosting unless you have dedicated DevOps/SRE resources.” Kimi K2 · negative prompt · hard negative
“This is a popular open-source option that is highly customizable and scalable. It's free to use” Mistral Small · budget prompt · first choice
“Datadog or Elastic Cloud are the most common sweet spots for companies of your size” DeepSeek V4 Flash · scale prompt · first choice
“I'd suggest Datadog or ELK Stack as starting points” Claude Haiku 4.5 · paraphrase prompt · first choice

What the models said about OpenObserve

No label in this category carried a quote.

Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.