AI · alternatives · 2026

24 alternatives to CueObserve
Open-source Anomaly detection on SQL data
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. CueObserve launched in 2021; newer entries below may have overtaken it.
- 1CO
2021 · github.com · its alternatives →
- 2OpenObserve▲305
AI-native, open-source Datadog alternative
Mar 2026 · openobserve.ai · its alternatives →
- 3
TraceRoot.AI▲344Fix bugs faster with open source, AI native observability
2025 · traceroot.ai · its alternatives →
- 4OE
Hello folks, We are launching OpenObserve. An open source Elasticsearch/Splunk/Datadog alternative written in rust and vue that is super easy to get started with and has 140x lower storage cost compared to elasticsearch. It offers logs, metrics, traces, dashboards, alerts, functions (run aws lambda like functions during ingestion and query to enrich, redact, transform, normalize and whatever else you want to do. Think redacting email IDs from logs, adding geolocation based on IP address, etc). You can do all of this from the UI, no messing up with configuration files. OpenObserve…
2023 · github.com · its alternatives →
- 5

- 6AB
I created a web page to compare different analytical databases (both self-managed and services, open-source and proprietary) on a realistic dataset. It contains 20+ databases, each with installation and data loading scripts. And they can be compared to each other on a set of 43 queries, by data load time or by storage size. There are switches to select different types of databases for comparison - for example, only MySQL compatible or PostgreSQL compatible. If you play with the switches, many interesting details will be uncovered. Full description:…
2022 · benchmark.clickhouse.com · its alternatives →
- 7MB
2021 · github.com · its alternatives →
- 8

- 9OS
2022 · opendatadiscovery.org · its alternatives →
- 10

Best no-code anomaly detection engine for Google Analytics
2022 · its alternatives →
- 11

- 12OO
Hi! One of the creators here. Very proud to finally be able to show you what we've been working on for over a year now. Curious to hear your thoughts! Objectiv is open-source (APLv2) product analytics infrastructure. It's built around a generic but strict event taxonomy, open/common data- and infra tools (currently PG, snowplow, working on bigquery with more to come), and the analyses are done using our pandas-like, SQL speaking modeling library called Bach. As a result, we’re moving towards a vision wherein models can be shared openly, independent of product, platform[1] or data…
2022 · objectiv.io · its alternatives →
- 13OO
Hey HN, Nir, Gal and Tomer here. We’re open-sourcing a set of extensions we’ve built on top of OpenTelemetry that provide visibility into LLM applications - whether it be prompts, vector DBs and more. Here’s the repo: https://github.com/traceloop/openllmetry. There’s already a decent number of tools for LLM observability, some open-source and some not. But what we found was missing for all of them is that they were closed-protocol by design, vendor-locking you to use their observability platform or their proprietary framework for running your LLMs. It’s still early in the…
2023 · github.com · its alternatives →
- 14D2
Hi! We are excited to announce the second release of Desbordante — an open-source, high-performance data profiler that is capable of discovering and validating many different patterns in data using various algorithms. Unlike existing data profilers, Desbordante focuses on discovering complex patterns in data, which are notoriously hard to extract. Since its inception in 2019, it has become the fastest open-source tool for these tasks. It also offers an array of patterns which have no alternative implementations. With this release, Desbordante now supports 17 types of patterns, such as:…
2024 · github.com · its alternatives →
- 15
OneGlanse▲77Free open-source GEO tracker for LLM visibility
Apr 2026 · oneglanse.com · its alternatives →
- 16

- 17MA
2020 · github.com · its alternatives →
- 18

- 19AR
2013 · getanomalous.com · its alternatives →
- 20

Hi HN, I'm Kaushik, and I built Rocketgraph. I believe that while other spaces have caught up to the AI wave, the observability space is still lagging behind, using the same tools and dashboards that we use to analyse logs from human-written code. But now the code is written and debugged by AI, so we need to rethink how we do observability where the observer itself is an AI. The problem that I run into is when an alert fires, I have to manually check the Grafana dashboards and write LogQL queries, which is pretty much like greping. But production usually breaks due to a schema mismatch, or a…
Jun 2026 · github.com · its alternatives →
- 21CA
Hi HN! We’re Clemens and Felix from Cito - thrilled to show you what we’ve built to help data engineers stay on top of data quality issues. Think Datadog meets Incident.io. Tests in dbt are great when checking whether specific expectations are true, but don’t work well for use cases where data patterns may change over time. When relying on testing alone, data teams regularly face situations where business stakeholders identify data issues in dashboards first, eroding trust. In such situations, understanding the implications of an issue and debugging can be a very manual and time-consuming…
2022 · citodata.com · its alternatives →
- 22SA
2017 · github.com · its alternatives →
- 23

- 24

Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →