24 tools indexed verified 2026·07·03 quality · catalog · lineage
Data observability,
indexed.
A reference catalog of tools in the modern data stack — structured for comparison, sourced from vendor documentation, free of paid placement, verified by hand. Three views of the same data: by cluster, by capability, by tool.
Tools indexed 24
Open source 9
Published pricing 8 · 16 sales-led
Last verification 2026·07·03
01
Browse by cluster
Three clusters, one vertical.
§ 01
Quality
& testing
11 tools · 3 open source
Pre-production and post-production checks on warehouse correctness, freshness, and schema. Where your data quality story actually starts.
Browse cluster → § 02
Catalog
& discovery
10 tools · 5 open source
Asset inventory, business glossary, ownership tracking, and search for warehouse data.
Browse cluster → § 03
Lineage
& metadata
3 tools · 1 open source
Cross-system data flow tracking, impact analysis, and column-level lineage from source through consumption.
Browse cluster → 02
Every tool, by name
The full ledger.
Cluster ▸
Scope ▸
24 / 24 shown
Idx Tool · Vendor One-liner Pricing Deploy License Q · C · L
01 Acceldata Acceldata · est. 2018 · Campbell, CA
Enterprise data observability with ML data quality, reconciliation, and a built-in catalog — strong on hybrid and on-prem estates.
Contact sales Hybrid Proprietary Q C L Quality & testing → 02 Alation Alation · est. 2012 · Redwood City, CA
The incumbent that defined the data catalog — behavioral search, deep governance, and strong column-level lineage.
Contact sales SaaS · Self-host Proprietary Q C L Catalog & discovery → 03 Amundsen LF AI & Data Foundation · est. 2019
The Lyft-born OSS catalog that invented search-first discovery — historically important, but development has largely stalled since 2024.
OSS · paid tiers Self-host OSS Q C L Catalog & discovery → 04 Anomalo Anomalo · est. 2018
GUI-first ML anomaly detection at petabyte scale — pivoting in 2026 around agentic AI and unstructured-data monitoring.
Contact sales SaaS · Self-host Proprietary Q C L Quality & testing → 05 Apache Atlas Apache Software Foundation · est. 2015
The ASF's Hadoop-native metadata framework — typed entities, classification propagation via lineage, and Ranger-enforced policies.
OSS · paid tiers Self-host OSS Q C L Catalog & discovery → 06 Atlan Atlan · est. 2019 · Singapore
Enterprise catalog and governance plane positioned as the AI context layer — connectors, lineage, contracts, and an MCP server for agents.
Contact sales Hybrid Proprietary Q C L Catalog & discovery → 07 Bigeye Bigeye · est. 2019
Enterprise data observability with Autometrics ML thresholds — repositioning in 2026 as an AI Trust Platform with runtime governance.
Contact sales SaaS · Self-host Proprietary Q C L Quality & testing → 08 Cloudera Data Lineage (Octopai) Cloudera · est. 2016 · Santa Clara, CA · acq. Cloudera 2024
SaaS lineage with 60+ connectors and a 24-hour deploy story — built for hybrid enterprise estates without IBM-stack baggage.
Contact sales SaaS Proprietary Q C L Lineage & metadata → 09 Collibra Collibra · est. 2008 · Brussels, Belgium
Enterprise data-and-AI governance incumbent: catalog, glossary, workflow stewardship, lineage, and a separate ML data-quality module.
Contact sales SaaS Proprietary Q C L Catalog & discovery → 10 Datafold Datafold · est. 2020 · San Francisco, CA
Pre-merge data diffing and column-level lineage — the tool that shifts data quality left into the pull request.
From $799 custom SaaS · Self-host Proprietary Q C L Quality & testing → 11 DataHub Acryl Data · est. 2021 · Palo Alto, CA
Apache-2.0 metadata platform with a serious managed counterpart — strongest event-driven architecture and column-level SQL lineage in OSS.
OSS · free SaaS · Self-host OSS Q C L Catalog & discovery → 12 dbt-expectations Metaplane (Datadog) · est. 2020
Open-source dbt package adding 50+ Great Expectations-style assertions as native dbt tests that run in your own warehouse.
OSS · paid tiers Self-host OSS Q C L Quality & testing → 13 Elementary Elementary Data · est. 2021 · Tel Aviv, Israel
The dbt-native observability layer — tests, anomaly detection, and lineage that live inside your dbt project.
OSS · free SaaS · Self-host OSS Q C L Quality & testing → 14 Great Expectations Great Expectations · est. 2017
Python-native data validation framework — the OSS standard, now in stewardship transition after the May 2026 acquisition.
OSS · free SaaS · Self-host OSS Q C L Quality & testing → 15 IBM Manta Data Lineage IBM · est. 2016 · Armonk, NY · acq. IBM 2023
The deepest scanner-driven lineage product on the market — built for legacy estates (SAP, Cognos, Informatica) modern catalogs miss.
Contact sales SaaS · Self-host Proprietary Q C L Lineage & metadata → 16 Marquez Marquez Project · est. 2018
The OpenLineage reference backend — vendor-neutral lineage events from Spark, Airflow, dbt, and Flink, stored and visualised.
OSS · paid tiers Self-host OSS Q C L Lineage & metadata → 17 Metaplane Metaplane (Datadog) · est. 2019 · Boston, MA · acq. Datadog 2025
ML-powered, no-code data observability for the dbt and warehouse stack with automatic column-level lineage — now Metaplane by Datadog.
Published SaaS Proprietary Q C L Quality & testing → 18 Monte Carlo Monte Carlo Data · est. 2019 · San Francisco, CA
Warehouse-side data observability for teams whose problems are upstream of dbt — ingestion, streaming, and across the full pipeline.
Contact sales SaaS Proprietary Q C L Quality & testing → 19 OpenMetadata Collate · est. 2021 · Saratoga, CA
Apache-2.0 unified metadata platform with a deliberately simple stack — discovery, lineage, quality, and contracts in one project.
OSS · free SaaS · Self-host OSS Q C L Catalog & discovery → 20 Secoda Secoda (Atlassian) · est. 2021 · Toronto, Ontario, Canada · acq. Atlassian 2025
AI-native data catalog, lineage, and observability from Toronto — acquired by Atlassian in December 2025 to power Rovo AI.
Contact sales SaaS · Self-host Proprietary Q C L Catalog & discovery → 21 Select Star Select Star (Snowflake) · est. 2020 · San Francisco, California, United States · acq. Snowflake 2025
Automated data catalog with column-level lineage parsed from query logs — being acquired by Snowflake to power Horizon Catalog.
Contact sales SaaS Proprietary Q C L Catalog & discovery → 22 Sifflet Sifflet · est. 2021 · Paris, France
EU-built full-stack data observability pairing ML-driven monitoring with an embedded catalog and field-level lineage.
Contact sales SaaS · Self-host Proprietary Q C L Quality & testing → 23 Soda Soda Data · est. 2019 · Brussels, Belgium
YAML-first data contracts and observability — SodaCL plus Soda Cloud, with anomaly detection and a self-hosted Kubernetes runner.
From $750 custom SaaS · Self-host Proprietary Q C L Quality & testing → 24 Unity Catalog Databricks · est. 2024 · San Francisco, CA
Open-source universal catalog for data and AI under Apache-2.0 — Iceberg-REST and Hive-MS compatible, Databricks-led, LF AI hosted.
OSS · paid tiers Self-host OSS Q C L Catalog & discovery → 03
Browse by capability
Cut the index by feature.
04
Browse by fit
Shortlists and head-to-heads.
Best tools for analytics engineers → Best tools for data engineers → Best tools for platform engineers → Best tools for data stewards → Best tools for data leaders (CDOs) → Best tools for open-source teams → Best tools for self-hosted deployments → All 100 head-to-head comparisons → The state of data observability, 2026 →
05
How tools are categorized
One schema, three cuts.
Each tool is placed in a primary cluster — the problem it was built for — and scored 0–3 against every cluster in the vertical. A tool with a primary cluster of quality testing and a strength of 2 against lineage appears on the quality hub as a primary entry and on the lineage hub as a strong secondary entry.
Categories, scoring rubrics, sourcing, and verification cadence are documented in full on the methodology page.
What this catalog is.
Data Stack Index is a structured reference for data tooling. Every tool is described against the same schema — deployment, pricing, capabilities, integrations, alternatives — so that two tools can be compared on the same fields rather than on incompatible vendor language.
The catalog is free, takes no money from vendors, and lists no tool because the vendor asked. Selection criteria, categorization, sourcing, and update cadence are documented on the methodology and independence pages. The project is built and maintained by one person; the coverage page is honest about what's indexed and what isn't.