End-to-End DataOps Platforms
12 entriesPlatforms that apply agile and DevOps practices across the whole data lifecycle.
01DataKitchenThe DataKitchen DataOps Platform enables cross-functional teams to seamlessly collaborate, quickly innovate, and instantly deliver error-free, on-demand insight.
02IBM DataOpsIBM DataOps solutions integrate automation, governance, and policy-aware intelligence to organize your data so it's trusted and business-ready for AI.
03DataOps.liveA DataOps platform that enhances dbt and CI/CD workflows for data engineering, with governance and collaboration across teams.
04Zaloni ArenaAn end-to-end DataOps platform built on an agile foundation that improves and safeguards your data assets.
05Saagie (now part of Scaleway)A DataOps platform, acquired by Scaleway, that brings together popular technologies so you can deliver and run data projects quickly and reliably.
06DataloopManage, collaborate on, distribute and use your data operations, integrated and managed through a single point of access. The dataloop.ai site did not respond to a link check on 23 October 2026.
07Mozart DataYour all-in-one modern data platform for centralizing, organizing, and analyzing your data. Get set up in an hour, without engineering resources.
08LensesRemoves the human bottlenecks from data projects, decouples business decisions from the infrastructure and makes data more accessible to the right people, with AI-assisted data streaming.
09Hitachi Vantara Unified Data ManagementModular data management portfolio from Hitachi Vantara spanning data integration and analytics; it replaces the older Lumada DataOps listing.
10HighByte Intelligence HubA secure, edge-native DataOps solution purpose-built for industrial data, curating and modeling AI-ready data across the enterprise.
11MachineMetricsA manufacturing operations platform that turns shop-floor data into insights and actions that reduce machine downtime and increase throughput.
12UnravelData platform optimization that helps operations engineers, developers and architects cut the complexity of delivering reliable, cost-efficient data workloads.
Orchestration & Transformation
7 entriesScheduling, workflow and transformation tools for reliable pipelines.
13Apache AirflowA community-built platform to programmatically author, schedule and monitor workflows. Apache Airflow 3.3.2 was released on 17 September 2026, according to PyPI.
14AstronomerA managed platform for running Apache Airflow, to build, run and observe data, ML and AI pipelines at scale.
15DagsterA data orchestrator platform for building, scheduling and monitoring reliable data pipelines, with an emphasis on data assets, lineage and observability. dagster 1.13.26 was released on 9 October 2026, according to PyPI.
16PrefectWorkflow orchestration for data, ML and agents, built on open-source foundations with production-ready platforms. prefect 3.9.0 was released on 21 October 2026, according to PyPI.
17KestraAn open-source orchestration platform that uses a declarative language to build simple, scalable and flexible workflows. v2.0.7 was released on 20 October 2026, according to GitHub.
18dbtWith dbt, data teams work directly within the warehouse to produce trusted datasets for reporting, ML modeling and operational workflows. dbt Labs merged with Fivetran in June 2026. Fivetran and dbt Labs completed their merger in June 2026, according to their press release. dbt-core 1.12.6 was released on 14 October 2026, according to PyPI.
19Databricks LakeflowDatabricks Lakeflow provides ingestion, processing and scheduling that minimises the complexity of building and maintaining pipelines and running ETL workloads on a data lake.
Data Integration & Movement
11 entriesIngestion, ELT, streaming and mastering platforms that feed DataOps pipelines.
20Fivetran (including Census)An automated data movement platform that includes Census's reverse ETL (now Fivetran Activations) for syncing warehouse data into business tools. Fivetran and dbt Labs completed their merger in June 2026.
21AirbyteAn open-source data movement platform that runs ELT pipelines across 700+ connectors to warehouses, lakes, vector databases and AI agents.
22MatillionA unified, cloud-native ELT platform with built-in AI to build data pipelines faster.
23RiveryRivery's SaaS platform provides a fully-managed solution for data ingestion, transformation, orchestration, reverse ETL, and more.
24NexlaNexla learns your schema, tracks its evolution, monitors changes to data characteristics, and manages data flows regardless of format or source type.
25MeltanoAn ETL platform for analytics engineers with 500+ connectors, predictable pricing and full control of pipelines. meltano 4.4.1 was released on 7 October 2026, according to PyPI.
26StriimStriim's self-managed platform offers real-time data integration and streaming for on-premise and cloud environments.
27IBM StreamSetsData integration that assumes change by design, bridging the gap between legacy and modern platforms to speed up digital transformation.
28InformaticaEnterprise cloud data management for integration, quality and governance, now part of Salesforce.
29Qlik Talend CloudData integration and quality with real-time pipelines and 500+ connectors; Talend is now part of Qlik.
30TamrTamr's data mastering platform integrates machine learning with human feedback to break down data silos and continuously clean and deliver accurate data.
Data Quality, Observability & Lineage
9 entriesTesting, monitoring, lineage and governance that keep data trustworthy.
31Monte CarloA data and AI observability platform for enterprise teams that detects data issues before they reach stakeholders.
32Great ExpectationsGX Core is an open-source framework for testing, validating and documenting data quality across modern data pipelines. The project's GitHub repository now sits under the fivetran organization. great-expectations 1.24.1 was released on 22 October 2026, according to PyPI.
33SodaAn automated data quality platform for finding, understanding and fixing data quality issues, from table level down to individual records. soda-core 4.28.0 was released on 20 October 2026, according to PyPI.
34BigeyeA data and AI trust platform for large enterprises that combines data observability, end-to-end lineage and AI governance.
35ElementaryA control plane for data and AI reliability that unifies observability, quality, governance and discovery, with engineers working in code. elementary-data 0.26.1 was released on 11 October 2026, according to PyPI.
36DatafoldDatafold is a data quality platform with diffs, column-level lineage, alerts, and more. No more broken pipelines, models, or dashboards. Datafold's open-source data-diff repository on GitHub is archived.
37lakeFSA control plane for AI-ready data that adds governance and makes AI training and agent runs reproducible. v1.88.0 was released on 22 September 2026, according to GitHub.
38OpenLineageAn open standard for collecting data lineage metadata consistently across data tools. openlineage-python 1.54.0 was released on 12 October 2026, according to PyPI.
39AtlanA metadata and governance platform that gives teams and AI agents the data graph, business logic and governance to act on trusted data.
Related Pages on This Site
7 entriesMore data engineering topics.
40Data Pipeline OrchestrationOrchestrators and managed services such as Airflow, Dagster, Prefect, Kestra and Argo Workflows.
41Data EngineeringHub of data engineering directories.
42Data Integration, ETL and CDC ToolsIntegration, ETL/ELT, CDC and orchestration tools.
43Enterprise Data Catalogs for DataOpsCatalog platforms with metadata management and lineage.
44Data Quality and Testing FrameworksFrameworks for profiling, validating and monitoring data quality.
45Data Observability ToolsTools for monitoring pipeline health and data reliability.
46Data Governance PlatformsGovernance platforms for ownership, access and responsible use.
DataOps Practice
4 entriesPractice.
Related Pages
0 entriesRelated research directories on this site.
Frequently Asked Questions
What is DataOps?
DataOps applies agile, DevOps and statistical quality-control practices to data pipelines, with automation, testing and monitoring so trusted data reaches users faster.
How is DataOps different from DevOps?
DevOps automates software delivery, while DataOps also manages the data itself: its quality, lineage, schema changes and freshness, alongside the code that transforms it.
What are the core DataOps capabilities?
Pipeline orchestration, automated testing and data quality checks, observability and lineage, version control for data and code, and CI/CD for data products.
How do orchestration tools differ?
Airflow is the widely used code-first scheduler, Dagster centres on data assets and lineage, Prefect emphasises flexible Python workflows, and Kestra uses declarative YAML.
What changed with Fivetran and dbt?
Fivetran and dbt Labs have merged, and both vendors' sites now describe themselves as one company, so the dbt and Fivetran entries are cross-referenced.
Which additional references does this page add?
The section 'DataOps Practice' lists DataOps Manifesto, dbt, Great Expectations, OpenLineage, Apache Airflow.
What changed recently in DataOps tooling?
According to PyPI and GitHub in October 2026: Great Expectations 1.24.1 (22 October), Prefect 3.9.0 (21 October), Soda Core 4.28.0 (20 October), Kestra v2.0.7 (20 October), dbt-core 1.12.6 (14 October), OpenLineage 1.54.0 (12 October) and Dagster 1.13.26 (9 October) have recent releases. Datafold's open-source data-diff repository is archived, and the dataloop.ai site did not respond to a link check.