GitLab
GitHub
BitBucket
CircleCI
Gitea
Jenkins
Jira
SourceForge
DQOps
DQLabs.ai
Metaplane
Melissa Data Quality
Collibra
Datadog
DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors.
The platform provides an efficient user interface to quickly add data sources, configure data quality checks, and manage issues. DQOps comes with over 150 built-in data quality checks, but you can also design custom checks to detect any business-relevant data quality issues. The platform supports incremental data quality monitoring to support analyzing data quality of very big tables. Track data quality KPI scores using our built-in or custom dashboards to show progress in improving data quality to business sponsors.
DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.
GitLab DQOpsGitLab is well-suited for developers, DevOps engineers, project managers, and teams that require robust CI/CD capabilities, strong security features, and an open-source platform that can be self-hosted or used as a cloud service. It is particularly beneficial for organizations looking for a comprehensive solution to streamline their development workflows.
Based on our record, GitLab seems to be a lot more popular than DQOps. While we know about 144 links to GitLab, we've tracked only 1 mention of DQOps. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We use GitHub here as an example, but there are also other hosts you could explore like GitLab and BitBucket. - Source: dev.to / 2 months ago
Expertise. The SaaS provider is declaring: "I am good at XYZ; I can deliver it better than any of my competitors, and I constantly work to improve how I deliver it." Who do you think can better run GitLab, your already overworked Operations team, or GitLab itself? - Source: dev.to / 4 months ago
Integration Capabilities: How easily does it plug into your daily workflow? Look for deep integrations with your IDE, source control (like GitHub or GitLab), and especially your CI/CD pipeline. - Source: dev.to / 5 months ago
Connect your GitLab account for seamless version control. - Source: dev.to / 7 months ago
Web Check CI stands out because it is the first CI/CD module of its kind available for GitLab! It's built on Google's Baseline initiative, the new standard for web platform compatibility. Instead of guessing which features are safe to use, developers get authoritative answers based on real browser support data. - Source: dev.to / 10 months ago
Open-source power: Check out DQOps, a free and Open-source data quality Platform. It's like having a community of data superheroes watching Your back. - Source: dev.to / over 1 year ago
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
DQLabs.ai - The Modern Data Quality Platform.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Metaplane - Metaplane is the Datadog for Data โ a data observability tool that continuously monitors your data stack, alerts you when something goes wrong, and provides relevant metadata to help you debug.
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
Melissa Data Quality - Melissa helps companies to harness Big Data, legacy data, and people data (names, addresses, phone numbers, and emails).
