Software Alternatives & Reviews

DQLabs.ai VS DQOps

Compare DQLabs.ai VS DQOps and see what are their differences

DQLabs.ai logo DQLabs.ai

The Modern Data Quality Platform.

DQOps logo DQOps

Increase confidence in your data by tracking the data quality
  • DQLabs.ai Landing page
    Landing page //
    2023-05-02

DQLabs.ai is a Modern Data Quality platform enabling organizations to observe, measure and discover the data that matters. The DQLabs platform harnesses the combined power of Data Observability, Data Quality and Data Discovery to enable data producers, consumers, and leaders to turn data into action faster, easier, and more collaboratively.

  • DQOps Checks in DQOps can be quickly edited with intuitive user interface
    Checks in DQOps can be quickly edited with intuitive user interface //
    2024-01-19
  • DQOps DQOps dashboards enable quick identification of tables with data quality issues
    DQOps dashboards enable quick identification of tables with data quality issues //
    2024-01-19
  • DQOps With DQOps, you can conveniently keep track of the issues that arise during data quality monitoring
    With DQOps, you can conveniently keep track of the issues that arise during data quality monitoring //
    2024-01-19
  • DQOps DQOps dashboards simplify monitoring of data quality KPIs
    DQOps dashboards simplify monitoring of data quality KPIs //
    2024-01-19
  • DQOps DQOps enables quick data profiling
    DQOps enables quick data profiling //
    2024-01-19
  • DQOps DQOps supports the most popular data sources
    DQOps supports the most popular data sources //
    2024-01-19

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.

DQOps

Website
dqops.com
$ Details
paid $5000.0 / Annually
Release Date
2020 January

Category Popularity

0-100% (relative to DQLabs.ai and DQOps)
Data Quality
70 70%
30% 30
Analytics
60 60%
40% 40
Data Observability
100 100%
0% 0
Data Management Platform (DMP)

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What are some alternatives?

When comparing DQLabs.ai and DQOps, you can also consider the following products

Collibra - Collibra automates data management processes by providing business-focused applications where collaboration and ease-of-use come first.

Ataccama - We deliver Self-Driving Data Management & Governance with Ataccama ONE. It’s a fully integrated yet modular platform for any data, user, domain, or deployment.

Melissa Data Quality - Melissa helps companies to harness Big Data, legacy data, and people data (names, addresses, phone numbers, and emails).

RingLead - RingLead offers a complete end-to-end suite of products to clean, protect, and enhance company and contact information.

Metaplane - Metaplane is the Datadog for Data — a data observability tool that continuously monitors your data stack, alerts you when something goes wrong, and provides relevant metadata to help you debug.

InfoSphere - IBM InfoSphere Information Server is a market-leading data integration platform which includes a family of products that enable you to understand, cleanse, monitor, transform, and deliver data.