Best Data Engineering Tools for SingleStore
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Compare the Top Data Engineering Tools that integrate with SingleStore as of August 2025
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This a list of Data Engineering tools that integrate with SingleStore. Use the filters on the left to add additional filters for products that have integrations with SingleStore. View the products that work with SingleStore in the table below.
What are Data Engineering Tools for SingleStore?
Data engineering tools are designed to facilitate the process of preparing and managing large datasets for analysis. These tools support tasks like data extraction, transformation, and loading (ETL), allowing engineers to build efficient data pipelines that move and process data from various sources into storage systems. They help ensure data integrity and quality by providing features for validation, cleansing, and monitoring. Data engineering tools also often include capabilities for automation, scalability, and integration with big data platforms. By streamlining complex workflows, they enable organizations to handle large-scale data operations more efficiently and support advanced analytics and machine learning initiatives. Compare and read user reviews of the best Data Engineering tools for SingleStore currently available using the table below. This list is updated regularly.
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Looker
Google
Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time. -
2
DQOps
DQOps
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.Starting Price: $499 per month -
3
Decube
Decube
Decube is a data management platform that helps organizations manage their data observability, data catalog, and data governance needs. It provides end-to-end visibility into data and ensures its accuracy, consistency, and trustworthiness. Decube's platform includes data observability, a data catalog, and data governance components that work together to provide a comprehensive solution. The data observability tools enable real-time monitoring and detection of data incidents, while the data catalog provides a centralized repository for data assets, making it easier to manage and govern data usage and access. The data governance tools provide robust access controls, audit reports, and data lineage tracking to demonstrate compliance with regulatory requirements. Decube's platform is customizable and scalable, making it easy for organizations to tailor it to meet their specific data management needs and manage data across different systems, data sources, and departments.
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