Best Data Quality Software for Amazon Redshift
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Compare the Top Data Quality Software that integrates with Amazon Redshift as of July 2025
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This a list of Data Quality software that integrates with Amazon Redshift. Use the filters on the left to add additional filters for products that have integrations with Amazon Redshift. View the products that work with Amazon Redshift in the table below.
What is Data Quality Software for Amazon Redshift?
Data quality software helps organizations ensure that their data is accurate, consistent, complete, and reliable. These tools provide functionalities for data profiling, cleansing, validation, and enrichment, helping businesses identify and correct errors, duplicates, or inconsistencies in their datasets. Data quality software often includes features like automated data correction, real-time monitoring, and data governance to maintain high-quality data standards. It plays a critical role in ensuring that data is suitable for analysis, reporting, decision-making, and compliance purposes, particularly in industries that rely on data-driven insights. Compare and read user reviews of the best Data Quality software for Amazon Redshift currently available using the table below. This list is updated regularly.
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1
Satori
Satori
Satori is a Data Security Platform (DSP) that enables self-service data and analytics. Unlike the traditional manual data access process, with Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. Satori’s DSP dynamically applies the appropriate security and access policies, and the users get secure data access in seconds instead of weeks. Satori’s comprehensive DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously discovers sensitive data across data stores and dynamically tracks data usage while applying relevant security policies. Satori enables data teams to scale effective data usage across the organization while meeting all data security and compliance requirements. -
2
Zuar Runner
Zuar, Inc.
Utilizing the data that's spread across your organization shouldn't be so difficult! With Zuar Runner you can automate the flow of data from hundreds of potential sources into a single destination. Collect, transform, model, warehouse, report, monitor and distribute: it's all managed by Zuar Runner. Pull data from Amazon/AWS products, Google products, Microsoft products, Avionte, Backblaze, BioTrackTHC, Box, Centro, Citrix, Coupa, DigitalOcean, Dropbox, CSV, Eventbrite, Facebook Ads, FTP, Firebase, Fullstory, GitHub, Hadoop, Hubic, Hubspot, IMAP, Jenzabar, Jira, JSON, Koofr, LeafLogix, Mailchimp, MariaDB, Marketo, MEGA, Metrc, OneDrive, MongoDB, MySQL, Netsuite, OpenDrive, Oracle, Paycom, pCloud, Pipedrive, PostgreSQL, put.io, Quickbooks, RingCentral, Salesforce, Seafile, Shopify, Skybox, Snowflake, Sugar CRM, SugarSync, Tableau, Tamarac, Tardigrade, Treez, Wurk, XML Tables, Yandex Disk, Zendesk, Zoho, and more! -
3
QuerySurge
RTTS
QuerySurge leverages AI to automate the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Apps/ERPs with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Hadoop & NoSQL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise App/ERP Testing QuerySurge Features - Projects: Multi-project support - AI: automatically create datas validation tests based on data mappings - Smart Query Wizards: Create tests visually, without writing SQL - Data Quality at Speed: Automate the launch, execution, comparison & see results quickly - Test across 200+ platforms: Data Warehouses, Hadoop & NoSQL lakes, databases, flat files, XML, JSON, BI Reports - DevOps for Data & Continuous Testing: RESTful API with 60+ calls & integration with all mainstream solutions - Data Analytics & Data Intelligence: Analytics dashboard & reports -
4
Syncari
Syncari
Syncari, a leader in data unification and automation, is modernizing enterprise master data with its innovative Autonomous Data Management platform. Syncari is revolutionizing how enterprises handle data by ensuring comprehensive accuracy, centralized governance, and democratized access. This approach facilitates near real-time decision-making and AI integration, enhancing observability and operations across multiple domains. By accelerating the speed to business impact, Syncari enhances decision-making capabilities and empowers organizations to fully leverage their data for substantial value extraction. Syncari ADM is one cohesive platform to sync, unify, govern, enhance, and access data across your enterprise. Experience continuous unification, data quality, distribution, programmable MDM, and distributed 360°. -
5
Sifflet
Sifflet
Automatically cover thousands of tables with ML-based anomaly detection and 50+ custom metrics. Comprehensive data and metadata monitoring. Exhaustive mapping of all dependencies between assets, from ingestion to BI. Enhanced productivity and collaboration between data engineers and data consumers. Sifflet seamlessly integrates into your data sources and preferred tools and can run on AWS, Google Cloud Platform, and Microsoft Azure. Keep an eye on the health of your data and alert the team when quality criteria aren’t met. Set up in a few clicks the fundamental coverage of all your tables. Configure the frequency of runs, their criticality, and even customized notifications at the same time. Leverage ML-based rules to detect any anomaly in your data. No need for an initial configuration. A unique model for each rule learns from historical data and from user feedback. Complement the automated rules with a library of 50+ templates that can be applied to any asset. -
6
Immuta
Immuta
Immuta is the market leader in secure Data Access, providing data teams one universal platform to control access to analytical data sets in the cloud. Only Immuta can automate access to data by discovering, securing, and monitoring data. Data-driven organizations around the world trust Immuta to speed time to data, safely share more data with more users, and mitigate the risk of data leaks and breaches. Founded in 2015, Immuta is headquartered in Boston, MA. Immuta is the fastest way for algorithm-driven enterprises to accelerate the development and control of machine learning and advanced analytics. The company's hyperscale data management platform provides data scientists with rapid, personalized data access to dramatically improve the creation, deployment and auditability of machine learning and AI. -
7
Coginiti
Coginiti
Coginiti, the AI-enabled enterprise data workspace, empowers everyone to get consistent answers fast to any business question. Accelerating the analytic development lifecycle from development to certification, Coginiti makes it easy for you to search and find approved metrics for your use case. Coginiti integrates all the functionality you need to build, approve, version, and curate analytics across all business domains for reuse, all while adhering to your data governance policy and standards. Data and analytic teams in the insurance, financial services, healthcare, and retail/consumer package goods industries trust Coginiti’s collaborative data workspace to deliver value to their customers.Starting Price: $189/user/year -
8
JuxtAPPose
Juxtappose
The Data Comparison Tool. Compare data from files (Excel, csv and txt) and Queries (MS-SQL, Oracle, Amazon Redshift, MySQL, and more...) Comparing data from files and queries has never been easier. Don't drown under hours of tutorials, spreadsheets and formulas that will be good for only ONE time, let the clicks do the work and compare A and B without learning how to code! If any of these situations prevents you to spend your time on things that require your actual talent, then this is the software for you (disclaimer, reading the list can cause pain): Reports migration, data differences between stages, data mismatch, "Row count match but numbers don't","this query works different in this other Engine/DB", "001 <> 1" (or vice versa), find missing data, "that report was different X days ago", "I have to compare this again", etc.Starting Price: $49.99 one-time payment -
9
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 -
10
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. -
11
Ataccama ONE
Ataccama
Ataccama reinvents the way data is managed to create value on an enterprise scale. Unifying Data Governance, Data Quality, and Master Data Management into a single, AI-powered fabric across hybrid and Cloud environments, Ataccama gives your business and data teams the ability to innovate with unprecedented speed while maintaining trust, security, and governance of your data. -
12
ThinkData Works
ThinkData Works
Data is the backbone of effective decision-making. However, employees spend more time managing it than using it. ThinkData Works provides a robust catalog platform for discovering, managing, and sharing data from both internal and external sources. Enrichment solutions combine partner data with your existing datasets to produce uniquely valuable assets that can be shared across your entire organization. Unlock the value of your data investment by making data teams more efficient, improving project outcomes, replacing multiple existing tech solutions, and providing you with a competitive advantage. -
13
Anomalo
Anomalo
Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear in your data and before anyone else is impacted. Detect, root-cause, and resolve issues quickly – allowing everyone to feel confident in the data driving your business. Connect Anomalo to your Enterprise Data Warehouse and begin monitoring the tables you care about within minutes. Our advanced machine learning will automatically learn the historical structure and patterns of your data, allowing us to alert you to many issues without the need to create rules or set thresholds. You can also fine-tune and direct our monitoring in a couple of clicks via Anomalo’s No Code UI. Detecting an issue is not enough. Anomalo’s alerts offer rich visualizations and statistical summaries of what’s happening to allow you to quickly understand the magnitude and implications of the problem. -
14
Metaplane
Metaplane
Monitor your entire warehouse in 30 minutes. Identify downstream impact with automated warehouse-to-BI lineage. Trust takes seconds to lose and months to regain. Gain peace of mind with observability built for the modern data era. Code-based tests take hours to write and maintain, so it's hard to achieve the coverage you need. In Metaplane, you can add hundreds of tests within minutes. We support foundational tests (e.g. row counts, freshness, and schema drift), more complex tests (distribution drift, nullness shifts, enum changes), custom SQL, and everything in between. Manual thresholds take a long time to set and quickly go stale as your data changes. Our anomaly detection models learn from historical metadata to automatically detect outliers. Monitor what matters, all while accounting for seasonality, trends, and feedback from your team to minimize alert fatigue. Of course, you can override with manual thresholds, too.Starting Price: $825 per month -
15
Telmai
Telmai
A low-code no-code approach to data quality. SaaS for flexibility, affordability, ease of integration, and efficient support. High standards of encryption, identity management, role-based access control, data governance, and compliance standards. Advanced ML models for detecting row-value data anomalies. Models will evolve and adapt to users' business and data needs. Add any number of data sources, records, and attributes. Well-equipped for unpredictable volume spikes. Support batch and streaming processing. Data is constantly monitored to provide real-time notifications, with zero impact on pipeline performance. Seamless boarding, integration, and investigation experience. Telmai is a platform for the Data Teams to proactively detect and investigate anomalies in real time. A no-code on-boarding. Connect to your data source and specify alerting channels. Telmai will automatically learn from data and alert you when there are unexpected drifts. -
16
Lightup
Lightup
Empower enterprise data teams to proactively prevent costly outages, before they occur. Quickly scale data quality checks across enterprise data pipelines with efficient time-bound pushdown queries — without compromising performance. Proactively monitor and identify data anomalies, leveraging prebuilt DQ-specific AI models — without manual threshold setting. Lightup’s out-of-the-box solution gives you the highest level of data health so you can make confident business decisions. Arm stakeholders with data quality intelligence for confident decision-making. Powerful, flexible dashboards provide transparency into data quality and trends. Avoid data silos by using Lightup’s built-in connectors to seamlessly connect to any data source in your data stack. Streamline workflows by replacing manual, resource-intensive processes with automated and accurate data quality checks. -
17
Foundational
Foundational
Identify code and optimization issues in real-time, prevent data incidents pre-deploy, and govern data-impacting code changes end to end—from the operational database to the user-facing dashboard. Automated, column-level data lineage, from the operational database all the way to the reporting layer, ensures every dependency is analyzed. Foundational automates data contract enforcement by analyzing every repository from upstream to downstream, directly from source code. Use Foundational to proactively identify code and data issues, find and prevent issues, and create controls and guardrails. Foundational can be set up in minutes with no code changes required. -
18
DataTrust
RightData
DataTrust is built to accelerate test cycles and reduce the cost of delivery by enabling continuous integration and continuous deployment (CI/CD) of data. It’s everything you need for data observability, data validation, and data reconciliation at a massive scale, code-free, and easy to use. Perform comparisons, and validations, and do reconciliation with re-usable scenarios. Automate the testing process and get alerted when issues arise. Interactive executive reports with quality dimension insights. Personalized drill-down reports with filters. Compare row counts at the schema level for multiple tables. Perform checksum data comparisons for multiple tables. Rapid generation of business rules using ML. Flexibility to accept, modify, or discard rules as needed. Reconciling data across multiple sources. DataTrust solutions offers the full set of applications to analyze source and target datasets. -
19
IBM Databand
IBM
Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems. -
20
Acceldata
Acceldata
Acceldata is an Agentic Data Management company helping enterprises manage complex data systems with AI-powered automation. Its unified platform brings together data quality, governance, lineage, and infrastructure monitoring to deliver trusted, actionable insights across the business. Acceldata’s Agentic Data Management platform uses intelligent AI agents to detect, understand, and resolve data issues in real time. Designed for modern data environments, it replaces fragmented tools with a self-learning system that ensures data is accurate, governed, and ready for AI and analytics. -
21
Datafold
Datafold
Prevent data outages by identifying and fixing data quality issues before they get into production. Go from 0 to 100% test coverage of your data pipelines in a day. Know the impact of each code change with automatic regression testing across billions of rows. Automate change management, improve data literacy, achieve compliance, and reduce incident response time. Don’t let data incidents take you by surprise. Be the first one to know with automated anomaly detection. Datafold’s easily adjustable ML model adapts to seasonality and trend patterns in your data to construct dynamic thresholds. Save hours spent on trying to understand data. Use the Data Catalog to find relevant datasets, fields, and explore distributions easily with an intuitive UI. Get interactive full-text search, data profiling, and consolidation of metadata in one place. -
22
Great Expectations
Great Expectations
Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. We recommend deploying within a virtual environment. If you’re not familiar with pip, virtual environments, notebooks, or git, you may want to check out the Supporting. There are many amazing companies using great expectations these days. Check out some of our case studies with companies that we've worked closely with to understand how they are using great expectations in their data stack. Great expectations cloud is a fully managed SaaS offering. We're taking on new private alpha members for great expectations cloud, a fully managed SaaS offering. Alpha members get first access to new features and input to the roadmap. -
23
rudol
rudol
Unify your data catalog, reduce communication overhead and enable quality control to any member of your company, all without deploying or installing anything. rudol is a data quality platform that helps companies understand all their data sources, no matter where they come from; reduces excessive communication in reporting processes or urgencies; and enables data quality diagnosing and issue prevention to all the company, through easy steps With rudol, each organization is able to add data sources from a growing list of providers and BI tools with a standardized structure, including MySQL, PostgreSQL, Airflow, Redshift, Snowflake, Kafka, S3*, BigQuery*, MongoDB*, Tableau*, PowerBI*, Looker* (* in development). So, regardless of where it’s coming from, people can understand where and how the data is stored, read and collaborate with its documentation, or easily contact data owners using our integrations.Starting Price: $0 -
24
Qualytics
Qualytics
Helping enterprises proactively manage their full data quality lifecycle through contextual data quality checks, anomaly detection and remediation. Expose anomalies and metadata to help teams take corrective actions. Automatically trigger remediation workflows to resolve errors quickly and efficiently. Maintain high data quality and prevent errors from affecting business decisions. The SLA chart provides an overview of SLA, including the total number of SLA monitoring that have been performed and any violations that have occurred. This chart can help you identify areas of your data that may require further investigation or improvement. -
25
Aggua
Aggua
Aggua is a data fabric augmented AI platform that enables data and business teams Access to their data, creating Trust and giving practical Data Insights, for a more holistic, data-centric decision-making. Instead of wondering what is going on underneath the hood of your organization's data stack, become immediately informed with a few clicks. Get access to data cost insights, data lineage and documentation without needing to take time out of your data engineer's workday. Instead of spending a lot of time tracing what a data type change will break in your data pipelines, tables and infrastructure, with automated lineage, your data architects and engineers can spend less time manually going through logs and DAGs and more time actually making the changes to infrastructure. -
26
Validio
Validio
See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only. -
27
Cleanlab
Cleanlab
Cleanlab Studio handles the entire data quality and data-centric AI pipeline in a single framework for analytics and machine learning tasks. Automated pipeline does all ML for you: data preprocessing, foundation model fine-tuning, hyperparameter tuning, and model selection. ML models are used to diagnose data issues, and then can be re-trained on your corrected dataset with one click. Explore the entire heatmap of suggested corrections for all classes in your dataset. Cleanlab Studio provides all of this information and more for free as soon as you upload your dataset. Cleanlab Studio comes pre-loaded with several demo datasets and projects, so you can check those out in your account after signing in.
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