Alternatives to Telmai
Compare Telmai alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Telmai in 2026. Compare features, ratings, user reviews, pricing, and more from Telmai competitors and alternatives in order to make an informed decision for your business.
-
1
DataHub
DataHub
DataHub Cloud is an event-driven AI & Data Context Platform that uses active metadata for real-time visibility across your entire data ecosystem. Unlike traditional data catalogs that provide outdated snapshots, DataHub Cloud instantly propagates changes, automatically enforces policies, and connects every data source across platforms with 100+ pre-built connectors. Built on an open source foundation with a thriving community of 13,000+ members, DataHub gives you unmatched flexibility to customize and extend without vendor lock-in. DataHub Cloud is a modern metadata platform with REST and GraphQL APIs that optimize performance for complex queries, essential for AI-ready data management and ML lifecycle support. -
2
SCIKIQ
SCIKIQ
SCIKIQ is an AI-native Data & Intelligence Platform designed to help enterprises make their data trusted, governed, connected, and ready for AI in weeks rather than years. Recognized by Forrester, NASSCOM League of 10, YourStory Tech30, Inc42, and DataIQ, SCIKIQ supports enterprises across the USA, India, UK, and UAE. SCIKIQ brings together Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products, and AI Agents within one unified platform. Unlike traditional data platforms that often require extensive replatforming or migration, SCIKIQ works with an enterprise’s existing technology ecosystem. Organizations can connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, data warehouses, and enterprise applications through 200+ pre-built connectors, without rip-and-replace. Contextual Intelligence at the Core SCIKIQ goes beyond connecting data by helping AI understand the business context behind it. Its semantic intelligence layer brings together business terminology, KPI definitions, metadata, lineage, ownership, business rules, ontologies, and relationships to create a trusted context layer for enterprise analytics and AI. Business users can ask questions in natural language, investigate KPIs, identify root causes, and generate insights without writing SQL. Data teams gain enterprise-grade capabilities for data integration, quality, governance, lineage, metadata, and control. AI teams gain trusted, contextual enterprise data for building Generative AI applications, copilots, and intelligent AI agents. Why Enterprises Choose SCIKIQ AI-ready in 3–6 weeks | 200+ connectors | 99.9% availability | No-code | Multi-cloud | No vendor lock-in | No replatforming SCIKIQ has production deployments across industries including manufacturing, retail, aviation, logistics, BFSI, healthcare, and other data-intensive enterprises. -
3
Code-Cube.io
Code-Cube.io
Code-Cube.io is the full-stack data collection observability platform that protects your dataLayer, tags and conversion data. It detects tracking issues instantly and provides real-time alerts to prevent data loss and performance drops. The platform eliminates the need for manual QA by continuously auditing tracking implementations across websites and applications. Users gain full visibility into how tags and events behave across both client-side and server-side environments. Code-Cube.io ensures that marketing data remains accurate, enabling better decision-making, preventing wasted ad spend and maximizing campaign performance. -
4
DataBuck
FirstEigen
DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world. -
5
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 -
6
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. -
7
IBM watsonx.data integration is a data integration platform designed to help organizations transform raw data into AI-ready data at scale. The platform enables data teams to build, manage, and optimize data pipelines across multiple environments, including on-premises systems and hybrid or multi-cloud infrastructures. With a unified control plane, watsonx.data integration supports multiple integration styles such as batch processing, real-time streaming, and data replication within a single solution. The platform also offers no-code, low-code, and pro-code development options, allowing both technical and non-technical users to design and manage data pipelines efficiently. By simplifying data integration workflows and reducing reliance on multiple tools, watsonx.data integration helps organizations deliver reliable data for analytics and AI applications.
-
8
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. -
9
Qualdo
Qualdo
We are a leader in Data Quality & ML Model for enterprises adopting a multi-cloud, ML and modern data management ecosystem. Algorithms to track Data Anomalies in Azure, GCP & AWS databases. Measure and monitor data issues from all your cloud database management tools and data silos, using a single, centralized tool. Quality is in the eye of the beholder. Data issues have different implications depending on where you sit in the enterprise. Qualdo is a pioneer in organizing all data quality management issues through the lens of multiple enterprise stakeholders, presenting a unified view in a consumable format. Deploy powerful auto-resolution algorithms to track and isolate critical data issues. Take advantage of robust reports and alerts to manage your enterprise regulatory compliance. -
10
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. -
11
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. -
12
Sift
Sift
Sift is a unified observability platform purpose-built for modern, mission-critical hardware systems that provides engineers with infrastructure and tooling to ingest, store, normalize, and explore high-frequency, high-cardinality telemetry and event data from design, validation, manufacturing, and operations in a single source of truth rather than fragmented dashboards and scripts; it centralizes diverse data types, aligns signals across subsystems, and structures information for fast search, visual review, and traceability so teams can detect anomalies, perform root-cause analysis, automate verification and validation, and debug hardware with real-time precision. It supports automated data review, no-code visualization and querying of massive datasets, continuous anomaly detection, and integration with engineering workflows, including CI/CD pipelines and tooling, while enabling telemetry governance, collaboration, reporting, and knowledge capture across siloed teams. -
13
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. -
14
Datagaps DataOps Suite
Datagaps
Datagaps DataOps Suite is a comprehensive platform designed to automate and streamline data validation processes across the entire data lifecycle. It offers end-to-end testing solutions for ETL (Extract, Transform, Load), data integration, data management, and business intelligence (BI) projects. Key features include automated data validation and cleansing, workflow automation, real-time monitoring and alerts, and advanced BI analytics tools. The suite supports a wide range of data sources, including relational databases, NoSQL databases, cloud platforms, and file-based systems, ensuring seamless integration and scalability. By leveraging AI-powered data quality assessments and customizable test cases, Datagaps DataOps Suite enhances data accuracy, consistency, and reliability, making it an essential tool for organizations aiming to optimize their data operations and achieve faster returns on data investments. -
15
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. -
16
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 -
17
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. -
18
Actian Data Observability
Actian
Actian Data Observability is an AI-powered platform designed to continuously monitor, validate, and manage the health, quality, and reliability of data across modern data environments. It uses automated Data Observability Agents that validate data as it arrives in data lakehouses or warehouses, detecting anomalies, explaining root causes, and coordinating resolution before issues impact dashboards, reports, or AI systems. It provides real-time visibility into data pipelines, ensuring that data remains accurate, complete, and trustworthy throughout its lifecycle. It eliminates blind spots by monitoring 100% of data rather than relying on sampling, allowing organizations to identify hidden errors that could otherwise corrupt analytics or machine learning outcomes. With built-in anomaly detection powered by AI and machine learning, it proactively identifies irregularities such as schema changes, missing data, or unexpected distributions, enabling faster diagnosis and resolution. -
19
SYNQ
SYNQ
SYNQ is a data observability platform that helps modern data teams define, monitor, and manage their data products. It brings together ownership, testing, and incident workflows so teams can stay ahead of issues, reduce data downtime, and deliver trusted data faster. With SYNQ, every critical data product has clear ownership and real-time visibility into its health. When something breaks, the right people are alerted—with the context they need to understand and resolve the issue quickly. At the center of SYNQ is Scout, your autonomous, always-on data quality agent. Scout proactively monitors data products, recommends what and where to test, does root-cause analysis and fixes issues. It connects lineage, issue history, and contextual data to help teams fix problems faster. SYNQ integrates with the tools you already use and is trusted by leading scale-ups and enterprises such as VOI, Avios, Aiven and Ebury.Starting Price: $0 -
20
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. -
21
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. -
22
Masthead
Masthead
See the impact of data issues without running SQL. We analyze your logs and metadata to identify freshness and volume anomalies, schema changes in tables, pipeline errors, and their blast radius effects on your business. Masthead observes every table, process, script, and dashboard in the data warehouse and connected BI tools for anomalies, alerting data teams in real time if any data failures occur. Masthead shows the origin and implications of data anomalies and pipeline errors on data consumers. Masthead maps data issues on lineage, so you can troubleshoot within minutes, not hours. We get a comprehensive view of all processes in GCP without giving access to our data was a game-changer for us. It saved us both time and money. Gain visibility into the cost of each pipeline running in your cloud, regardless of ETL. Masthead also has AI-powered recommendations to help you optimize your models and queries. It takes 15 min to connect Masthead to all assets in your data warehouse.Starting Price: $899 per month -
23
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. -
24
Mozart Data
Mozart Data
Mozart Data is the all-in-one modern data platform that makes it easy to consolidate, organize, and analyze data. Start making data-driven decisions by setting up a modern data stack in an hour - no engineering required. -
25
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. -
26
Matia
Matia
Matia is a unified DataOps platform designed to simplify modern data management by combining multiple core functions into a single, integrated system. It brings together ETL, reverse ETL, data observability, and a data catalog, eliminating the need for multiple disconnected tools and reducing the complexity of managing fragmented data stacks. It enables teams to move data quickly and reliably from various sources into data warehouses using advanced ingestion capabilities, including real-time updates and error handling, while also allowing them to push trusted data back into operational tools for business use. Matia emphasizes built-in observability at every stage of the data pipeline, providing monitoring, anomaly detection, and automated quality checks to ensure data accuracy and reliability before issues impact downstream systems. -
27
Integrate.io
Integrate.io
Unify Your Data Stack: Experience the first no-code data pipeline platform and power enlightened decision making. Integrate.io is the only complete set of data solutions & connectors for easy building and managing of clean, secure data pipelines. Increase your data team's output with all of the simple, powerful tools & connectors you’ll ever need in one no-code data integration platform. Empower any size team to consistently deliver projects on-time & under budget. We ensure your success by partnering with you to truly understand your needs & desired outcomes. Our only goal is to help you overachieve yours. Integrate.io's Platform includes: -No-Code ETL & Reverse ETL: Drag & drop no-code data pipelines with 220+ out-of-the-box data transformations -Easy ELT & CDC :The Fastest Data Replication On The Market -Automated API Generation: Build Automated, Secure APIs in Minutes - Data Warehouse Monitoring: Finally Understand Your Warehouse Spend - FREE Data Observability: Custom -
28
MetricSign
MetricSign
MetricSign monitors your entire data stack and detects incidents before your stakeholders do. Connect Power BI via Microsoft OAuth in 2 minutes. MetricSign immediately starts detecting refresh failures, slow datasets, and missed schedules — classifying each with the exact error code and a root cause hint. Beyond Power BI, MetricSign monitors Azure Data Factory, Databricks, dbt Cloud, dbt Core, and Microsoft Fabric. When an ADF pipeline fails and cascades into a Power BI refresh failure, you get one incident — not five separate alerts from five different tools. Key capabilities: - Refresh failure detection with 98+ error code classifications - End-to-end lineage: source → pipeline → dataset → report - Slow refresh and missed schedule detection - Alerts via email, Telegram, webhook - Free plan available — no credit card requiredStarting Price: 69€/3 workspaces -
29
Bigeye
Bigeye
Bigeye is the data observability platform that helps teams measure, improve, and communicate data quality clearly at any scale. Every time a data quality issue causes an outage, the business loses trust in the data. Bigeye helps rebuild trust, starting with monitoring. Find missing and busted reporting data before executives see it in a dashboard. Get warned about issues in training data before models get retrained on it. Fix that uncomfortable feeling that most of the data is mostly right, most of the time. Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data. Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestrators go down. Find out about changes to event names, region codes, product types, and other categorical data. Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected. -
30
Observo AI
Observo AI
Observo AI is an AI-native data pipeline platform designed to address the challenges of managing vast amounts of telemetry data in security and DevOps operations. By leveraging machine learning and agentic AI, Observo AI automates data optimization, enabling enterprises to process AI-generated data more efficiently, securely, and cost-effectively. It reduces data processing costs by over 50% and accelerates incident response times by more than 40%. Observo AI's features include intelligent data deduplication and compression, real-time anomaly detection, and dynamic data routing to appropriate storage or analysis tools. It also enriches data streams with contextual information to enhance threat detection accuracy while minimizing false positives. Observo AI offers a searchable cloud data lake for efficient data storage and retrieval. -
31
Axoflow
Axoflow
Axoflow, the Security Data Layer is the foundation for your SIEM and analytics tools enabling the use of AI, up to 70% faster investigations, and more than 50% reduction in SIEM spend by feeding them with actionable data. Axoflow Platform is built up of the following parts: A pipeline acting as the transportation layer for your security data and also acting as an automated ‘translator’ between data schemas. AI - If you prefer to run your detection content locally - whether it’s an AI or ML model, a threat intel lookup, or another type of enrichment - we’ve got you covered. Storage solutions to facilitate the cost-effective storage of security data and also acting as local storage to run your decentralized detection. Orchestration to weave all of the parts together in an easy-to-use GUI that lets youmonitor and manage, and control and search your data. -
32
Kensu
Kensu
Kensu monitors the end-to-end quality of data usage in real time so your team can easily prevent data incidents. It is more important to understand what you do with your data than the data itself. Analyze data quality and lineage through a single comprehensive view. Get real-time insights about data usage across all your systems, projects, and applications. Monitor data flow instead of the ever-increasing number of repositories. Share lineages, schemas and quality info with catalogs, glossaries, and incident management systems. At a glance, find the root causes of complex data issues to prevent any "datastrophes" from propagating. Generate notifications about specific data events and their context. Understand how data has been collected, copied and modified by any application. Detect anomalies based on historical data information. Leverage lineage and historical data information to find the initial cause. -
33
Digna
digna GmbH
digna is a data quality and observability platform designed to monitor, analyze, and validate data directly within enterprise data environments. It combines anomaly detection, time-series analytics, and validation into a unified system that helps teams detect issues early and understand how data behaves over time. Core Capabilities * Data Anomaly Detection Identifies changes in data volume, distribution, and behavior using statistical methods and AI-driven models without relying on manually defined rules. * Time-Series Analytics Built-in analytical methods (regression, pattern detection, seasonality analysis) allow users to interpret trends and deviations directly within the platform. * Data Timeliness Monitoring Tracks expected data arrival times and identifies delays across pipelines and data flows. * Data Validation Supports rule-based validation with reusable templates and centralized definitions of allowed values. * Schema Change Tracking Detects structural changes in dat -
34
Collate
Collate
Collate is an AI‑driven metadata platform that empowers data teams with automated discovery, observability, quality, and governance through agent‑based workflows. Built on the open source OpenMetadata foundation and a unified metadata graph, it offers 90+ turnkey connectors to ingest metadata from databases, data warehouses, BI tools, and pipelines, delivering in‑depth column‑level lineage, data profiling, and no‑code quality tests. Its AI agents automate data discovery, permission‑aware querying, alerting, and incident‑management workflows at scale, while real‑time dashboards, interactive analyses, and a collaborative business glossary enable both technical and non‑technical users to steward high‑quality data assets. Continuous monitoring and governance automations enforce compliance with standards such as GDPR and CCPA, reducing mean time to resolution for data issues and lowering total cost of ownership.Starting Price: Free -
35
Rupert
Rupert
With Rupert's no-code custom alerts, find the actionable opportunities, anomalies, or exceptions you care about and push them directly to Slack. Unlock value from your data warehouse or BI dashboards with Rupert's flexible, no-code monitoring & alerting. Set up monitoring for any metric or event in minutes. Use dynamic thresholds and combine multiple rules to build more valuable alerts. Add breakdowns and filters to scope alerts to the right granularity or cut of data. Choose period over period comparisons, moving averages, anomaly detection and more from our no-code trigger library. Give recipients complete context on alerts by inserting any data from your warehouse, beyond the monitored metric or event Embed programmable actions buttons into alerts. Build any custom URL or use native Jira & Salesforce integrations.Starting Price: $199 per month -
36
MatchX
VE3 Global
MatchX is an AI-powered data quality and matching platform that cleans, connects, and governs your data — without the manual struggle. It finds and fixes duplicates, inconsistencies, missing fields, and mismatches across systems, even in complex, unstructured sources like scanned documents. The result? You get clean, connected, and trusted data — ready for AI, analytics, automation, and everyday business decisions. MatchX offers a comprehensive AI-enhanced data quality and matching solution that revolutionizes how companies manage their information assets. By integrating powerful data ingestion capabilities and intelligent schema mapping, MatchX structures and validates data from diverse sources, including APIs, databases, and documents. The platform’s self-learning AI models automatically detect and correct inconsistencies, duplicates, and anomalies, ensuring data integrity without intensive manual intervention. -
37
LotusEye
LotusEye
LotusEye is a cloud-based AI anomaly detection service that automatically learns normal behavior from uploaded numerical or sensor data in CSV format and continuously calculates anomaly scores to flag deviations that may indicate faults or unexpected activity, providing alerts and visual insights without requiring users to have expertise in machine learning. It supports both wide-format CSV files, where each row represents sensor values at a timestamp, and long-format CSV with timestamp, sensor name, and value columns, and lets users upload data via drag-and-drop or through an API for scheduled automated processing. After training an AI model with normal operation data, users can upload test data to see calculated anomaly scores and review them in dashboards with time-series graphs, threshold indicators, and filters, helping teams spot unusual patterns and investigate potential issues quickly.Starting Price: $13 per month -
38
Intelligent Threat Detection. Faster Response. 98% of all threats start with Active Directory and nearly always involve the compromise of data stored on enterprise data stores. Our unique combination of detailed auditing, anomaly detection, real time alerting, and real time data discovery and classification allows you to identify, prioritize and investigate threats - fast. Protect Sensitive Data from Rogue Users and Compromised User Accounts. We enable you to detect and investigate threats to your most sensitive data in ways no other vendor can. Bringing together data discovery and classification with threat detection enables you to investigate all events, changes, actions and anomalies with context. End to end visibility of Active Directory, Group Policy, File Servers, Office 365, NetApp, SharePoint, Box, Dropbox and more. Detect and Respond to Security Threats 10x Faster. Investigate threats as they emerge in Active Directory and track movement
-
39
Orchestra
Orchestra
Orchestra is a Unified Control Plane for Data and AI Operations, designed to help data teams build, deploy, and monitor workflows with ease. It offers a declarative framework that combines code and GUI, allowing users to implement workflows 10x faster and reduce maintenance time by 50%. With real-time metadata aggregation, Orchestra provides full-stack data observability, enabling proactive alerting and rapid recovery from pipeline failures. It integrates seamlessly with tools like dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and more, ensuring compatibility with existing data stacks. Orchestra's modular architecture supports AWS, Azure, and GCP, making it a versatile solution for enterprises and scale-ups aiming to streamline their data operations and build trust in their AI initiatives. -
40
VictoriaMetrics Anomaly Detection
VictoriaMetrics
VictoriaMetrics Anomaly Detection is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real time. It does so by utilizing user-configurable machine learning models. In the dynamic and complex world of system monitoring, VictoriaMetrics Anomaly Detection, a part of our Enterprise offering, is a pivotal tool for achieving advanced observability. It empowers SREs and DevOps teams by automating the intricate task of identifying abnormal behavior in time-series data. It goes beyond traditional threshold-based alerting, utilizing machine learning techniques to detect anomalies and minimize false positives, thus reducing alert fatigue. Providing simplified alerting mechanisms atop unified anomaly scores enables teams to spot and address potential issues faster, ensuring system reliability and operational efficiency. -
41
DQ on Demand
DQ Global
Native to Azure, DQ on Demand™ is architected to provide incredible performance and scalability. Switch data providers with ease and enhance your customer data on a pay-as-you-go basis by plugging straight into our DQ on Demand™ web services, providing you with an easy-to-access data quality marketplace. Many data services are available including data cleansing, enrichment, formatting, validation, verification, data transformations, and many more. Simply connect to our web-based APIs. Switch data providers with ease, giving you ultimate flexibility. Benefit from complete developer documentation. Only pay for what you use. Purchase credits and apply them to whatever service you require. Easy to set up and use. Expose all of our DQ on Demand™ functions right within Excel for a familiar, easy-to-use low-code no-code solution. Ensure your data is cleansed right within MS Dynamics with our DQ PCF controls. -
42
Soda
Soda
Soda drives your data operations by identifying data issues, alerting the right people, and helping teams diagnose and resolve root causes. With automated and self-serve data monitoring capabilities, no data—or people—are ever left in the dark. Get ahead of data issues quickly by delivering full observability through easy instrumentation across your data workloads. Empower data teams to discover data issues that automation will miss. Self-service capabilities deliver the broad coverage that data monitoring needs. Alert the right people at the right time to help teams across the business diagnose, prioritize, and fix data issues. With Soda, your data never leaves your private cloud. Soda monitors data at the source and only stores metadata in your cloud. -
43
definity
definity
Monitor and control everything your data pipelines do with zero code changes. Monitor data and pipelines in motion to proactively prevent downtime and quickly root cause issues. Optimize pipeline runs and job performance to save costs and keep SLAs. Accelerate code deployments and platform upgrades while maintaining reliability and performance. Data & performance checks in line with pipeline runs. Checks on input data, before pipelines even run. Automatic preemption of runs. definity takes away the effort to build deep end-to-end coverage, so you are protected at every step, across every dimension. definity shifts observability to post-production to achieve ubiquity, increase coverage, and reduce manual effort. definity agents automatically run with every pipeline, with zero footprints. Unified view of data, pipelines, infra, lineage, and code for every data asset. Detect in run-time and avoid async checks. Auto-preempt runs, even on inputs. -
44
iceDQ
iceDQ
iceDQ is the #1 data reliability platform offering powerful, unified capabilities for Data Testing, Data Monitoring, and Data Observability. Designed for modern data environments, iceDQ automates complex data pipelines and data migration testing to ensure accuracy, integrity, and trust in your data systems. Its AI-based observability engine continuously monitors data in real-time, quickly detecting anomalies and minimizing business risks. With robust cross-platform connectivity, iceDQ supports seamless data validation, data profiling, and data reconciliation across diverse sources — including databases, files, data lakes, SaaS applications, and cloud environments. Whether you're migrating data, ensuring ETL/ELT process quality, or monitoring live data streams, iceDQ helps enterprises deliver high-quality, reliable data at scale. From financial services to healthcare and beyond, organizations rely on iceDQ to make confident, data-driven decisions backed by trusted data pipelines.Starting Price: $1000 -
45
Revefi Data Operations Cloud
Revefi
Your zero-touch copilot for data quality, spending, performance, and usage. Your data team won’t be the last to know about broken analytics or bottlenecks. We pull out anomalies and alert you right away. Improve your data quality and eliminate downtimes. When performance trends the wrong way, you’ll be the first to know. We help you connect the dots between data usage and resource allocation. Reduce and optimize costs, and allocate resources effectively. We slice and dice your spending areas by warehouse, user, and query. When spending trends the wrong way, you get a notification. Get insights on underutilized data and its impact on your business value. Revefi constantly watches out for waste and surfaces opportunities for you to better rationalize usage with resources. Say goodbye to manual data checks with automated monitoring built on your data warehouse. You can find the root cause and solve issues within minutes before they affect your downstream users.Starting Price: $299 per month -
46
datuum.ai
Datuum
AI-powered data integration tool that helps streamline the process of customer data onboarding. It allows for easy and fast automated data integration from various sources without coding, reducing preparation time to just a few minutes. With Datuum, organizations can efficiently extract, ingest, transform, migrate, and establish a single source of truth for their data, while integrating it into their existing data storage. Datuum is a no-code product and can reduce up to 80% of the time spent on data-related tasks, freeing up time for organizations to focus on generating insights and improving the customer experience. With over 40 years of experience in data management and operations, we at Datuum have incorporated our expertise into the core of our product, addressing the key challenges faced by data engineers and managers and ensuring that the platform is user-friendly, even for non-technical specialists. -
47
Data Quality Sense
Tucario
Data Quality Sense (DQS) is a 100% Salesforce-native data quality app by Tucario. It measures, monitors, and improves the reliability of your CRM data without ever exporting it — everything runs inside your Salesforce org. DQS scores your data across six dimensions — Completeness, Validity, Uniqueness, Consistency, Timeliness, and PII Detection — producing a weighted Data Quality Score at the org, object, and field level. A no-code Definition Builder (5-step wizard) lets admins define rules, scheduled scans keep scores current, and Insight Studio surfaces trends and field health. Automatic PII detection (8 pattern types incl. SSN, credit card, IBAN, email, IP, date of birth) helps teams find and protect sensitive data before exposure. With Agentforce and AI on the rise, DQS prepares your Salesforce data for reliable AI — an AI agent is only as good as the data behind it. Available on the Salesforce AppExchange.Starting Price: $1000 -
48
Data Quality Validator (DQV)
Kumaran Systems
DQV is Kumaran Systems' data quality and testing platform for teams who move, mask, or validate large volumes of data. It compares source and target datasets field by field, flags drift, and generates a mismatch report instead of manual spreadsheet checks. It covers five areas: field-level comparison with drift detection, migration mapping between schemas, deterministic PII masking, record- and table-level validation with on-the-fly correction, and synthetic data generation for teams without production data to test against. It connects to SQL Server, Oracle, MySQL, PostgreSQL, AWS, Azure, GCP, flat files, JSON, XML, and REST APIs, and plugs into Informatica, Databricks, and CI/CD pipelines, or runs standalone as a library or CLI tool. In production, DQV has validated 26.6 million bank records in under 22 minutes. A free trial is available, alongside individual, enterprise, and on-premises licensing. -
49
VirtualMetric
VirtualMetric
VirtualMetric is a powerful telemetry pipeline solution designed to enhance data collection, processing, and security monitoring across enterprise environments. Its core offering, DataStream, automatically collects and transforms security logs from a wide range of systems such as Windows, Linux, MacOS, and Unix, enriching data for further analysis. By reducing data volume and filtering out non-meaningful logs, VirtualMetric helps businesses lower SIEM ingestion costs, increase operational efficiency, and improve threat detection accuracy. The platform’s scalable architecture, with features like zero data loss and long-term compliance storage, ensures that businesses can maintain high security standards while optimizing performance.Starting Price: Free -
50
Segwise
Segwise
Automatically tracks and monitors every data point in your MMP every day. You'll receive daily alerts on campaigns and creatives that are impacting your ROAS or behaving unexpectedly. Monitors campaign and creative metrics and sends alerts when it breaches expected thresholds. No matter where your data is stored, Segwise offers seamless, no-code integration with all data sources. Key features include anomaly detection, alerting, and cost-per-custom-event monitoring, providing a comprehensive view of campaign performance. Segwise also monitors the impact of product and LiveOps changes, such as new app versions, experiments, and offers, delivering a 360° perspective on revenue and retention metrics. Users can start with a 14-day free trial, which does not require a credit card or engineering resources, and get up and running in just two minutes. The platform integrates seamlessly with various data sources, offering a no-code solution that requires no engineering effort.
