Communications Outsourcing

Customer Success Management Training

Customer Training

Help Desk

Web and Video Conferencing

Customer Support

Functional Testing

Kubernetes Monitoring

Development

Admissions and Enrollment

Alumni Management

Virtual Classroom

Education

Barcode

Business Intelligence (BI)

Collaboration

Intellectual Property (IP) Management

Workflow

Enterprise

Accounting

Crypto Tax

Treasury Management

Finance and Accounting

Applicant Tracking

Corporate Learning Management

Freelance Management

HR Management

On-Demand Payment

Payroll

Resume Parsing

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

Authentication

Cloud Storage

Cybersecurity Consulting

Data Pipeline

Digital Experience Monitoring (DEM)

Disaster Recovery

Fraud Detection

Function as a Service (FaaS)

Identity Management

Integration Platform as a Service (iPaaS)

Managed Public Cloud Infrastructure

Modular Storage Area Network (SAN)

Network Performance Monitoring

SaaS Backup

Sensitive Data Discovery

User Activity Monitoring

Vulnerability Management

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Contact Center

Content Management

Direct Mail Automation

Email Marketing

Marketing Automation

Marketing Resource Management

Referral Marketing

Social Media Management

Survey & Forms Building

Web Analytics

Marketing

Project Management

Transcription

Professional Services

Call Recording

Customer Relationship Management (CRM)

Point of Sale

Sales Coaching

eCommerce Analytics

Sales

Secure Service Edge

Security

Banking

Clinical Trial Management

Financial Services CRM

Geographic Information

Internet of Medical Things

Nonprofit Advocacy

Retail Execution

Vertical-Specific

medium

large

Acceldata is an enterprise data observability platform designed to offer users insights into their data stack to improve data and pipeline reliability, platform performance, and spend efficiency.

Acceldata

Data Observability

Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.

Discover

Business

Dataiku DSS

Data Science

Platform Connectivity

Data Exploration

Data Preparation

Platform Data Modeling

Model Deployment

Connect to Multiple Data Sources

Extend Existing Data Sources

Automatic Data Format Detection

MDM Integration

Visualization

Interactive Data Analysis

Interactive Data Cleaning and Enrichment

Data Transformations

Data Encryption

Built-in Processors

Multiple Model Development Languages and Tools

Automated Machine Learning

Single platform for multiple model development

Self-Service Model Delivery

Flexible Model Publishing Options

Security, Governance, and Cost Controls

Dataiku

Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.

Free

Standard

Infrastructure

Log Management

Datadog

Observability

small

Retrace (formerly APM+) is a lightweight Application Performance Management solution. Retrace gives developers continuous, real-time analysis through a combination of code-level visibility with in-line log and error data. Retrace helps identify top performance offenders by analyzing top page requests, top SQL queries, and top external web services.

Essentials

Retrace

Application monitoring

Database monitoring

Threshold alerts

Application performance management console

Collaboration tools

Out-of-the box templates to monitor applications

Application dependency mapping and thresholding

Virtualization monitoring

Server availability and performance monitoring

Server usage monitoring and capacity forecasting

IT Asset Discovery

Stackify

The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.

Informatica Cloud Data Quality

Data Quality

Data source connectivity

Data profiling

Master data management (MDM) integration

Data element standardization

Match and merge

Address verification

Informatica Cloud Data Quality informatica data explorer

Informatica

Moogsoft is an IT alert management platform from the San Francisco-headquartered company of the same name with an office in the UK... also comprising the original developers of IBM's acquired Netcool technology.

Advanced

Moogsoft

Bigeye Data Observability Platform

Bigeye

Calyptia

Cribl.Cloud

Cribl Inc.

Databand

Kensu

Kensu, Inc.

Metaplane

Soda

Soda Data NV

Telmai

Telm.ai

Google BigQuery

Amazon Redshift

Snowflake

Amazon Athena

Amazon S3 (Simple Storage Service)

Chartio (discontinued)

Apache Hive

Databricks Lakehouse Platform

Mode

Microsoft Teams

PagerDuty

Slack

OpsGenie

Mattermost

Looker

Sisense

Apache Airflow

AWS Glue

Presto

Apache Spark

Prefect

Monte Carlo is a data monitoring and observability platform that helps users to quickly detect issues in their data pipelines. Customers have had positive experiences with Monte Carlo, with many praising the ease of set up and intuitive UI. The product offers features like anomaly detection, data freshness monitoring, Slack notifications, custom alerts, and a GraphQL API. Customers appreciate that it helps detect issues early and proactively identify problems before they cause downstream impacts. With the product impact being positive overall, customers are pleased with the customer success team and responsiveness to feedback from the entire team. Features such as lineage tracking, incident IQ pages for working on data incidents easily, and ML-powered anomaly detection have improved users’ observability and debugging capabilities. Customers found that it helped save resources as well as trust in data systems while offering valuable insight into the infrastructure. Suggestions for improvement include improved UI for bulk operations, more flexible email notification settings, and integration with Teams. Overall, customers find Monte Carlo to be a useful tool that saves time and effort in data monitoring processes.

It enables anomaly detection, which allows users to identify potential problems before they become more serious or costly. Monte Carlo also provides Slack notifications, so users can be alerted immediately of any changes in their data. Additionally, the product offers data freshness monitoring. Customers have found it easy to set up and use with an intuitive UI and responsive development team. The product has helped them become proactive when it comes to resolving anomalies, saving resources in the process. It also provides valuable metadata insights into existing infrastructure and capabilities for improvement. 

Overall, customers find Monte Carlo an invaluable tool for data observability and debugging; however, there are still areas for improvement such as minor UI issues and more alert customization settings. Despite these minor shortcomings, Monte Carlo has been well-received by customers due to the helpful customer success team and responsive product team who are open to suggestions from customers of how the product can be further improved.

Users have found Monte Carlo to be a great asset, providing out-of-the-box anomaly detection and data observability. It has helped improve trust in data and give data consumers and producers a sense of ownership. Slack notifications are easy to understand and link back to incidents within Monte Carlo. Lineage capabilities have also been useful for identifying downstream impacts of any issues. Customers appreciate the product team's responsiveness and openness to suggestions. Despite some minor UI/UX issues, customers find that their return on investment is high when using this product as it helps them become active in resolving data anomalies instead of reactive. They have noted that custom alerts routing and message customization could be improved, but the product is under active development and updates are frequent. Overall, users have had a positive experience with Monte Carlo and would recommend it as an excellent observability tool.

Users find Monte Carlo to be an invaluable tool for detecting data anomalies quickly and easily. Common pros or likes include:

* Out-of-the-box monitoring with minimal configuration needed
* Ability to catch issues and errors faster from constant monitoring of data freshness 
* Excellent collaboration with a product team that is open to feedback and suggestions from customers 

These features make Monte Carlo an attractive choice for users looking for a comprehensive, easy-to-use observability platform. 

Monte Carlo is a data observability platform that many customers appreciate for its ease of use and ability to detect issues quickly. However, there are some common cons or dislikes expressed by users.

* Limited customization of email notifications: Users report wanting more flexibility with setting up email notifications from Monte Carlo.
* Teams integration: Some users wish they could integrate Teams into the product. 
* UI/UX improvements needed: While the UI has become better over time, some customers still suggest ongoing improvements such as better sorting and searching on certain pages.

Monte Carlo headquartered in San Francisco, offers what they present as a data observability engine that is designed to reduce data downtime, increase data reliability, and improve trust in company data and access to it.

TimeXtender was designed to be a holistic solution for data integration that empowers organizations to build data solutions 10x faster using metadata and low-code automation.

Operating Systems	Unspecified
Mobile Application	No

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