# Bigeye vs Monte Carlo Comparison
---
## AI Generated Summary
- **G2 reviewers report** that Monte Carlo excels in user experience, particularly highlighting its **intuitive setup** and **automated monitoring** features. Users appreciate how quickly insights into data can be accessed, with one reviewer noting that the integration process was a breeze, aided by helpful guidance from the Monte Carlo team.
- **Users say** that Bigeye offers a straightforward approach to data observability, with concepts that are **easy to understand** at a glance. Reviewers mention the simplicity of creating freshness and volume checks, which can be particularly beneficial for teams looking for quick solutions without extensive technical knowledge.
- **According to verified reviews** , Monte Carlo stands out for its **quality of support** , receiving high praise for its responsiveness and helpfulness. Users have noted that the platform acts as a reliable partner in business, with one reviewer stating that it helps maintain confidence in data quality through effective troubleshooting capabilities.
- **Reviewers mention** that while Bigeye provides valuable features for data quality checks, it sometimes lacks the depth of automation found in Monte Carlo. Users have expressed that Monte Carlo's ability to **self-learn** and create new rules and alerts significantly reduces manual oversight, making it a more efficient choice for data teams.
- **G2 reviewers highlight** that Monte Carlo's focus on **data lineage** and alerting mechanisms allows teams to quickly detect and address data quality issues. This capability is particularly appreciated by users who need to ensure data integrity across complex systems, as it simplifies the troubleshooting process.
- **Users say** that Bigeye shines in its **customization options** , allowing for tailored SQL checks that can adapt to specific data needs. However, some users feel that it may not be as robust in terms of overall analytics capabilities compared to Monte Carlo, which offers a more comprehensive suite of features for data observability.



---
## Frequently Asked Questions

### What is the difference between Monte Carlo vs Bigeye?

Monte Carlo stands out for its higher G2 rating, larger review base, and more frequently cited strengths in ease of use and integrations compared to Bigeye.

| [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) | [Bigeye](https://www.g2.com/products/bigeye/reviews) |
| --- | --- |
| 4.3/5 (536 reviews) | 4.1/5 (22 reviews) |
| — | — |
| 8.2 | 8.1 |
| 9.0 | 8.2 |
| Ease of Use (104 all-time mentions) | Ease of Use (recent reviews) |



### How do the pricing models of Monte Carlo and Bigeye compare?

Monte Carlo is rated higher on value-related satisfaction, but reviewers for both Monte Carlo and Bigeye mention pricing as a consideration.

- **Monte Carlo:** Reviewers frequently cite the product as expensive, especially as usage scales, but also note that the ROI is justified by time savings and proactive monitoring.
- **Bigeye:** Reviewers mention that the cost may be a consideration for smaller organizations, but appreciate the platform's value in monitoring and troubleshooting data pipelines.
- **Switching reasons:** Recent reviews for both products highlight value for money and operational efficiency as key factors in their purchasing decisions.



### What are the best alternatives to Monte Carlo and Bigeye?

The top 3 alternatives to Monte Carlo and Bigeye are Acceldata, Anomalo, and Databricks.

| Product | G2 Rating (reviews) | Largest Segment | Pricing Insight | Top Reviewer-Cited Strength |
| --- | --- | --- | --- | --- |
| [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) | 4.3/5 (536 reviews) | — | Pricing is frequently cited as high, but justified by ROI and time savings | Ease of Use (104 all-time mentions) |
| [Bigeye](https://www.g2.com/products/bigeye/reviews) | 4.1/5 (22 reviews) | — | Cost may be a consideration for smaller organizations | Ease of Use (recent reviews) |
| [Acceldata](https://www.g2.com/products/acceldata/reviews) | 4.4/5 (56 reviews) | Enterprise | — | — |
| [Anomalo](https://www.g2.com/products/anomalo/reviews) | 4.4/5 (44 reviews) | Enterprise | — | — |
| [Databricks](https://www.g2.com/products/databricks/reviews) | 4.6/5 (1366 reviews) | Enterprise | — | — |



### Which AI Agent Observability features should I prioritize when comparing Monte Carlo and Bigeye?

Buyers should prioritize integrations, alerting and monitoring, data lineage, automation, and anomaly detection when comparing Monte Carlo and Bigeye.

- **Integrations:** Monte Carlo has 45 all-time mentions for integrations and 44 for easy integrations; Bigeye has recent mentions but only 1 all-time mention for integrations.
- **Alerting and Monitoring:** Monte Carlo is cited in 98 reviews for alerts and 92 for monitoring; Bigeye is mentioned for monitoring in recent reviews.
- **Data Lineage:** Monte Carlo has 46 all-time mentions for data lineage; Bigeye is cited for lineage in recent reviews.
- **Automation:** Monte Carlo is mentioned in 34 reviews for automation; Bigeye is cited for automated anomaly detection in recent reviews.
- **Anomaly Detection:** Monte Carlo has 33 all-time mentions for anomaly detection; Bigeye is cited for automated anomaly detection in recent reviews.



### What are the pros and cons of Monte Carlo vs Bigeye?

Monte Carlo's headline strength is its ease of use and integrations, while Bigeye is noted for its user-friendly platform and real-time monitoring.

- **Monte Carlo strengths:** Ease of Use (104 all-time mentions), Alerts (98), Monitoring (92), Integrations (45), Data Lineage (46), Automation (34), Anomaly Detection (33).
- **Monte Carlo trade-offs:** Alert Management (58), Alert Overload (57), Inefficient Alert System (47), UX Improvement (46), Limited Functionality (36), pricing is frequently cited as high.
- **Bigeye strengths:** Ease of Use (recent reviews), real-time monitoring, automated anomaly detection, collaborative investigation tools, user-friendly interface.
- **Bigeye trade-offs:** Limited Features (1), Limited Integrations (1), cost may be a consideration for smaller organizations, some reviewers cite bugs and performance issues.



### Is Monte Carlo or Bigeye better for small businesses?

Bigeye is a better fit for small businesses based on reviewer sentiment and cost considerations.

- **Monte Carlo:** Reviewers note that pricing can be high for small-sized organizations, making it less accessible for smaller businesses.
- **Bigeye:** Reviewers from smaller organizations appreciate its user-friendly platform and mention that while cost is a consideration, the platform is valuable for monitoring and troubleshooting data pipelines.



### Which AI Agent Observability platform has better integrations?

Monte Carlo is favored by reviewers for integrations, with significantly more mentions and third-party tool support than Bigeye.

- **Monte Carlo:** Slack (99 all-time mentions), Snowflake (33), PagerDuty (11); integrations are cited in 45 reviews and easy integrations in 44.
- **Bigeye:** Integrations are mentioned in recent reviews, including Hubspot, MySQL, and Snowflake, but only 1 all-time mention for integrations.



### How do Monte Carlo and Bigeye compare on customer support?

Monte Carlo leads Bigeye on Quality of Support by 0.8 points, a material difference in reviewer satisfaction.

- **Monte Carlo:** Reviewers consistently praise the support team for responsiveness, onboarding assistance, and resolving issues quickly.
- **Bigeye:** Reviewers describe customer service as great and helpful, but some mention occasional delays or bugs affecting support experiences.



### Which is easier to implement, Monte Carlo or Bigeye?

Monte Carlo and Bigeye score within 0.1 points of each other on Ease of Setup, indicating parity in implementation experience.

- **Monte Carlo:** Reviewers describe setup as easy and straightforward, with onboarding support frequently cited as a positive.
- **Bigeye:** Reviewers note that setup is simple and user-friendly, with no-code interfaces and quick integration with data sources.



### Which product has better Integrations?

Monte Carlo is the stronger product for integrations, with more reviewer-cited integrations and higher all-time mention counts.

- **Monte Carlo:** Integrations are cited in 45 reviews, easy integrations in 44, and specific integrations like Slack (99), Snowflake (33), and PagerDuty (11) are frequently mentioned.
- **Bigeye:** Integrations are mentioned in recent reviews, including Hubspot, MySQL, and Snowflake, but only 1 all-time mention for integrations.



| | Bigeye | Monte Carlo | 
|---|---|---|
| **Star Rating** | 4.1 out of 5 | 4.3 out of 5 | 
| **Total Reviews** | 22 | 549 | 

---
## Top Pros & Cons

### Bigeye

Pros:
- Ease of Use (1 reviews)
- Features (1 reviews)

Cons:
- Limited Features (1 reviews)
- Limited Integrations (1 reviews)

### Monte Carlo

Pros:
- Ease of Use (104 reviews)
- Alerts (98 reviews)

Cons:
- Alert Management (58 reviews)
- Alert Overload (57 reviews)

---
## Ratings Comparison
| Rating | Bigeye | Monte Carlo | 
|---|---|---|
  | **Meets Requirements** | 8.0 (22 reviews) | 8.4 (490 reviews) | 
  | **Ease of Use** | 8.5 (22 reviews) | 8.3 (500 reviews) | 
  | **Ease of Setup** | 8.1 (12 reviews) | 8.2 (360 reviews) | 
  | **Ease of Admin** | 7.2 (12 reviews) | 8.5 (167 reviews) | 
  | **Quality of Support** | 8.2 (20 reviews) | 9.0 (442 reviews) | 
  | **Has the product been a good partner in doing business?** | 8.3 (12 reviews) | 9.3 (171 reviews) | 
  | **Product Direction (% positive)** | 7.8 (21 reviews) | 8.8 (473 reviews) | 

---
## Pricing

### Bigeye

#### Entry-Level Pricing

Plan: Enterprise Starter

Price: Contact Us

Key Features:
- End-to-end lineage
- Cloud, on prem, and hybrid support
- Cross-source columnar mapping

[Learn more about Bigeye](https://www.g2.com/products/bigeye/reviews)

#### Free Trial

No

### Monte Carlo

#### Entry-Level Pricing

No pricing available

#### Free Trial

No information available

---
## Features Comparison By Category

### Database Monitoring

| Product | Score | Reviews |
|---|---|---|
| **Bigeye** | N/A | N/A |
| **Monte Carlo** | 7.6/10 | 269 |

#### Functionality

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Monitoring** | Not enough data | 9.0 (265 reviews) | 
| **Alerting** | Not enough data | 8.8 (266 reviews) | 
| **Logging** | Not enough data | 7.8 (238 reviews) | 
| **Response Time** | Not enough data | 8.3 (246 reviews) | 
| **Reporting** | Not enough data | 7.7 (243 reviews) | 
| **Data Visualization** | Not enough data | 7.4 (243 reviews) | 
| **Performance Monitoring** | Not enough data | Not enough data | 
| **Real-Time Monitoring** | Not enough data | Not enough data | 
| **Server Monitoring** | Not enough data | Not enough data | 
| **Real-Time Reporting** | Not enough data | Not enough data | 
| **Uptime Reporting** | Not enough data | Not enough data | 
| **Transaction Monitoring** | Not enough data | Not enough data | 
| **Real-Time Data** | Not enough data | Not enough data | 

#### Agentic AI - Database Monitoring

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Autonomous Task Execution** | Not enough data | 7.1 (13 reviews) | 
| **Multi-step Planning** | Not enough data | 6.9 (13 reviews) | 
| **Cross-system Integration** | Not enough data | 6.8 (13 reviews) | 
| **Adaptive Learning** | Not enough data | 7.3 (14 reviews) | 
| **Natural Language Interaction** | Not enough data | 6.8 (12 reviews) | 
| **Proactive Assistance** | Not enough data | 6.5 (13 reviews) | 
| **Decision Making** | Not enough data | 7.1 (13 reviews) | 
| **Third-Party Integrations** | Not enough data | Not enough data | 
| **Capacity Planning** | Not enough data | Not enough data | 

#### Additional Functionality

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Resource Management** | Not enough data | Not enough data | 
| **Anomaly Detection** | Not enough data | Not enough data | 
| **Visual Analytics** | Not enough data | Not enough data | 
| **Remote Monitoring & Management** | Not enough data | Not enough data | 
| **Secure Data Storage** | Not enough data | Not enough data | 
| **Dashboard** | Not enough data | Not enough data | 
| **Generative AI** | Not enough data | Not enough data | 
| **Configuration Management** | Not enough data | Not enough data | 
| **API** | Not enough data | Not enough data | 
| **User Management** | Not enough data | Not enough data | 
| **Capacity Management** | Not enough data | Not enough data | 
| **Diagnostic Tools** | Not enough data | Not enough data | 
| **Dependency Tracking** | Not enough data | Not enough data | 
| **Troubleshooting** | Not enough data | Not enough data | 
| **Reporting & Statistics** | Not enough data | Not enough data | 
| **Reporting/Analytics** | Not enough data | Not enough data | 
| **Predictive Analytics** | Not enough data | Not enough data | 
| **Audit Management** | Not enough data | Not enough data | 
| **Real-Time Notifications** | Not enough data | Not enough data | 
| **Application Management** | Not enough data | Not enough data | 
| **Data Storage Management** | Not enough data | Not enough data | 
| **Application-Level Analysis** | Not enough data | Not enough data | 
| **Multitenancy** | Not enough data | Not enough data | 
| **Query Analysis** | Not enough data | Not enough data | 
| **Performance Management** | Not enough data | Not enough data | 
| **Access Controls/Permissions** | Not enough data | Not enough data | 
| **Compliance Management** | Not enough data | Not enough data | 
| **Historical Trend Analysis** | Not enough data | Not enough data | 
| **Alerts/Notifications** | Not enough data | Not enough data | 
| **Summary Reports** | Not enough data | Not enough data | 
| **AI Copilot** | Not enough data | Not enough data | 
| **Event Logs** | Not enough data | Not enough data | 
| **Dashboard Creation** | Not enough data | Not enough data | 
| **Automated Discovery** | Not enough data | Not enough data | 
| **Prioritization** | Not enough data | Not enough data | 
| **Issue Tracking** | Not enough data | Not enough data | 
| **Activity Dashboard** | Not enough data | Not enough data | 
| **Performance Metrics** | Not enough data | Not enough data | 
| **Resource Optimization** | Not enough data | Not enough data | 
| **Real-Time Analytics** | Not enough data | Not enough data | 
| **Status Tracking** | Not enough data | Not enough data | 

### DataOps Platforms

| Product | Score | Reviews |
|---|---|---|
| **Bigeye** | 9.0/10 | 5 |
| **Monte Carlo** | 7.6/10 | 59 |

#### Data Management

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Data Integration** | 8.3 (5 reviews) | 8.6 (53 reviews) | 
| **Metadata** | 8.3 (5 reviews) | 8.4 (48 reviews) | 
| **Self-service** | 8.7 (5 reviews) | 8.6 (53 reviews) | 
| **Automated workflows** | 9.3 (5 reviews) | 8.0 (51 reviews) | 

#### Agentic AI - DataOps Platforms

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Autonomous Task Execution** | Not enough data | 7.6 (7 reviews) | 
| **Multi-step Planning** | Feature Not Available | 6.7 (6 reviews) | 
| **Cross-system Integration** | Not enough data | 6.9 (6 reviews) | 
| **Adaptive Learning** | Not enough data | 7.4 (7 reviews) | 
| **Decision Making** | Feature Not Available | 6.9 (6 reviews) | 

#### Analytics

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Analytics capabilities** | 9.0 (5 reviews) | 7.9 (51 reviews) | 
| **Dasboard visualizations** | 9.7 (5 reviews) | 7.7 (48 reviews) | 

#### Monitoring and Management

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Data Observability** | 9.3 (5 reviews) | 9.2 (58 reviews) | 
| **Testing capabilities** | Not enough data | 7.7 (49 reviews) | 

#### Cloud Deployment

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Hybrid cloud support** | 9.0 (5 reviews) | 7.5 (44 reviews) | 
| **Cloud migration capabilities** | 9.0 (5 reviews) | 7.1 (42 reviews) | 

#### Generative AI

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **AI Text Generation** | Feature Not Available | 6.3 (35 reviews) | 
| **AI Text Summarization** | Not enough data | 6.2 (35 reviews) | 

### Data Observability

| Product | Score | Reviews |
|---|---|---|
| **Bigeye** | 7.8/10 | 19 |
| **Monte Carlo** | 7.6/10 | 382 |

#### Functionality

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Real-time Analytics** | 8.2 (19 reviews) | 7.4 (293 reviews) | 
| **Data quality monitoring** | 9.0 (19 reviews) | 8.8 (342 reviews) | 
| **Automation** | 8.1 (18 reviews) | 8.2 (306 reviews) | 
| **End to End visiblity** | 7.8 (18 reviews) | 8.1 (312 reviews) | 

#### Management

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Anomaly identification** | 8.2 (19 reviews) | 8.8 (345 reviews) | 
| **Single pane view** | 7.6 (18 reviews) | 7.8 (292 reviews) | 
| **Real-time alerts** | 7.9 (18 reviews) | 8.3 (332 reviews) | 
| **Data lineage** | 7.2 (18 reviews) | 8.0 (315 reviews) | 
| **Integrations** | 8.4 (18 reviews) | 8.2 (326 reviews) | 

#### Generative AI

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **AI Text Generation** | 5.8 (6 reviews) | 5.8 (232 reviews) | 

#### Agentic AI - Data Observability

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Autonomous Task Execution** | Not enough data | 6.9 (33 reviews) | 
| **Multi-step Planning** | Feature Not Available | 6.5 (28 reviews) | 
| **Cross-system Integration** | Not enough data | 7.0 (30 reviews) | 
| **Natural Language Interaction** | Feature Not Available | 6.7 (27 reviews) | 
| **Proactive Assistance** | Not enough data | 7.1 (32 reviews) | 

### AI Agent Observability

| Product | Score | Reviews |
|---|---|---|
| **Bigeye** | N/A | N/A |
| **Monte Carlo** | 9.3/10 | 14 |

#### Tracing & Debugging

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Agent Debugging** | Not enough data | Not enough data | 
| **Trace Visualization** | Not enough data | Not enough data | 
| **End-to-End Agent Tracing** | Not enough data | Not enough data | 

#### Evaluation & Quality

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Regression Testing** | Not enough data | Not enough data | 
| **Hallucination Detection** | Not enough data | Not enough data | 
| **Automated Output Evaluation** | Not enough data | Not enough data | 

#### Production Monitoring

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Alerts & Notifications** | Not enough data | 9.3 (9 reviews) | 
| **Latency Monitoring** | Not enough data | Not enough data | 
| **Token Usage & Cost Tracking** | Not enough data | Not enough data | 

#### Agent Discovery & Governance

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Audit Logging** | Not enough data | Not enough data | 
| **Agent Discovery** | Not enough data | Not enough data | 
| **Policy Compliance Monitoring** | Not enough data | Not enough data | 

### Data Quality

| Product | Score | Reviews |
|---|---|---|
| **Bigeye** | N/A | N/A |
| **Monte Carlo** | 7.0/10 | 203 |

#### Functionality

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Identification** | Not enough data | 8.1 (193 reviews) | 
| **Correction** | Not enough data | 6.5 (176 reviews) | 
| **Normalization** | Not enough data | 6.7 (170 reviews) | 
| **Preventative Cleaning** | Not enough data | 6.1 (165 reviews) | 
| **Data Matching** | Not enough data | 6.5 (166 reviews) | 
| **Real-Time Data** | Not enough data | Not enough data | 

#### Management

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Reporting** | Not enough data | 7.2 (169 reviews) | 
| **Automation** | Not enough data | 7.5 (170 reviews) | 
| **Quality Audits** | Not enough data | 8.0 (170 reviews) | 
| **Dashboard** | Not enough data | 7.4 (179 reviews) | 
| **Governance** | Not enough data | 7.6 (170 reviews) | 

#### Generative AI

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **AI Text Generation** | Not enough data | 5.2 (145 reviews) | 
| **AI Text Summarization** | Not enough data | 5.3 (145 reviews) | 
| **Generative AI** | Not enough data | Not enough data | 

#### Additional Functionality

| Feature | Bigeye | Monte Carlo | 
|---|---|---|
| **Metadata Management** | Not enough data | Not enough data | 
| **Collaboration Tools** | Not enough data | Not enough data | 
| **Search/Filter** | Not enough data | Not enough data | 
| **Workflow Management** | Not enough data | Not enough data | 
| **AI Copilot** | Not enough data | Not enough data | 
| **Third-Party Integrations** | Not enough data | Not enough data | 
| **Data Synchronization** | Not enough data | Not enough data | 
| **Data Import/Export** | Not enough data | Not enough data | 
| **Customizable Rules** | Not enough data | Not enough data | 
| **Master Data Management** | Not enough data | Not enough data | 
| **Monitoring** | Not enough data | Not enough data | 
| **Data Transformation** | Not enough data | Not enough data | 
| **Multiple Data Sources** | Not enough data | Not enough data | 
| **Self Service Portal** | Not enough data | Not enough data | 
| **Customer Database** | Not enough data | Not enough data | 
| **Data Verification** | Not enough data | Not enough data | 
| **Data Migration** | Not enough data | Not enough data | 
| **Multi-Language** | Not enough data | Not enough data | 
| **Single Sign On** | Not enough data | Not enough data | 
| **Duplicate Detection** | Not enough data | Not enough data | 
| **Email Address Extraction** | Not enough data | Not enough data | 
| **Reporting/Analytics** | Not enough data | Not enough data | 
| **Data Profiling** | Not enough data | Not enough data | 
| **Data Extraction** | Not enough data | Not enough data | 
| **Data Mapping** | Not enough data | Not enough data | 
| **Address Validation** | Not enough data | Not enough data | 
| **Match & Merge** | Not enough data | Not enough data | 
| **Performance Metrics** | Not enough data | Not enough data | 
| **Visual Analytics** | Not enough data | Not enough data | 
| **Version Control** | Not enough data | Not enough data | 
| **API** | Not enough data | Not enough data | 
| **Data Capture and Transfer** | Not enough data | Not enough data | 
| **Access Controls/Permissions** | Not enough data | Not enough data | 
| **Compliance Management** | Not enough data | Not enough data | 
| **Data Discovery** | Not enough data | Not enough data | 

---
## Categories
**Shared Categories (2):** [DataOps Platforms](https://www.g2.com/categories/dataops-platforms), [Data Observability Software](https://www.g2.com/categories/data-observability)


**Unique to Monte Carlo (3):** [AI Agent Observability Software](https://www.g2.com/categories/ai-agent-observability), [Data Quality Tools](https://www.g2.com/categories/data-quality), [Database Monitoring Tools](https://www.g2.com/categories/database-monitoring)


---
## Reviewer Demographics

### By Company Size

| Segment | Bigeye | Monte Carlo | 
|---|---|---|
| **Small-Business** | 54.5% | 4.7% | 
| **Mid-Market** | 27.3% | 43.1% | 
| **Enterprise** | 18.2% | 52.2% | 

### By Industry

#### Bigeye

- **Information Technology and Services:** 22.7%
- **Computer Software:** 13.6%
- **Consulting:** 4.5%
- **Sports:** 4.5%
- **Online Media:** 4.5%
- **Mental Health Care:** 4.5%
- **Management Consulting:** 4.5%
- **Logistics and Supply Chain:** 4.5%
- **Internet:** 4.5%
- **Information Services:** 4.5%
- **Other:** 27.3%

#### Monte Carlo

- **Financial Services:** 13.0%
- **Computer Software:** 11.9%
- **Information Technology and Services:** 11.9%
- **Manufacturing:** 3.9%
- **Marketing and Advertising:** 3.5%
- **Retail:** 3.1%
- **Pharmaceuticals:** 3.1%
- **Entertainment:** 2.9%
- **Oil & Energy:** 2.9%
- **Online Media:** 2.7%
- **Other:** 41.1%

---
## Alternatives

### Alternatives to Bigeye

- [Databricks](https://www.g2.com/products/databricks/reviews) — 4.6/5 stars (1374 reviews)
- [Hightouch](https://www.g2.com/products/hightouch/reviews) — 4.6/5 stars (416 reviews)
- [Fivetran](https://www.g2.com/products/fivetran/reviews) — 4.3/5 stars (844 reviews)
- [Boost.space](https://www.g2.com/products/boost-space/reviews) — 4.6/5 stars (350 reviews)
- [Informatica Data Integration and Engineering](https://www.g2.com/products/informatica-data-integration-and-engineering/reviews) — 4.3/5 stars (337 reviews)
- [Mezmo](https://www.g2.com/products/mezmo/reviews) — 4.6/5 stars (224 reviews)
- [Integrate.io](https://www.g2.com/products/integrate-io/reviews) — 4.4/5 stars (213 reviews)
- [dbt](https://www.g2.com/products/dbt/reviews) — 4.7/5 stars (209 reviews)
- [Cloudera](https://www.g2.com/products/cloudera/reviews) — 4.2/5 stars (200 reviews)
- [OpsPilot](https://www.g2.com/products/opspilot/reviews) — 4.8/5 stars (181 reviews)

### Alternatives to Monte Carlo

- [Acceldata](https://www.g2.com/products/acceldata/reviews) — 4.4/5 stars (55 reviews)
- [Anomalo](https://www.g2.com/products/anomalo/reviews) — 4.4/5 stars (44 reviews)
- [Datadog](https://www.g2.com/products/datadog/reviews) — 4.4/5 stars (731 reviews)
- [Soda](https://www.g2.com/products/soda/reviews) — 4.4/5 stars (55 reviews)
- [Metaplane](https://www.g2.com/products/metaplane/reviews) — 4.8/5 stars (116 reviews)
- [Sifflet](https://www.g2.com/products/sifflet/reviews) — 4.3/5 stars (56 reviews)
- [Dynatrace](https://www.g2.com/products/dynatrace/reviews) — 4.5/5 stars (1371 reviews)
- [Databricks](https://www.g2.com/products/databricks/reviews) — 4.6/5 stars (1374 reviews)
- [Hightouch](https://www.g2.com/products/hightouch/reviews) — 4.6/5 stars (416 reviews)
- [IBM Instana](https://www.g2.com/products/ibm-instana/reviews) — 4.4/5 stars (481 reviews)

---
## Top Discussions

### Bigeye

No discussions available for this product.

### Monte Carlo

- Title: [What is Monte Carlo software?](https://www.g2.com/discussions/what-is-monte-carlo-software) — 1 comment
  > **Top comment:** "Monte Carlo is a fully automated, end-to-end data observability platform that helps data engineering teams reduce time to detection and resolution for data..."

---
**Source:** [G2.com](https://www.g2.com) | [Comparison Page](https://www.g2.com/compare/bigeye-vs-monte-carlo)