BigPanda vs InfluxDB comparison

BigPanda and InfluxData are both solutions in the IT Infrastructure Monitoring category. BigPanda is ranked #21 with an average rating of 8.3, while InfluxData is ranked #14 with an average rating of 8.2. BigPanda holds a 0.7% mindshare in IM, compared to InfluxData’s 0.7% mindshare. Additionally, 85% of BigPanda users are willing to recommend the solution, compared to 100% of InfluxData users who would recommend it.

BigPanda

Read 20 BigPanda reviews

4,250 Views
2,253 Comparison Views

85% willing to recommend

InfluxDB

Read 20 InfluxDB reviews

6,493 Views
1,883 Comparison Views

100% willing to recommend

BigPanda

InfluxDB

Comparison Buyer's Guide

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Executive SummaryUpdated on Oct 9, 2024

BigPanda and InfluxDB are products that compete in the realm of IT operations and data management. BigPanda has an advantage in incident response management, while InfluxDB has the upper hand in handling high-volume time-series data.

Features:BigPanda specializes in IT operation automation, with features like incident normalization, correlation, and automation that streamline workflows. It integrates with various monitoring tools to centralize alerts and reduce noise. The platform also provides AI-based incident intelligence to understand root causes. InfluxDB offers a high-performance time-series database with robust query capabilities for real-time analytics. It supports data retention policies to manage storage efficiently and provides a comprehensive set of tools for data visualization and alerting. InfluxDB also enables seamless integration with popular data processing platforms.

Room for Improvement:BigPanda could improve by expanding its integration capabilities to support more niche tools. Enhancing the AI-driven insights for better predictive analysis would be beneficial. The user interface could be more intuitive for new users. InfluxDB may need to streamline its scaling process to simplify managing extensive data loads. More user-friendly deployment options could be considered. Enhanced support for non-time-series data types would broaden its applicability.

Ease of Deployment and Customer Service:BigPanda typically offers seamless deployment with strong support channels, ensuring quick setup and operation. InfluxDB's deployment can be complex, especially when scaling operations, but it provides detailed documentation and community support. BigPanda focuses on supporting operational efficiency, whereas InfluxDB requires tailored efforts for data management deployment.

Pricing and ROI:BigPanda's pricing may involve higher initial costs due to its extensive automation features but offers clear ROI through improved incident management efficiency. InfluxDB's cost model targets scalable solutions, often presenting lower initial costs with favorable ROI, particularly for operations dependent on time-series data analytics. The products align costs with operational gains differently, BigPanda emphasizing automation value and InfluxDB data utility.

To learn more, read our detailed BigPanda vs. InfluxDB Report (Updated: June 2026).

Buyer's Guide

BigPanda vs. InfluxDB

June 2026

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Helped 902,988 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

ROI

Sentiment score

5.5

BigPanda surpasses Netcool in efficiency, reducing resources and enhancing incident resolution and recovery times for heavy users.

Sentiment score

5.8

Companies experienced enhanced operational efficiency and increased customer satisfaction with InfluxDB through real-time monitoring and automation.

BigPanda offers significant time-saving, cost-saving, and resource-saving benefits.

reviewer2691138

Technical Lead

BigPanda saves time with its advanced features and manages large environments while requiring fewer resources compared to our previous tool, Netcool.

CHANTI BANOTH

Software Engineer at Trianz

Resource count has probably reduced by about ten to twenty percent due to the reduced incident count, which enables me to identify issues faster, meaning business recovery is quicker.

KiranMs

Director Of Engineering at Broadcom Inc.

For more quotes and insights, download the BigPanda report

These improvements translated into both cost savings and better service reliability, directly impacting business outcomes.

reviewer2804886

Senior Data Engineer at a university with 201-500 employees

It simplifies processes and reduces the need for additional employees.

Mugeesh Husain

Team Lead, Software at Energybox

It has reduced a lot of time in terms of troubleshooting because the way it produces the data on a time-series basis allows me to collect and store the data for future reference.

Gaurav Dangaich

Sdet Performance Engineer at a tech vendor with 10,001+ employees

For more quotes and insights, download the InfluxDB report

Customer Service

Sentiment score

6.5

BigPanda's support is praised for responsiveness and effectiveness, despite occasional delays, with some users noting communication issues.

Sentiment score

5.8

InfluxDB customer support is praised for enterprise-level help but needs faster response times and more complex deployment support.

If BigPanda can consistently provide such competent contacts, I would rate the support ten out of ten, otherwise, it is an eight out of ten.

Atharva Jagdale

Engineer - Cloud and Infrastructure Services at a tech vendor with 10,001+ employees

Companies like CoreLogix, which is a log platform, achieve ten out of ten due to their responsiveness.

Michael Wenn

CEO / Co-Founder at Aiops ltd

For technical support, we have only had to address password resets and alert mismatching.

reviewer2691138

Technical Lead

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They get on a call, resolve issues, and handle everything efficiently.

Manas Kashyap

Senior Dev Ops Engineer at 11 East Capital

The InfluxDB support team was knowledgeable and helped us troubleshoot complex problems efficiently.

reviewer2804886

Senior Data Engineer at a university with 201-500 employees

Obtaining that quantity of data directly from InfluxDB is quite challenging, and that is why we ask for help from the InfluxDB team to retrieve the data to avoid timeouts and those kinds of issues.

Mugeesh Husain

Team Lead, Software at Energybox

For more quotes and insights, download the InfluxDB report

Scalability Issues

Sentiment score

7.2

BigPanda efficiently scales across environments, managing numerous alerts and servers, with high ratings despite occasional peak-time delays.

Sentiment score

7.0

InfluxDB scales efficiently in enterprises, supports large data volumes, and integrates well, though backup stability varies by deployment.

It handles large volumes of alerts without limitations.

Sneha Vigneshwari

Works

We manage a large environment with over 50,000 servers and various monitoring tools like Dynatrace, New Relic, Splunk, Nagios, and Datadog.

CHANTI BANOTH

Software Engineer at Trianz

I rate the scalability of BigPanda at eight.

RajneeshKumar3

Manager Observability at ICE

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The main challenge with InfluxDB, which is common with all databases, was handling very high throughput systems and high throughput message flow.

Sayak Roy

Deployment Engineer at Derq

It can handle large volumes of time-series data and with high ingestion rates, making it suitable for enterprise-scale deployments.

reviewer2804886

Senior Data Engineer at a university with 201-500 employees

We’ve scaled on volume with seven years of continuous data without performance degradation.

Henning Jansen

Senior System Developer at Norled

For more quotes and insights, download the InfluxDB report

Stability Issues

Sentiment score

7.5

BigPanda is stable with slight slowdowns; users request intuitive features, appreciate communication, and note improved stability and task management.

Sentiment score

8.0

InfluxDB is reliable, stable, and supported, with minor issues resolved by integrations and support, except in Azure China.

BigPanda is now stable.

Sneha Vigneshwari

Works

I would rate the availability of BigPanda at nine because it's almost 99.99% available.

RajneeshKumar3

Manager Observability at ICE

However, when handling critical traffic, the BigPanda site can slow down, which we manage with a load balancer.

CHANTI BANOTH

Software Engineer at Trianz

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It serves as the backbone of our application, and its stability is crucial.

Henning Jansen

Senior System Developer at Norled

We have used it to support mission-critical systems with continuous data ingestion and real-time analytics.

reviewer2804886

Senior Data Engineer at a university with 201-500 employees

It is very stable, with no reliability or downtime in InfluxDB.

Btece Lodi

Student at a educational organization with 1,001-5,000 employees

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Room For Improvement

BigPanda requires AI enhancements, bug fixes, improved usability, expanded features, and better integration to address cost and performance issues.

InfluxDB requires improvements in query language, UI, pricing, documentation, scalability, cloud integration, and support for non-technical users.

A 'deep dive' analysis feature would be appreciated to give detailed insights such as CPU usage and disk space analysis.

Sneha Vigneshwari

Works

It would be beneficial if BigPanda leveraged AI to solve critical issues related to editing and sending alerts based on enrichment mapping files.

CHANTI BANOTH

Software Engineer at Trianz

If BigPanda could integrate AI, it would enhance the platform significantly by offering chatbot functionality within the BigPanda UI.

Atharva Jagdale

Engineer - Cloud and Infrastructure Services at a tech vendor with 10,001+ employees

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InfluxDB deprecated FluxQL, which was intuitive since developers are already familiar with standard querying.

Milan Predic

Chief Technology Officer at Presta Agency

Having a SQL abstraction in InfluxDB could be beneficial, making it more accessible for teams that prefer querying with SQL-style syntax.

Henning Jansen

Senior System Developer at Norled

It could include automated backup and a monitoring solution for InfluxDB or a script developed by a REST API.

reviewer2778060

Network engineer at a energy/utilities company with 10,001+ employees

For more quotes and insights, download the InfluxDB report

Setup Cost

BigPanda offers competitive pricing and flexible licensing, benefiting high-growth companies with potential costs reaching $200,000 annually.

InfluxDB's pricing shift to a monthly model prompts enterprises to consider open-source options for cost-effective scalability and flexibility.

The pricing for BigPanda is reasonable compared to other event management tools, given its advantages.

CHANTI BANOTH

Software Engineer at Trianz

There are indirect costs related to managing open-source products, leading to resource investment in maintaining the dashboards for these capabilities.

KiranMs

Director Of Engineering at Broadcom Inc.

For more quotes and insights, download the BigPanda report

We use the open-source version of InfluxDB, so it is free.

Henning Jansen

Senior System Developer at Norled

I find the cloud version pricing of InfluxDB reasonable, and for the on-premises solution we use in our service, we need to purchase licenses.

Mugeesh Husain

Team Lead, Software at Energybox

Pricing is based on data volume, retention, and features, which really makes it scalable but requires careful planning to avoid unexpected costs.

reviewer2804886

Senior Data Engineer at a university with 201-500 employees

For more quotes and insights, download the InfluxDB report

Valuable Features

BigPanda enhances incident management with AI-driven analysis, reducing response times via integration and alert consolidation for improved reliability.

InfluxDB excels in fast data writes, analytics, and integration, enhancing efficiency and visualization with robust community support.

Its automation has significantly improved incident response times, reducing the process to within one minute.

Sneha Vigneshwari

Works

It can correlate multiple issues within a single device, create a single incident, and thus reduce noise and provide faster resolution.

RajneeshKumar3

Manager Observability at ICE

BigPanda improves service reliability with instant resolution, increased uptime, and reduced mean time to resolution, thus enhancing service quality.

reviewer2691138

Technical Lead

For more quotes and insights, download the BigPanda report

The most important feature for us is low latency, which is crucial in building a high-performance engine for day trading.

Milan Predic

Chief Technology Officer at Presta Agency

InfluxDB’s core functionality is crucial as it allows us to store our data and execute queries with excellent response times.

Henning Jansen

Senior System Developer at Norled

It helps me maintain my solution easily because it is very reliable, so we didn't face any performance issues or crashes regarding our queries; we can get the results very fast.

reviewer2761710

Solutions Engineer at a tech vendor with 51-200 employees

For more quotes and insights, download the InfluxDB report

Categories and Ranking

BigPanda

Ranking in IT Infrastructure Monitoring

21st

Average Rating

7.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

IT Alerting and Incident Management (9th), AIOps (9th)

InfluxDB

Ranking in IT Infrastructure Monitoring

14th

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Non-Relational Databases (1st), Open Source Databases (7th), Network Monitoring Software (13th), NoSQL Databases (6th)

Mindshare comparison

As of July 2026, in the IT Infrastructure Monitoring category, the mindshare of BigPanda is 0.7%, down from 0.9% compared to the previous year. The mindshare of InfluxDB is 0.7%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

IT Infrastructure Monitoring Mindshare Distribution
Product	Mindshare (%)
InfluxDB	0.7%
BigPanda	0.7%
Other	98.6%

IT Infrastructure Monitoring

Featured Reviews

Michael Wenn

CEO / Co-Founder at Aiops ltd

Automated incident workflows have reduced alert noise and now improve response efficiency

In my opinion, the best feature of BigPanda is its speed in terms of deployment. It has very strong integration with all of the major platforms and workflows that organizations need. The biggest customers are enterprises like HSBC and Barclays. Implementing something effective for them that dramatically reduces meantime to repair and the number of incidents is substantially difficult, as projects can often extend three years with very small results. BigPanda is different; it is a tool relied on by many enterprises, fitting over existing toolsets rather than trying to replace them, which makes it non-competitive to many existing alerts and monitoring tools. It enhances existing systems to provide actionable intelligence for business solutions.

Read full review

Mugeesh Husain

Team Lead, Software at Energybox

Time series data has been managed efficiently for IoT sensors but reporting still needs improvement

How InfluxDB can be improved is relevant since for Energy Box, we face certain issues. We have customers worldwide, including the United States, United Kingdom, and Europe, but when we expanded to China two years ago, they indicated that they do not support the cloud version there. Our application is built on the cloud, which required us to create a separate application for Azure China, which was painful for us. The second issue involves frequent version changes. For example, we started with version one, transitioned to version two, and I heard they are considering InfluxDB version three, reverting to earlier practices. InfluxDB should improve without completely changing its approach. Now we have to redo our work for InfluxDB version three. Regarding needed improvements, the documentation is sufficient, but pricing presents a challenge. InfluxDB has standard pricing, which is acceptable for large companies. However, for startups in our position, they should provide special discounts so everyone can utilize it. The pricing should adapt as companies grow, which is a reasonable expectation.

Read full review

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Top Industries

By visitors reading reviews

Financial Services Firm

24%

Manufacturing Company

Healthcare Company

Outsourcing Company

Financial Services Firm

12%

Manufacturing Company

10%

Comms Service Provider

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Large Enterprise	12

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	5
Large Enterprise	9

Questions from the Community

Any advice about APM solutions?

There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...

See all answers

What is your experience regarding pricing and costs for BigPanda?

Regarding extra expenses, I pay more for communication and do not incur costs for another dashboard perspective, but there are indirect costs related to managing open-source products, leading to re...

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What needs improvement with BigPanda?

Something that comes to mind regarding improvements is communication, as I rely heavily on another tool. If BigPanda could provide communication capabilities beyond just sending notifications—such ...

See all answers

What needs improvement with InfluxDB?

If the dashboarding facility can be improved in terms of the visualization parameters and the amount of support available from the community, as well as having smarter alerts to send those alerts t...

See all answers

What is your primary use case for InfluxDB?

My main use case for InfluxDB is to inject all my performance data and visualize it as a data source into Grafana. My data comes from JMeter from a plugin, which is inserting data to InfluxDB, and ...

See all answers

What advice do you have for others considering InfluxDB?

It is good to start with InfluxDB to stabilize your data, visualize your data, and have the data stored on a time-series basis. I would recommend everyone to get into InfluxDB and start using it. T...

See all answers

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Compared 9% of the time

PagerDuty Operations Cloud vs BigPanda

Compared 9% of the time

Splunk ITSI (IT Service Intelligence) vs BigPanda

Compared 6% of the time

Zabbix vs BigPanda

Compared 5% of the time

Dynatrace vs BigPanda

Compared 5% of the time

More BigPanda Competitors

PostgreSQL vs InfluxDB

Compared 7% of the time

MySQL vs InfluxDB

Compared 6% of the time

SQLite vs InfluxDB

Compared 6% of the time

MongoDB Enterprise Advanced vs InfluxDB

Compared 6% of the time

ClickHouse vs InfluxDB

Compared 6% of the time

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Product Reports

Buyer's Guide

BigPanda

June 2026

Download BigPanda product report

Buyer's Guide

InfluxDB

June 2026

Download InfluxDB product report

Overview

BigPanda enhances incident management through root cause analysis, alert deduplication, and event correlation. The AI-driven platform is designed for environments with high alert volumes, providing insights for data-driven decisions and seamless integration with tools like ServiceNow and Teams.

BigPanda addresses the complexities of incident management by offering an AI-focused approach to anomaly detection. Automation improves response times, while unified analytics supports informed decision-making. Despite AI integration and usability needing enhancement, the platform simplifies observability and ticketing through integrations with New Relic and Slack. Features like enrichment mapping and unified search improve functionality, though reporting and visualization aspects require development.

What are the key features of BigPanda?

Root Cause Analysis: Efficient identification of the sources of incidents.
Alert Deduplication: Reduces alert noise by consolidating duplicates.
Event Correlation: Connects related alerts for easier incident management.
Automation: Streamlines processes for faster response times.
Seamless Integration: Connects with tools like ServiceNow and Teams.

What benefits or ROI can users find in reviews?

Increased Efficiency: Automates incident management tasks.
Operational Insights: Provides valuable analytics for strategic decisions.
Improved Collaboration: Integrates notifications with Slack and other platforms.
Reduced Alert Fatigue: Deduplication and suppression improve focus on critical issues.

BigPanda is widely implemented in industries focusing on observability and predictive analysis, providing efficient alert processing and incident management. Users utilize its capabilities to seamlessly integrate with solutions like Dynatrace, particularly in environments that handle high volumes of alerts, ensuring effective notification delivery through various platforms.

BigPanda

InfluxDB offers efficient time series data handling with fast writes, optimized storage, and seamless Grafana integration, making it ideal for high-volume applications like crypto trading and real-time monitoring. Its SQL-like query language and cloud-based options enhance user experience and system scalability.

InfluxDB stands out with its ability to handle high-volume time series data efficiently, thanks to fast data writes and efficient compression. It is highly scalable, providing clustering features for improved performance management. Integration with Grafana enhances visualization, making it easier to analyze complex data through a user-friendly SQL-like query language. Real-time monitoring, historical data access, and proactive alerts enhance system reliability. Its cloud offering simplifies maintenance and operations, making it attractive for users seeking an efficient time series database.

What are the key features of InfluxDB?

Fast Data Writes: Ensures quick data handling necessary for real-time applications.
Optimized Storage: Reduces space requirements and improves performance.
Efficient Compression: Supports high-volume data like time series, enhancing throughput.
Grafana Integration: Supports seamless visualization and analysis of data.
SQL-like Query Language: Simplifies complex data operations with user-friendly queries.

What benefits or ROI can users expect?

Enhanced Performance: Fast processing and optimized storage for better application responsiveness.
Scalability: Clustering features ensure adaptability to growing data volumes.
Improved Reliability: Proactive alerts and real-time monitoring prevent system downtimes.
Ease of Use: SQL-like language and intuitive visuals improve user accessibility.

InfluxDB is applied extensively in industries handling high-volume data needs. For sensor data storage in production environments, it offers reliable performance. Its role in server management metrics and performance monitoring is crucial for maintaining optimal operations. In crypto market data collection, it supports fast-paced trading environments. Industries use it for real-time tracking, like maritime vessel monitoring, leveraging its rapid data handling and visualization capabilities. Its applications also extend to IoT environments, API performance tracking, HVAC systems, and log aggregation, often integrating with Prometheus, Docker, and AWS to enhance system capabilities.

InfluxData

Sample Customers

Nagios, ServiceNow, ITSM, NOC, CMDB Evolved, RemedyIncident Management Process

ebay, AXA, Mozilla, DiDi, LeTV, Siminars, Cognito, ProcessOut, Recommend, CATS, Smarsh, Row 44, Clustree, Bleemeo

Buyer's Guide

BigPanda vs. InfluxDB

June 2026

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