Best IoT Analytics Platforms

How Many IoT Analytics Platforms Products Does G2 Track?

Total Products under this Category: 150

Category Stats (Sep 2026)

  • Average Rating: 4.41/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Plutoshift (+0.86%) - Among all products in this category, Plutoshift recorded the largest rating increase compared to last month

Last updated: September 26, 2026

How Does G2 Rank IoT Analytics Platforms Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 2,400+ Authentic Reviews
  • 150+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for IoT Analytics Platforms

G2 Grid® for IoT Analytics Platforms plotting products by satisfaction and market presence

Highlighted products: Insights Hub, TagoIO, Rayven, TRACTIAN, Elastic Observability, SAP Business Technology Platform, Google Cloud IoT Core, and AWS IoT Analytics.

Underlying data: [Grid® JSON](https://www.g2.com/categories/iot-analytics-platforms/grids.json?focus%5B%5D=siemens-digital-industries-software-insights-hub&focus%5B%5D=tagoio&focus%5B%5D=rayven&focus%5B%5D=tractian-tractian&focus%5B%5D=elastic-observability&focus%5B%5D=sap-business-technology-platform&focus%5B%5D=google-cloud-iot-core&focus%5B%5D=aws-iot-analytics)

Insights Hub

Insights Hub is a solution for Data-Driven Manufacturing. It is designed to help users harness the power of data generated from assets and operations within smart manufacturing environments and implement a continuous improvement process. It leverages AI to transform raw data into actionable insights, enabling organizations to continuously enhance their manufacturing processes and make informed decisions that drive operational excellence. Targeted primarily at manufacturers and industrial operators, Insights Hub serves a diverse audience that includes equipment manufacturers, facility managers, and production teams. The solution addresses a variety of use cases, such as asset monitoring, performance optimization, quality improvement, and maintenance streamlining. By utilizing Insights Hub, organizations can gain a comprehensive understanding of their operations, identify inefficiencies, and implement strategies that lead to enhanced productivity and reduced costs. This makes it an essential tool for businesses looking to stay competitive in an increasingly data-driven industry. Insights Hub encompasses several key features that cater to specific operational needs. For instance, Insights Hub Monitor allows users to track asset performance in real-time, providing critical data that can inform maintenance schedules and operational adjustments. This feature is particularly beneficial for organizations aiming to minimize downtime and maximize the availability of their equipment. Insights Hub OEE focuses on overall equipment effectiveness, helping organizations analyze performance metrics to improve efficiency and reduce downtime. Additionally, Insights Hub Quality Prediction enhances quality inspection processes by utilizing predictive analytics to identify potential defects before they occur, thereby minimizing rework and waste. Insights Hub Asset Health and Maintenance is tailored for equipment manufacturers and operators, offering tools to streamline maintenance services and extend asset lifecycles. Insights Hub is also providing dedicated solutions to improve sustainability, leveraging Machine Learning to reduce energy and resource consumption. It also enhances traceability and facilitates containment of issues, avoiding negative impact on customers. By integrating these features, Insights Hub delivers significant value to its users. Insights Hub not only improves operational decision-making through data-driven insights but also fosters a culture of continuous improvement within manufacturing environments. The expanded portfolio, which includes software, IoT-connected hardware, and related services, allows customers and partners within the Siemens Xcelerator ecosystem to develop industry-specific applications tailored to their unique operational challenges. This adaptability ensures that Insights Hub remains relevant and effective in a rapidly evolving industrial landscape, positioning organizations to thrive in the era of smart manufacturing.

Average Rating: 4.5/5.0

Total Reviews: 66

How Do G2 Users Rate Insights Hub?

  • Ease of Use: 8.1/10 (Category avg: 8.9/10)
  • Quality of Support: 8.3/10 (Category avg: 8.9/10)

Who Is the Company Behind Insights Hub?

Who Uses This Product?

  • Top Industries: Industrial Automation, Food & Beverages
  • Company Size: 37% Large, 33% Small

What Do G2 Reviewers Say About Insights Hub?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Insights Hub, finding dashboards and reporting simpler and more intuitive.
  • Users love the centralized platform of Insights Hub, which effectively integrates data and enhances performance monitoring.
  • Users find Insights Hub to be incredibly user-friendly, simplifying data management and enhancing decision-making efficiency.
  • Users love the easy integrations of Insights Hub, enhancing data availability and supporting streamlined performance monitoring.
  • Users value the custom dashboards of Insights Hub for their intuitive design and ability to simplify data visualization.
Cons
  • Users find the learning curve steep, indicating a need for improved user-friendliness and smoother navigation.
  • Users desire more customization options for report designs in Insights Hub to enhance versatility and detail.
  • Users often face navigation issues in Insights Hub, finding the interface complex and experience not user-friendly.
  • Users find the poor usability of Insights Hub challenging due to its complex interface and navigation issues.
  • Users find difficult navigation in Insights Hub, requiring time or assistance to understand the platform effectively.

What Are Recent G2 Reviews of Insights Hub?

TagoIO

TagoIO is a full-stack IoT platform that simplifies how teams build and scale IoT applications, freeing them to focus on innovation instead of infrastructure. The platform combines ease of use with enterprise-grade capabilities, enabling businesses to connect, manage, and analyze device data at scale while maintaining full control over their solutions. Trusted by over 20,000 developers across 130+ countries, TagoIO powers IoT solutions in Agriculture, Energy, Buildings, Industrial, and Logistics. The same platform that accelerates a quick proof of concept can scale to millions of data points in global production, without lock-in, and with real human support along the way. Create a free account and start turning your ideas based on sensors, data, and analytics into solutions. For more information, visit www.tago.io.

Average Rating: 4.9/5.0

Total Reviews: 60

How Do G2 Users Rate TagoIO?

  • Ease of Use: 9.2/10 (Category avg: 8.9/10)
  • Quality of Support: 9.7/10 (Category avg: 8.9/10)

Who Is the Company Behind TagoIO?

  • Seller: TagoIO
  • Company Website:
  • Year Founded: 2014
  • HQ Location: Raleigh, US
  • Twitter: @tagoio
    878 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    24 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Industrial Automation, Information Technology and Services
  • Company Size: 78% Small, 13% Medium

What Do G2 Reviewers Say About TagoIO?

AI-generated summary from verified user reviews

Pros
  • Users find TagoIO incredibly easy to use, enjoying its seamless setup, helpful documentation, and responsive support.
  • Users appreciate the flexibility of TagoIO, praising its ease of use and ability to share dashboards effectively.
  • Users appreciate the user-friendly interface of TagoIO, making it easy to create IoT solutions efficiently.
  • Users value the custom dashboards of TagoIO, praising their ease of use and quick setup with templates.
  • Users value the easy integrations of TagoIO, enabling fast setup and seamless connectivity for IoT devices.
Cons
  • Users find the steep learning curve of TagoIO challenging, especially due to its extensive features and capabilities.
  • Users express concern over the high pricing, feeling that monthly costs for TagoIO could be reduced.
  • Users find the complexity of TagoIO can lead to tedious and repetitive tasks during dashboard configuration.
  • Users find the limited customization options in TagoIO restrictive, especially with device templates and dashboard widgets.
  • Users often struggle with poor documentation, making it challenging to grasp advanced features and troubleshoot effectively.

What Are Recent G2 Reviews of TagoIO?

Rayven

What is Rayven? Rayven is an operational software platform that delivers an AI data fabric - connecting every system, data source, and data stream across a business into a single managed environment, then letting teams build custom apps, AI agents, workflow automations, dashboards, and MCP servers for direct AI model connectivity on top. It is the platform for organisations that need to act on operational data in real-time, deploy AI that actually works in production + build software that fits the way their business operates - without replacing existing systems or waiting 18 months for results. The Problem Rayven Solves Most organisations already have the systems and data they need. The challenge is fragmentation. ERP systems, SCADA platforms, IoT devices, databases, cloud tools, and files all generate valuable data - but it sits in silos, impossible to act on in real-time. The result: manual reporting, disconnected workflows, and AI projects that fail before reaching production. Industry research shows 95% of AI projects never ship - most because the underlying data layer is not clean, connected, or ready. Rayven builds that foundation first, then activates it. The Rayven Platform Rayven operates across five unified layers, delivered as a single managed environment: - Integration: More than 600 pre-built connectors pull data from IT, OT, IoT, files, APIs, databases, and data streams - bidirectionally, in real-time. Connects industrial protocols (OPC UA, Modbus, MQTT, BACnet) alongside cloud platforms, business systems, and proprietary tools. - Data: All connected data lands in a single managed platform - structured, governed + AI-ready. Real-time processing, ETL pipelines, data lakes, and AI model training handled in one place. - Execution: Automation rules, predictive models + agentic AI run directly on live operational data. Rules-based logic, machine learning, and goal-seeking autonomous agents all operate in one execution environment. - Presentation: Custom apps, dashboards, portals, conversational interfaces, and mobile applications deployed from the same platform - built for specific workflows, not generic reporting. - Security, Governance + Hosting: Role-based access control, data lineage, audit trails, AES-256 encryption, data residency controls, and enterprise-grade infrastructure - included as standard. AI Capabilities Rayven includes ten native AI capabilities built directly into the platform: 1. Custom AI agents (goal-seeking, action-taking) 2. Predictive analytics and machine learning 3. Conversational analytics 4. Real-time and continuous model training 5. AI-led workflow automation 6. Multimodal processing (documents, video, images, audio) 7. Anomaly and risk detection 8. Forecasting and optimisation 9. Vision and edge AI inference 10. Generative operational summaries MCP server support enables direct connectivity for AI models including Claude, GPT, and others. What Gets Built Rayven customers build and deploy: - Custom operational apps and field applications. - AI agents that monitor conditions, detect anomalies + take corrective action autonomously. - Predictive maintenance and performance models running on live plant data. - Real-time dashboards and executive reporting tools. - Workflow automations spanning IT and OT systems. - Customer and partner portals. - Data pipelines and integration layers. - White-label software products delivered under partner brands. Key Differentiators vs. Point solutions (Zapier, MuleSoft, Power BI, DataRobot): point solutions do one thing well but force teams to stitch together five separate tools to cover integration, data, AI, presentation, and governance. Rayven replaces the stack. vs. Traditional enterprise platforms (SAP, Oracle, Palantir): enterprise platforms take 12-18 months and seven figures to implement. Rayven deploys in two to 12 weeks at fixed scope and fixed price. vs. Low-code app builders (Mendix, OutSystems): app builders handle the presentation layer but do not solve the underlying data and integration problem. Rayven covers the full stack. Technology Compatibility Rayven is fully technology-agnostic and works alongside existing systems: - Cloud platforms: Microsoft Azure, Google Cloud + AWS - Business systems: SAP, Salesforce, Oracle, and Microsoft 365 - OT platforms: Siemens, Rockwell, Schneider Electric, and Ignition - Industrial protocols: OPC UA, Modbus, MQTT, BACnet, and EtherNet/IP - IoT devices: any device with a data output - Custom and proprietary systems via API, webhook, or direct connector Nothing needs to be replaced. Every existing investment is preserved. Who Uses Rayven Rayven serves businesses from growth-stage to large enterprise across 24+ industries globally - manufacturing, mining, construction, infrastructure, logistics, utilities, financial services, healthcare, agriculture, government, and more. Customers across Australia, Europe, North America, South America, and Africa. Named customers include Anglo American, Fulton Hogan, Glencore, Vodafone, NSW Ports, CSIRO, Collective Intelligence, Ramjack, and AngloGold Ashanti. Delivery Options - DIY: Full platform access. Internal teams build and deploy independently. - Done-For-You: Australia-based delivery team. Fixed scope, fixed price, two to 12 weeks from brief to go-live. - Hybrid: Guided delivery first, with the customer's team taking increasing ownership over time. By the Numbers - More than 600 pre-built connectors. - Ten native AI capabilities. - More than 240 deployments live globally. - Rated 5/5 across more than 140 independent reviews. - Deploys 66% faster than traditional development. - Two to 12 weeks to first working solution. - Rayven exists to close the gap: 95% of AI projects never reach production (industry average).

Average Rating: 4.9/5.0

Total Reviews: 29

How Do G2 Users Rate Rayven?

  • Ease of Use: 9.9/10 (Category avg: 8.9/10)
  • Quality of Support: 9.9/10 (Category avg: 8.9/10)

Who Is the Company Behind Rayven?

  • Seller: Rayven
  • Year Founded: 2016
  • HQ Location: Sydney, AU
  • Twitter: @RayvenIOT
    56 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    32 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Retail
  • Company Size: 69% Medium, 52% Small

What Do G2 Reviewers Say About Rayven?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of Rayven, allowing seamless integration and workflow creation without coding skills.
  • Users value Rayven for its real-time data integration and seamless unification of various tools into one efficient system.
  • Users value Rayven's automation capabilities, enabling seamless integration and real-time data unification for improved performance tracking.
  • Users value the customization capabilities of Rayven, enabling tailored solutions to meet specific healthcare needs seamlessly.
  • Users value the robust data management of Rayven, enabling real-time processing and efficient automation across diverse systems.
Cons
  • Users report a steep initial learning curve due to complex setups and the need for technical knowledge.
  • Users find the difficult learning curve challenging due to overwhelming initial setup and complex feature configurations.
  • Users find the learning difficulty challenging due to the overwhelming initial setup and complex configuration processes.
  • Users find the complex setup of Rayven challenging, necessitating extensive planning for effective use and integration.
  • Users find the setup complexity challenging, often needing extra support for advanced integrations and configurations.

What Are Recent G2 Reviews of Rayven?

TRACTIAN

Tractian is the AI-powered platform for Predictive Maintenance and Production Performance chosen by 1,500 of the world’s most demanding manufacturers. We provide an end-to-end "Plug & Play" ecosystem that combines IoT sensors, software, and patented AI to protect operations and cut unplanned downtime. Trusted by global leaders like Bosch, KraftHeinz, Stellantis, Whirlpool, and Cummins, Tractian enables maintenance, reliability, and production teams to: ✔️Catch failures weeks in advance with real-time machine health monitoring ✔️Have full visibility of the plant through high-fidelity data sampled by industrial-grade sensors ✔️Meet demand and hit production goals with performance tracking ✔️Unify the shop floor with tools for maintenance and production teams Backed by its own security management system certified with ISO 27001 and SOC 2 Type II, Tractian can deliver up to 7x ROI in the first year and reduce unplanned downtime by 43%.

Average Rating: 4.7/5.0

Total Reviews: 54

How Do G2 Users Rate TRACTIAN?

  • Ease of Use: 9.0/10 (Category avg: 8.9/10)
  • Quality of Support: 9.4/10 (Category avg: 8.9/10)

Who Is the Company Behind TRACTIAN?

  • Seller: Tractian
  • Company Website:
  • Year Founded: 2019
  • HQ Location: Atlanta, GA
  • Twitter: @tractian
    523 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    889 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Manufacturing, Food & Beverages
  • Company Size: 43% Medium, 20% Small

What Do G2 Reviewers Say About TRACTIAN?

AI-generated summary from verified user reviews

Pros
  • Users commend the ease of use of TRACTIAN, highlighting its clear information and user-friendly integration process.
  • Users appreciate TRACTIAN for its real-time monitoring capabilities, enhancing equipment management and reducing downtime effectively.
  • Users highlight the timely and precise customer support of TRACTIAN, enhancing their overall experience and satisfaction.
  • Users value the efficiency of TRACTIAN, enhancing productivity and minimizing delays with easy-to-use machine health sensors.
  • Users appreciate TRACTIAN for its real-time monitoring, enhancing equipment maintenance and reducing unplanned downtime effectively.
Cons
  • Users find the complex usability of TRACTIAN challenging, particularly in setup and mobile interface navigation.
  • Users find the difficult learning curve of TRACTIAN hampers efficient use, especially for occasional users needing training.
  • Users feel the product is a bit expensive, requiring a budget increase and staff training for effective use.
  • Users find the learning curve steep, requiring extra training and adjustment time for effective use of TRACTIAN.
  • Users find the usability issues of TRACTIAN frustrating, especially on mobile devices and during setup.

What Are Recent G2 Reviews of TRACTIAN?

SAP Business Technology Platform

SAP Business Technology Platform (SAP BTP) is a multi-cloud platform-as-a-Service optimized to work with SAP solutions. It is a unified platform of technologies SAP uses for its own innovation, to extend and integrate business applications, and to infuse artificial intelligence and context-aware business data. SAP BTP brings together intelligent enterprise applications with database and data management, analytics, integration and extension capabilities into one platform for both cloud and hybrid environments, including hundreds of prebuilt business content and integrations for faster time-to-value. It can be used to create personalized experiences across business processes, build applications, analytics, and integrations faster, and to run mission-critical innovation confidently on major cloud providers' infrastructure fully managed by SAP. SAP BTP offers a range of capabilities and services that: - offers fit-for-purpose tools and services that are optimized for SAP applications along with composable bespoke business processes - provides an open environment with pre-built connectors to 3rd party apps and the availability to run on leading hyperscaler IaaS Clouds (AWS, Azure, GCP, etc.) connects AI & ML into business processes to enhance intelligence, automation, and productivity - delivers security and improved insights by keeping contextual data close to core business processes and applications - enables future-proofing by keeping core systems clean, greatly reducing technical debt to take advantage of cloud economics

Average Rating: 4.4/5.0

Total Reviews: 397

How Do G2 Users Rate SAP Business Technology Platform?

  • Ease of Use: 8.2/10 (Category avg: 8.9/10)
  • Quality of Support: 8.5/10 (Category avg: 8.9/10)

Who Is the Company Behind SAP Business Technology Platform?

  • Seller: SAP
  • Year Founded: 1972
  • HQ Location: Walldorf
  • Twitter: @SAP
    297,052 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    149,349 employees on LinkedIn®
  • Ownership: NYSE:SAP

Who Uses This Product?

  • Who Uses This: Software Engineer, System Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 39% Large, 36% Medium

What Do G2 Reviewers Say About SAP Business Technology Platform?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of SAP BTP, enabling seamless integration and intuitive app development in one platform.
  • Users value the seamless integrations of SAP BTP, enhancing connectivity and efficiency across various applications and services.
  • Users value the seamless integration capabilities of SAP Business Technology Platform, enabling effortless connections with various applications.
  • Users appreciate the comprehensive integration of SAP BTP, enabling seamless data management, app development, and enhanced flexibility.
  • Users appreciate the centralized data management of SAP BTP, seamlessly connecting tools and fostering innovation.
Cons
  • Users experience a significant learning curve with SAP BTP, making initial navigation and setup challenging for newcomers.
  • Users report a steep learning curve with SAP BTP, as its complexity can overwhelm newcomers to the platform.
  • Users find the pricing structure complex, making it difficult to monitor costs effectively with SAP BTP.
  • Users often face a steep learning difficulty with SAP BTP, especially those unfamiliar with SAP systems.
  • Users find the difficult learning curve of SAP BTP can be overwhelming, requiring extensive time and experience.

What Are Recent G2 Reviews of SAP Business Technology Platform?

What Are G2 Users Discussing About SAP Business Technology Platform?

Google Cloud IoT Core

A fully managed service to easily and securely connect, manage, and ingest data from globally dispersed devices

Average Rating: 4.1/5.0

Total Reviews: 29

How Do G2 Users Rate Google Cloud IoT Core?

  • Ease of Use: 7.7/10 (Category avg: 8.9/10)
  • Quality of Support: 8.3/10 (Category avg: 8.9/10)

Who Is the Company Behind Google Cloud IoT Core?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • Twitter: @google
    31,899,995 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG

Who Uses This Product?

  • Company Size: 47% Small, 33% Medium

What Are Recent G2 Reviews of Google Cloud IoT Core?

What Are G2 Users Discussing About Google Cloud IoT Core?

AWS IoT SiteWise

AWS IoT SiteWise is a managed service that makes it easy to collect and organize data from industrial equipment at scale. You can easily monitor equipment across your industrial facilities to identify waste, such as breakdown of equipment and processes, production inefficiencies, and defects in products.

Average Rating: 4.4/5.0

Total Reviews: 19

How Do G2 Users Rate AWS IoT SiteWise?

  • Ease of Use: 8.6/10 (Category avg: 8.9/10)
  • Quality of Support: 8.5/10 (Category avg: 8.9/10)

Who Is the Company Behind AWS IoT SiteWise?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 41% Small, 36% Large

What Are Recent G2 Reviews of AWS IoT SiteWise?

What Are G2 Users Discussing About AWS IoT SiteWise?

Elastic Observability

OpenTelemetry-native observability for fast, AI-driven root cause analysis Search, analyze, and act with logs, metrics, and traces. SRE leaders aim to proactively prevent downtime, simplify tool stacks, and reduce toil, but multi-cloud complexity and fragmented toolsets create visibility gaps that make it hard to stay ahead. OTel-native and AI-powered, Elastic Observability ingests and correlates petabytes of telemetry across your applications, services, and infrastructure, in real-time. Accelerate troubleshooting with built-in agentic workflows and an AI Assistant that goes well beyond chat to bolster team expertise and guide investigations, grounded with context from your organizational knowledge-bases. More data, more problems? Not anymore. Most observability and logging solutions weren’t built for today’s scale. Elastic is. Our architecture is designed to handle petabytes of logs with indexing, compression, and efficient searchable storage so you can keep all the telemetry you need, without breaking the bank. Store more, spend less, and resolve issues faster with a scalable, open, and extensible platform that unifies visibility across your entire environment.

Average Rating: 4.3/5.0

Total Reviews: 103

How Do G2 Users Rate Elastic Observability?

  • Ease of Use: 7.4/10 (Category avg: 8.9/10)
  • Quality of Support: 7.9/10 (Category avg: 8.9/10)

Who Is the Company Behind Elastic Observability?

  • Seller: Elastic
  • Company Website:
  • Year Founded: 2012
  • HQ Location: San Francisco, CA
  • Twitter: @elastic
    65,200 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    10,457 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Senior Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 50% Large, 43% Medium

What Do G2 Reviewers Say About Elastic Observability?

AI-generated summary from verified user reviews

Pros
  • Users find Elastic Observability to be intuitively easy to use, facilitating effortless integration and quick setup for various needs.
  • Users value the real-time alerting capabilities of Elastic Observability, enhancing proactive monitoring and issue resolution.
  • Users value the excellent log collection and monitoring capabilities of Elastic Observability for efficient server management.
  • Users appreciate the excellent monitoring capabilities of Elastic Observability for comprehensive insights into their applications and infrastructure.
  • Users value the flexibility and unified view of Elastic Observability, enhancing troubleshooting and operational visibility.
Cons
  • Users face a steep learning curve with Elastic Observability, requiring extensive knowledge and training for effective use.
  • Users find the difficult learning curve for Elastic Observability challenging, particularly for teams unfamiliar with the Elastic Stack.
  • Users struggle with the lack of log integration and find log generation with APM challenging without ELK knowledge.
  • Users find the learning difficulty frustrating, particularly due to overwhelming logs and advanced feature navigation.
  • Users struggle with log management issues, from hardware corruption to lack of integration with existing log files.

What Are Recent G2 Reviews of Elastic Observability?

What Are G2 Users Discussing About Elastic Observability?

AWS IoT Analytics

AWS IoT Analytics is a fully-managed service that makes it easy to run sophisticated analytics on massive volumes of IoT data without having to worry about all the cost and complexity typically required to build your own IoT analytics platform.

Average Rating: 4.5/5.0

Total Reviews: 17

How Do G2 Users Rate AWS IoT Analytics?

  • Ease of Use: 8.7/10 (Category avg: 8.9/10)
  • Quality of Support: 8.6/10 (Category avg: 8.9/10)

Who Is the Company Behind AWS IoT Analytics?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Company Size: 38% Large, 38% Small

What Are Recent G2 Reviews of AWS IoT Analytics?

What Are G2 Users Discussing About AWS IoT Analytics?

ThingSpeak

The open data platform for the Internet of Things

Average Rating: 4.3/5.0

Total Reviews: 15

How Do G2 Users Rate ThingSpeak?

  • Ease of Use: 8.3/10 (Category avg: 8.9/10)
  • Quality of Support: 8.6/10 (Category avg: 8.9/10)

Who Is the Company Behind ThingSpeak?

  • Seller: MathWorks
  • Year Founded: 1984
  • HQ Location: Natick, MA
  • Twitter: @MATLAB
    105,142 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    7,985 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 40% Medium, 33% Small

What Are Recent G2 Reviews of ThingSpeak?

What Are G2 Users Discussing About ThingSpeak?

Datadog

Datadog is the monitoring, security and analytics platform for developers, IT operations teams, security engineers and business users in the cloud age. The SaaS platform integrates and automates infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of our customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.

Average Rating: 4.4/5.0

Total Reviews: 715

How Do G2 Users Rate Datadog?

  • Ease of Use: 8.2/10 (Category avg: 8.9/10)
  • Quality of Support: 8.4/10 (Category avg: 8.9/10)

Who Is the Company Behind Datadog?

  • Seller: Datadog
  • Company Website:
  • Year Founded: 2010
  • HQ Location: New York
  • Twitter: @datadoghq
    51,207 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    10,780 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, DevOps Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 47% Medium, 34% Large

What Do G2 Reviewers Say About Datadog?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Datadog, enjoying intuitive dashboard creation and straightforward implementation.
  • Users appreciate the intuitive monitoring features of Datadog, enabling easy integration and insightful data analysis.
  • Users value the real-time monitoring capabilities of Datadog, enhancing oversight across various applications and infrastructures.
  • Users appreciate the user-friendly interface and robust integration capabilities of Datadog for effective monitoring.
  • Users value the intuitive dashboard creation in Datadog, which enhances monitoring and analysis efficiency.
Cons
  • Users find Datadog's pricing to be expensive, suggesting it should be more affordable given its features.
  • Users find pricing issues with Datadog, citing rapidly escalating costs and high subscription fees as concerns.
  • Users find the steep learning curve challenging, especially with rapidly evolving features and required knowledge.
  • Users find the costs to be unpredictable and excessively high, especially with data storage and additional features.
  • Users find learning difficulty in Datadog, noting that new users may require training to understand its complexities.

What Are Recent G2 Reviews of Datadog?

What Are G2 Users Discussing About Datadog?

Seeq

Seeq is a global leader in industrial AI that brings together operational data, human expertise, and AI to help industrial organizations accelerate better decisions and measurable outcomes. Seeq captures and connects the knowledge of subject matter experts, making proven approaches easier to access, apply, and scale across teams, assets, and sites. With transparent, traceable AI, Seeq helps organizations move from insight to action while keeping human judgment at the center. Trusted by leading industrial companies, Seeq supports improvements in reliability, efficiency, sustainability, workforce productivity, and profitability. Seeq helps every industrial decision benefit from collective knowledge, operational context, and intelligent action.

Average Rating: 4.6/5.0

Total Reviews: 145

How Do G2 Users Rate Seeq?

  • Ease of Use: 8.5/10 (Category avg: 8.9/10)
  • Quality of Support: 9.2/10 (Category avg: 8.9/10)

Who Is the Company Behind Seeq?

  • Seller: Seeq Corporation
  • Company Website:
  • Year Founded: 2013
  • HQ Location: Seattle, Washington
  • Twitter: @SeeqCorporation
    959 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    325 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Process Engineer
  • Top Industries: Oil & Energy, Chemicals
  • Company Size: 58% Large, 32% Medium

What Do G2 Reviewers Say About Seeq?

AI-generated summary from verified user reviews

Pros
  • Users value the capability to analyze and visualize complex data sets effectively with Seeq's user-friendly design.
  • Users appreciate the ease of use of Seeq, as it simplifies data analysis for professionals across various fields.
  • Users value the transformative capabilities of Seeq in delivering actionable insights for enhanced decision-making and performance.
  • Users appreciate the intuitive analysis capabilities of Seeq, making it easy to explore and identify data trends.
  • Users value the intuitive and robust data visualization capabilities of Seeq, enhancing both analysis and reporting.
Cons
  • Users find the complex usability of Seeq challenging, especially when visualizing LIMS and time series data.
  • Users find the difficult learning curve of Seeq challenging, especially when trying to navigate the tool independently.
  • Users find the learning curve steep, especially when navigating the tool without guidance, requiring engineering knowledge for full usage.
  • Users find the learning difficulty of Seeq to be challenging, especially when trying to master its formula functions.
  • Users find complexity in scaling analysis and integrating features, which hinders their overall experience with Seeq.

What Are Recent G2 Reviews of Seeq?

What Are G2 Users Discussing About Seeq?

TrendMiner

TrendMiner offers a fast, powerful, and intuitive industrial analytics & AI software platform. With a focus on highly digitized manufacturing industries, energy companies, and organizations with operations that need to maintain controlled environments. TrendMiner combines self-service, low-code data analysis for time series and event data with sophisticated machine learning (ML) and Agentic AI tools to deliver industrial data visualization, monitoring, and predictive capabilities. TrendMiner, a Vercore company, was founded in 2008 with a global headquarters located in Belgium, and offices in the U.S., Germany, Spain, and the Netherlands. TrendMiner has strategic partnerships with Amazon, Microsoft, SAP, GE Digital, Siemens, and Aveva, and offers standard integrations with a wide range of data platforms such as AVEVA PI, Yokogawa Exaquantum, AspenTech IP.21, Honeywell PHD, GE Proficy Historian, Canary, and Aveva Historian.

Average Rating: 4.6/5.0

Total Reviews: 182

How Do G2 Users Rate TrendMiner?

  • Ease of Use: 8.8/10 (Category avg: 8.9/10)
  • Quality of Support: 9.2/10 (Category avg: 8.9/10)

Who Is the Company Behind TrendMiner?

  • Seller: TrendMiner
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Hasselt, Flemish Region
  • Twitter: @TrendMining
    777 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    89 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Process Analytics Engineer, Process Engineer
  • Top Industries: Chemicals, Oil & Energy
  • Company Size: 53% Large, 35% Medium

What Do G2 Reviewers Say About TrendMiner?

AI-generated summary from verified user reviews

Pros
  • Users value the intuitive design of TrendMiner, making it easy to navigate and enhancing their overall experience.
  • Users value the speed of TrendMiner, enabling quick insights and efficient data analysis.
  • Users love the easy-to-create dashboards in TrendMiner, enhancing their ability to visualize important process data over time.
  • Users value the intelligent data analysis capabilities of TrendMiner, enhancing decision-making and improving performance efficiently.
  • Users find TrendMiner's easy learning curve enhances their analytics process, enabling self-service analysis effortlessly.
Cons
  • Users find complex usability in TrendMiner, struggling with connectivity and inadequate training materials for new users.
  • Users find the difficult learning curve of TrendMiner frustrating, as advanced features demand significant technical expertise.
  • Users find the learning curve steep, as mastering TrendMiner's extensive features requires significant time and training.
  • Users find the limited accessibility of TrendMiner challenging, especially due to the absence of a mobile app.
  • Users find the complexity of advanced functions in TrendMiner necessitating training and cumbersome system administration.

What Are Recent G2 Reviews of TrendMiner?

What Are G2 Users Discussing About TrendMiner?

dataPARC

dataPARC is a self-service industrial data visualization & analytics toolkit designed for process manufacturers seeking to improve quality, increase yield, & optimize their operations. Collect, connect, & analyze IoT data from across the plant with dataPARC’s process data analytics & visualization platform. Solve challenging process & product quality issues with simple, yet powerful trending & diagnostic analytics tools. Build sophisticated dashboards and displays to monitor processes & share production KPIs across your enterprise. Leverage artificial intelligence (AI) and machine learning to drive continuous improvement & increase margins via predictive modelling.

Average Rating: 4.9/5.0

Total Reviews: 39

How Do G2 Users Rate dataPARC?

  • Ease of Use: 9.1/10 (Category avg: 8.9/10)
  • Quality of Support: 9.6/10 (Category avg: 8.9/10)

Who Is the Company Behind dataPARC?

  • Seller: dataPARC
  • Year Founded: 1997
  • HQ Location: Washougal, US
  • Twitter: @dataPARCsolutio
    26 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    110 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Paper & Forest Products
  • Company Size: 62% Medium, 31% Large

What Do G2 Reviewers Say About dataPARC?

AI-generated summary from verified user reviews

Pros
  • Users value the customizability of dataPARC, allowing personalized displays and extensive functionality for all skill levels.
  • Users value the speed and extensive data analysis capabilities of dataPARC, enhancing their productivity and efficiency.
  • Users value the intuitive data visualization features of dataPARC, enhancing their ability to monitor and analyze information effectively.
  • Users commend the ease of use of dataPARC, citing its intuitive layout and minimal training requirements.
  • Users value the versatile software depth of dataPARC, catering to both novices and experienced users effectively.
Cons
  • Users find the complex usability of dataPARC challenging, particularly when needing more VB language examples and explanations.
  • Users find the data management issues in dataPARC challenging, particularly due to insufficient VB language support and examples.
  • Users find difficult learning due to insufficient examples and explanations in DataParc's VB documentation for beginners.
  • Users find the learning curve steep due to a lack of examples and detailed VB language explanations in dataPARC.
  • Users feel the need for more in-depth tutorials on VB to enhance their experience with dataPARC's functionality.

What Are Recent G2 Reviews of dataPARC?

What Are G2 Users Discussing About dataPARC?

Cisco Edge Intelligence

Connect, automate, and scale with Cisco Kinetic

Average Rating: 4.5/5.0

Total Reviews: 13

How Do G2 Users Rate Cisco Edge Intelligence?

  • Ease of Use: 8.0/10 (Category avg: 8.9/10)
  • Quality of Support: 8.0/10 (Category avg: 8.9/10)

Who Is the Company Behind Cisco Edge Intelligence?

  • Seller: Cisco
  • Year Founded: 1984
  • HQ Location: San Jose, CA
  • Twitter: @Cisco
    720,366 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    95,294 employees on LinkedIn®
  • Ownership: NASDAQ:CSCO

Who Uses This Product?

  • Company Size: 57% Small, 21% Medium

What Are Recent G2 Reviews of Cisco Edge Intelligence?

Bijou Barry
BB
Researched and written by Bijou Barry
Updated October 3, 2024

IoT Analytics Topics

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Learn More About IoT Analytics Platforms

What are IoT Analytics Platforms?

Data analytics is at the core of the Internet of Things (IoT), alongside process automation and asset management. Equipping machinery, office space, transport vehicles, and other things with smart sensors allows organizations to gather more data and glean more insight than ever before. Additionally, it shows how various assets perform and interact with one another. IoT analytics platforms help business leaders unlock actionable insights so they can learn about their operations and how to effectively optimize them from every angle.

For a connected business, there might be hundreds or thousands of advanced data sets to ingest each day. This data might include information about how devices are used, working conditions, and prescriptive analytics. The platforms in this fast-growing category offer methods for visualizing, analyzing, organizing, and exploring real-time and historical data generated by disparate IoT devices. Most businesses collect overwhelming amounts of enterprise IoT data. These solutions help determine the most relevant and actionable insights based on connected applications and their corresponding strategies and goals.

Key Benefits of IoT Analytics Platforms

  • Synthesize data generated by a network of smart devices and IoT sensors
  • Maximize ROI for diverse connected platforms across an organization
  • Shape operational strategies using prescriptive and predictive analytics
  • Identify the most relevant insights for data analytics and translate them into visualizations for easy consumption and analysis
  • Make noteworthy data points from IoT networks searchable and accessible for future reference

Why Use IoT Analytics Platforms?

Digital transformation is increasingly focused on connected devices, artificial intelligence, and other solutions to make workplaces automated and efficient. Smart devices—from factory machinery to office appliances—can assist with task automation as well as reveal insights about a company, building, employees, and customers. Connected assets help track details related to output, performance, and engagement with software platforms, employees, customers, and other applications connected to a network. IoT analytics solutions empower business users to sort and make sense of these findings. They can learn more about their business operations from the perspective of everyday “things" used across the company, regardless of their cost, size, or function.

Many platforms in this category offer tools to view and convert raw data into shareable formats. In some cases this entails integrations with data visualization software, business intelligence platforms, or other tools used for data analytics. In addition to gathering and preparing valuable data from smart devices, some platforms provide tools for real-time monitoring and reporting, helping users make instant decisions based on momentary events. The real-time streaming of powerful insights helps decision makers adjust and improve processes when these devices are involved, without waiting for lengthy reports.

Thanks to modern edge computing technology, the data gathered on these platforms can be processed and stored on the edge of company networks rather than centralized data warehouses. This helps deliver the right data at a faster rate, without eating into the bandwidth of critical systems. To establish an edge computing scenario for IoT devices and the data they collect, a business must configure edge devices (e.g., routers, integrated access devices or IADs) that control the flow of data. As a company builds out their IoT, analytics platforms help unlock the full potential of these devices without compromising the performance of their assets or IT infrastructures. A number of IoT platforms include analytics solutions or certain reporting features, but dedicated analytics platforms such as those in this category offer deeper insights related to IoT devices, networks, and more related functions in an organization.

Who Uses IoT Analytics Platforms?

The extensive insights from IoT analytics platforms are valuable to everyone in an organization; these insights influence strategic decisions and help the company improve business outcomes. However, only select individuals are typically trained to use these platforms, understand the data, and communicate the findings. The following teams or individuals are the most likely users of IoT analytics platforms.

IoT specialists — As the popularity of IoT grows, so does the need for dedicated experts within an organization. New positions such as IoT architect and IoT engineer are prioritized in thousands of tech-forward businesses. Individuals taking focused courses or training on smart technology and its applications may be recruited by an organization to fill an emerging role. In many cases, managers train existing employees so they can take on new responsibilities related to IoT strategy, such as tracking and comprehension of IoT analytics. The exact job titles of these individuals may vary based on the company’s unique approach to the focus area. Internal IoT specialists likely use platforms in this category. These platforms are essential for maximizing the value of IoT investments and making strategic decisions based on smart object activity. If a company designates one or more employees as IoT specialists, the right analytics tool can make a significant impact and convert IoT activity into actionable insights.

Data scientists and analysts — Depending on the size and scope of a company’s IoT infrastructure, they may not designate team members to be purely focused on IoT. In these cases, they may distribute related tasks and responsibilities to different teams or employees. Analytics experts, such as data analysts and data scientists, might be tasked with observing IoT data and determining appropriate responses to these findings. In addition to their existing analytics software and other business tools they use, data experts utilize IoT analytics platforms to observe, sort, and share unique insights generated by smart devices and any asset configured with an IoT sensor. In some cases, these findings are exported to other platforms for further studying, storing, or sharing. An IoT analytics platform can be essential for consuming the continuous stream of data connected devices produce, such as time-series data and streaming data from critical equipment on a factory line. Additionally, these platforms assist with modeling and blending unique data sets for optimal analysis.

IoT development firms — Internet of things developers, or IoT developers, are agencies that specialize in designing and deploying smart applications to use in an organization. These experts offer custom manufacturing of IoT objects and help configure new IoT networks. When working with one of these agencies, a business may need additional assistance with testing, troubleshooting, and tracking devices and IoT activity. IoT development teams might leverage a data analytics platform to visualize the findings of connected objects at any point in the customer experience, so customers can yield desired results with their IoT strategies.

IoT Analytics Platform Features

The diverse platforms in this category offer a unique set of tools to assist with IoT data analytics. The following are primary features common in this category of software platform.

Data models and customization — IoT analytics solutions often come with data models for organizing and standardizing information generated by connected devices. Data modeling is useful for revealing relationships between large sets of unorganized data so users can draw conclusions. With some platforms, users can customize data models or configure entirely new models to fit their particular needs. Models may be useful for observing logical relationships within data sets, and determining how data is retrieved, stored, and formatted.

Ingestion and filtering — IoT sensors enable objects to generate limitless data; this increases based on the portfolio of devices in the network. IoT analytics platforms usually include filtering and ingestion tools, allowing users to collect the most relevant data points. When determining how data is ingested from IoT devices, users can decide whether specific types of data will be used immediately or filed away for later use. In some cases, users can create dashboards for real-time data streaming including location and what settings are most beneficial at the time.

Event scheduling and alerts — Along with determining which data should be collected, users of IoT analytics platforms can determine when to generate reports. Scheduling analytics readings could revolve around a specific time schedule, or particular events. Users might track IoT data in response to alerts such as environmental changes or equipment issues. In other cases, they may simply want to schedule data ingestion for a particular time to make basic observations about patterns and performance. Companies can elect to pull data in a variety of ways and adjust their analytics strategy over the course of their IoT campaign. The platforms in this category offer a number of configurations for reporting to suit these needs.

Potential Issues with IoT Analytics Platforms

Data gaps — In addition to taking systems offline at unexpected and inconvenient times, random lapses in connectivity cause inconsistencies in time-series data. For example, you may notice several hours between two data points where there would normally be a steady, uninterrupted time line of data. These random gaps can be a source of frustration when it comes to studying and drawing conclusions. To prevent this, IT experts should monitor edge networks and routers and proactively address any issues.

False or corrupted readings — The more end points a company adds to its IoT stack, the greater the potential for transmission issues from an individual sensor. This is an unfortunate risk of any new technology, when it comes to IoT, these possibilities are multiplied by the number of devices they enable. A false reading can happen for a number of reasons, inaccurate data point can corrupt the integrity of data sets. It’s important to perform audits on data and run as many tests as possible to quickly identify issues, before problematic devices contribute additional false readings. Regular software updates are critical to keep distributed smart devices updated, reducing the chances of incomplete or inaccurate data.