# Best IoT Analytics Platforms - Page 9 *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)* IoT analytics platforms allows businesses to analyze and visualize sensor data from internet-connected devices. IoT analytics platofrms are used to understand the continuous stream of structured, unstructured, and time series data produced by connected devices, so that businesses can understand historical data and predict future outcomes. Companies may utilize IoT analytics solutions to track the performance of machinery, provide predictive maintenance recommendations, and better understand unique data related to their devices such as temperature, motion, and sound. Data analysts can use IoT analytics platforms to prepare, filter, transform, and drill into sensor data, the same way they would analyze structured data with a [business intelligence platform](https://www.g2.com/categories/business-intelligence-platforms). To qualify for inclusion in the IoT Analytics Platforms category, a product must: - Consume data directly from internet-connected devices, sensors, and time series databases - Support data modeling, blending, and discovery - Allow users to drill down into the data with interactive visualization - Create reports and visualizations based on the data ## How Many IoT Analytics Platforms Products Does G2 Track? **Total Products under this Category:** 139 ### Category Stats (May 2026) - **Average Rating**: 4.41/5 (↑0.01 vs Apr 2026) - **New Reviews This Quarter**: 11 - **Buyer Segments**: Small-Business 38% │ Mid-Market 31% │ Enterprise 31% - **Top Trending Product**: Rayven (+0.039) *Last updated: May 18, 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 - 139+ 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. ## Which IoT Analytics Platforms Is Best for Your Use Case? - **Leader:** [Insights Hub](https://www.g2.com/products/siemens-digital-industries-software-insights-hub/reviews) - **Highest Performer:** [dataPARC](https://www.g2.com/products/dataparc/reviews) - **Easiest to Use:** [dataPARC](https://www.g2.com/products/dataparc/reviews) - **Top Trending:** [ThingSpeak](https://www.g2.com/products/thingspeak/reviews) - **Best Free Software:** [SAP Business Technology Platform](https://www.g2.com/products/sap-business-technology-platform/reviews) ## What Is IoT Analytics Platforms? [IoT Management Platforms](https://www.g2.com/categories/iot-management) ## What Software Categories Are Similar to IoT Analytics Platforms? - [IoT Platforms](https://www.g2.com/categories/iot-platforms) - [IoT Device Management Platforms](https://www.g2.com/categories/iot-device-management-platforms) - [Manufacturing Intelligence Software](https://www.g2.com/categories/manufacturing-intelligence) - [Industrial IoT Software](https://www.g2.com/categories/industrial-iot) --- ## How Do You Choose the Right IoT Analytics Platforms? ### What You Should Know About IoT Analytics Platforms ### What are IoT Analytics Platforms? Data analytics is at the core of the Internet of Things (IoT), alongside [process automation](https://www.g2.com/categories/process-automation) and [asset management](https://www.g2.com/categories/asset-management-f3e79baa-6f93-4d40-b734-16e9b562fc14). 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](https://www.g2.com/categories/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](https://www.g2.com/categories/data-visualization), [business intelligence platforms](https://www.g2.com/categories/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](https://www.g2.com/categories/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](https://www.g2.com/categories/analytics) 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](https://www.g2.com/categories/internet-of-things-iot-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. ### Software and Services Related to IoT Analytics Platforms Realizing the benefits of smart technology is a significant undertaking. There is a great deal of planning, training, and investment that goes into an IoT initiative, including collecting and securing data from distributed platforms. Business leaders should do considerable research on the different types of [IoT management software](https://www.g2.com/categories/iot-management) and services on the market, and work with a consulting firm to determine which solutions to prioritize. The following are professional solutions that complement IoT analytics tools. They all help companies collect insights about their modern systems, and optimize their operation using groundbreaking technology. [**Stream analytics software**](https://www.g2.com/categories/stream-analytics) **—** Stream analytics, also known as streaming analytics, is the study of data transferred between applications and exchanges, both historically and in real time. Stream analytics software enables the capture and analysis of this information. These platforms allow users to understand the flow and retrieval of data by disparate end points. A major use case for this is monitoring IoT telemetry across end points and the events pertaining to information exchange. If data is not received correctly, users of stream analytics tools can be notified and given insights into streaming issues. The platforms in this category are a natural complement to IoT analytics platforms, ensuring companies stay informed about the continuous flow of information between connected objects so devices can reliably execute tasks and generate their own insights. [**Big data analytics software**](https://www.g2.com/categories/big-data-analytics) **—** Big data analytics involves the consumption of massive data clusters, culling the most notable findings using advanced data queries. Big data and [big data software](https://www.g2.com/categories/big-data) are increasingly common across a number of industries. With the rise of IoT, substantial data clusters are the focus of big data analytics and include observable information that can be exported from smart devices. If a business desires to analyze IoT data as part of a larger pool of data, they might consider a big data analytics tool such as those featured in this category. While IoT analytics solutions offer actionable insights into specific data generated by connected platforms, big data analytics can study these findings in relation to other critical data collected from various sources. This practice paints a more complete picture of relevant data patterns across the operation. Users can create detailed visualizations and record their queries into data sets to share discoveries with internal teams, business partners, and investors. Some platforms offer specific features for monitoring IoT data and collections of big data. [**IoT device management software**](https://www.g2.com/categories/iot-device-management) **—** Depending on the size and scope of IoT strategy, hundreds or thousands of devices are configured to work together and communicate information with one another and the network itself. Proper management, troubleshooting, and updates to these devices is essential for accurate data collection. This ensures each device performs the expected actions and generates the right insights. After designing and deploying an IoT network using [IoT platforms](https://www.g2.com/categories/iot-platforms), businesses may use IoT device management tools to monitor the state of their devices and maintain them as needed. At the very least, these platforms assist with pushing software and firmware updates required with certain devices and sensors. IoT device management tools provide assistance with device permissions and device vulnerability tracking, among other things. To receive the best possible data from smart devices, IT administrators need to make a consistent effort toward device tracking and organization. IoT device managers help prepare teams for success and ensure they maintain visibility and control over a company’s IoT infrastructure. [**IoT security services providers**](https://www.g2.com/categories/iot-security-services) **—** The power of IoT and device analytics comes paired with the responsibility of keeping these systems protected from unwanted access, theft, viruses, and other threats. Smart connectivity is a term used to describe the reliable connection of complex networks, including those used in edge computing and IoT networks. This connectivity requires reliable, uninterrupted transmission of data, and the ability to withstand environmental influences and malicious activity. Companies might require lots of outside assistance to supplement internal efforts and maintain a high degree of reliability. This is where IoT security services can help. IoT security providers are specialized firms that help companies configure IoT systems for optimum performance and consistency in the face of untold threats. Cybercrime is evolving, especially as new vulnerabilities are introduced. The specialists in this category can be enlisted to keep systems updated, adding or adjusting layers of protection based on the changing landscape of potential dangers. When mapping out a security strategy, businesses might also consider [data security services](https://www.g2.com/categories/data-security-services) to bolster internal defense efforts. Data security experts can assist with protecting large volumes of critical business data, up to and including data sets generated by smart objects. A number of IoT security services providers offer solutions for protecting IoT data from external threats. A company might desire a more comprehensive program that touches on all aspects of data protection and the various groupings of data a business might collect. Data services providers can offer strategic advice, train employees on security practices, and assist with the implementation of [security software](https://www.g2.com/categories/security) so teams can maintain a consistent level of protection for data and company systems using internal resources. In some cases they can remotely monitor and respond to data-related threats in a business. In the current age, there is no limit to the security measures a company should consider, especially as operations are increasingly built on a foundation of technology. Compromised data, including IoT-related analytics, can be detrimental to a business and also place its employees and customers at serious risk. When adopting an IoT strategy, managers should take measures to keep assets and business data as safe as possible.