Alternatives to Embiot

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

icCube, a Swiss-made analytics solution, is crafted for B2B SaaS product and development teams aiming to integrate advanced analytics directly into their applications. Our dashboards are designed to merge effortlessly within the SaaS solution's UI and UX, powered by icCube’s strong analytical engine, which supports complex data models with high-level security features. Adopting a developer-to-developer approach, the icCube team guides clients to ensure a smooth, rapid transition to production. We recognize the challenges of data navigation, so we’re thrilled to offer our Data Analytics Boutique Services. Tailored for both new and existing clients, this suite provides seamless data integration, fortified security, deep insights, automated decision-making, and visually impactful reports. At every project stage and throughout the product lifecycle, we partner closely with our clients, from providing quick feedback to full project and product launches.

Open Automation Software IIoT platform Windows and Linux allows you to liberate your Industry4.0 data. OAS is an unlimited IoT Gateway that works with Windows, Linux, Raspberry Pi 4 and Windows IoT Core. It can also be used to deploy Docker containers. HMI visualizations for web, WPF, WinForm C#, and VB.NET applications. Log data and alarms to SQL Server and MS Access, SQL Server, Oracle and MS Access, MySQL and Azure SQL, PostgreSQL and Cassandra. MQTT Broker and Client interface, as well as cloud connectivity to Azure IoT Gateway and AWS IoT Gateway. Remote Excel Workbooks can be used to read and write data. Notifications of alarm sent to voice, SMS text and email. Access to programmatic information via REST API and.NET Allen Bradley ControlLogix and CompactLogix, GuardLogix. Micro800, MicroLogix. MicroLogix. SLC 500. PLC-5. Siemens S7-220, S7-3300, S7-405, S7-490, S7-1200, S7-1500, and S7-1500 Modbus TCP and Modbus RTU are Modbus ASCII and Modbus TCP for Master and Slave communication. OPTO-22, MTConnect and OPC UA, OPC DA.

Instant™, Enterprise Data and Intelligence. All transaction data is visible, as it happens, from anywhere in the world. Organizations can access worldwide accounting, liquidity management, marketing, and supply chain information with just one network connection. This allows them to be empowered with enterprise intelligence. The TreasuryPay product set streams global receivables information and provides instant accountancy as well as cognitive services. It is simply the most advanced intelligence platform and insights platform available to global organizations. You can instantly provide enriched information to your entire global organization. It's easy to make the change. The Return on Investment is remarkable. With TreasuryPay Instant™, you can now access actionable intelligence and global accountancy in real-time.

Cumulocity IoT stands out as the premier low-code, self-service IoT platform, uniquely offering pre-integration with essential tools for rapid outcomes, including device connectivity and management, application enablement, integration, and advanced analytics for both streaming and predictive insights. Break free from restrictive proprietary technology ecosystems, as this platform is entirely open, allowing you to connect any device today or in the future. Customize your setup by bringing your own hardware and selecting the components that suit your needs best. You can quickly jump into the IoT world within minutes by connecting a device, monitoring its data, and crafting an interactive dashboard in real-time. Additionally, you can establish rules to oversee and respond to events—all without needing IT assistance or writing any code! Effortlessly integrate fresh IoT data into the existing core enterprise systems, applications, and processes that have supported your business for years, again without the need for coding, ensuring seamless data flow. This capability enhances your understanding, providing you with richer context to make informed decisions and improve overall business outcomes.

EMQX is the world's most scalable and reliable MQTT messaging platform designed by EMQ. It supports 100M concurrent IoT device connections per cluster while maintaining extremely high throughput and sub-millisecond latency. EMQX boasts more than 20,000 global users from over 50 countries, connecting more than 100M IoT devices worldwide, and is trusted by over 300 customers in mission-critical IoT scenarios, including well-known brands like HPE, VMware, Verifone, SAIC Volkswagen, and Ericsson. Our edge-to-cloud IoT data solutions are flexible to meet the demands of various industries towards digital transformation, including connected vehicles, Industrial IoT, oil & gas, carrier, finance, smart energy, and smart cities. EMQX Enterprise: The World’s # 1 Scalable MQTT Messaging Platform -100M concurrent MQTT connections -1M/s messages throughput under 1ms latency -Business-critical reliability, Up to 99.99% SLA -Integrate IoT data seamlessly with over 40 cloud services and enterprise systems EMQX Cloud: Fully Managed MQTT Service for IoT - Scale as you need, pay as you go - Flexible and rich IoT data integration up to 40+ choices - Run in 19 regions across AWS, GCP, and Microsoft Azure - 100% MQTT

In the field of IoT stream processing and analytics, SQLstream ranks #1 according to ABI Research. Used by Verizon, Walmart, Cisco, and Amazon, our technology powers applications on premises, in the cloud, and at the edge. SQLstream enables time-critical alerts, live dashboards, and real-time action with sub-millisecond latency. Smart cities can reroute ambulances and fire trucks or optimize traffic light timing based on real-time conditions. Security systems can detect hackers and fraudsters, shutting them down right away. AI / ML models, trained with streaming sensor data, can predict equipment failures. Thanks to SQLstream's lightning performance -- up to 13 million rows / second / CPU core -- companies have drastically reduced their footprint and cost. Our efficient, in-memory processing allows operations at the edge that would otherwise be impossible. Acquire, prepare, analyze, and act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code, GUI dev environment. Edit scripts instantly and view instantaneous results without compiling. Deploy with native Kubernetes support. Easy installation includes Docker, AWS, Azure, Linux, VMWare, and more

KX Streaming Analytics offers a comprehensive solution for ingesting, storing, processing, and analyzing both historical and time series data, ensuring that analytics, insights, and visualizations are readily accessible. To facilitate rapid productivity for your applications and users, the platform encompasses the complete range of data services, which includes query processing, tiering, migration, archiving, data protection, and scalability. Our sophisticated analytics and visualization tools, which are extensively utilized in sectors such as finance and industry, empower you to define and execute queries, calculations, aggregations, as well as machine learning and artificial intelligence on any type of streaming and historical data. This platform can be deployed across various hardware environments, with the capability to source data from real-time business events and high-volume inputs such as sensors, clickstreams, radio-frequency identification, GPS systems, social media platforms, and mobile devices. Moreover, the versatility of KX Streaming Analytics ensures that organizations can adapt to evolving data needs and leverage real-time insights for informed decision-making.

IBM® StreamSets allows users to create and maintain smart streaming data pipelines using an intuitive graphical user interface. This facilitates seamless data integration in hybrid and multicloud environments. IBM StreamSets is used by leading global companies to support millions data pipelines, for modern analytics and intelligent applications. Reduce data staleness, and enable real-time information at scale. Handle millions of records across thousands of pipelines in seconds. Drag-and-drop processors that automatically detect and adapt to data drift will protect your data pipelines against unexpected changes and shifts. Create streaming pipelines for ingesting structured, semistructured, or unstructured data to deliver it to multiple destinations.

The Hitachi Streaming Data Platform (SDP) is engineered for real-time processing of extensive time-series data as it is produced. Utilizing in-memory and incremental computation techniques, SDP allows for rapid analysis that circumvents the typical delays experienced with conventional stored data processing methods. Users have the capability to outline summary analysis scenarios through Continuous Query Language (CQL), which resembles SQL, thus enabling adaptable and programmable data examination without requiring bespoke applications. The platform's architecture includes various components such as development servers, data-transfer servers, data-analysis servers, and dashboard servers, which together create a scalable and efficient data processing ecosystem. Additionally, SDP’s modular framework accommodates multiple data input and output formats, including text files and HTTP packets, and seamlessly integrates with visualization tools like RTView for real-time performance monitoring. This comprehensive design ensures that users can effectively manage and analyze data streams as they occur.

FairCom EDGE makes it easy to integrate sensor and machine data at their source - be that a factory, water treatment facility, oil platform, wind farm, or other industrial site. FairCom EDGE is the first converged IoT/Industrial IoT hub in the world. It unifies messaging and persistence with an all-in one solution. It also offers browser-based administration, configuration, and monitoring. FairCom EDGE supports MQTT, OPC UA and SQL for machine-tomachine (M2M), communication, and HTTP/REST for monitoring and real-time reporting. It constantly retrieves data from sensors and devices with OPC UA support and receives messages from machines with MQTT support. The data is automatically parsed and persisted, and made available via MQTT or SQL.

The significance of streaming data derived from operations, transactions, sensors, and IoT devices becomes apparent when it is thoroughly comprehended. SAS's event stream processing offers a comprehensive solution that encompasses streaming data quality, analytics, and an extensive selection of SAS and open source machine learning techniques alongside high-frequency analytics. This integrated approach facilitates the connection, interpretation, cleansing, and comprehension of streaming data seamlessly. Regardless of the velocity at which your data flows, the volume of data you manage, or the diversity of data sources you utilize, you can oversee everything effortlessly through a single, user-friendly interface. Moreover, by defining patterns and addressing various scenarios across your entire organization, you can remain adaptable and proactively resolve challenges as they emerge while enhancing your overall operational efficiency.

Effortlessly gather, manage, and scrutinize video and data streams as they occur. Amazon Kinesis simplifies the process of collecting, processing, and analyzing streaming data in real-time, empowering you to gain insights promptly and respond swiftly to emerging information. It provides essential features that allow for cost-effective processing of streaming data at any scale while offering the adaptability to select the tools that best align with your application's needs. With Amazon Kinesis, you can capture real-time data like video, audio, application logs, website clickstreams, and IoT telemetry, facilitating machine learning, analytics, and various other applications. This service allows you to handle and analyze incoming data instantaneously, eliminating the need to wait for all data to be collected before starting the processing. Moreover, Amazon Kinesis allows for the ingestion, buffering, and real-time processing of streaming data, enabling you to extract insights in a matter of seconds or minutes, significantly reducing the time it takes compared to traditional methods. Overall, this capability revolutionizes how businesses can respond to data-driven opportunities as they arise.

Apama Streaming Analytics empowers businesses to process and respond to IoT and rapidly changing data in real-time, enabling them to react intelligently as events unfold. The Apama Community Edition serves as a freemium option from Software AG, offering users the chance to explore, develop, and deploy streaming analytics applications in a practical setting. Meanwhile, the Software AG Data & Analytics Platform presents a comprehensive, modular, and cohesive suite of advanced capabilities tailored for managing high-velocity data and conducting analytics on real-time information, complete with seamless integration to essential enterprise data sources. Users can select the features they require, including streaming, predictive, and visual analytics, alongside messaging capabilities that facilitate straightforward integration with various enterprise applications and an in-memory data store that ensures rapid access. Additionally, by incorporating historical data for comparative analysis, organizations can enhance their models and enrich critical customer and operational data, ultimately leading to more informed decision-making. This level of flexibility and functionality makes Apama an invaluable asset for companies aiming to leverage their data effectively.

Real-time analytics on raw data. Live ingest from S3, DynamoDB, DynamoDB and more. Raw data can be accessed as SQL tables. In minutes, you can create amazing data-driven apps and live dashboards. Rockset is a serverless analytics and search engine that powers real-time applications and live dashboards. You can directly work with raw data such as JSON, XML and CSV. Rockset can import data from real-time streams and data lakes, data warehouses, and databases. You can import real-time data without the need to build pipelines. Rockset syncs all new data as it arrives in your data sources, without the need to create a fixed schema. You can use familiar SQL, including filters, joins, and aggregations. Rockset automatically indexes every field in your data, making it lightning fast. Fast queries are used to power your apps, microservices and live dashboards. Scale without worrying too much about servers, shards or pagers.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) simplifies the process of creating and operating applications that leverage Apache Kafka for handling streaming data. As an open-source framework, Apache Kafka enables the construction of real-time data pipelines and applications. Utilizing Amazon MSK allows you to harness the native APIs of Apache Kafka for various tasks, such as populating data lakes, facilitating data exchange between databases, and fueling machine learning and analytical solutions. However, managing Apache Kafka clusters independently can be quite complex, requiring tasks like server provisioning, manual configuration, and handling server failures. Additionally, you must orchestrate updates and patches, design the cluster to ensure high availability, secure and durably store data, establish monitoring systems, and strategically plan for scaling to accommodate fluctuating workloads. By utilizing Amazon MSK, you can alleviate many of these burdens and focus more on developing your applications rather than managing the underlying infrastructure.

Create advanced applications that streamline workflows, provide ongoing operational monitoring, and manage processes in real-time. Your solutions are designed to operate continuously on cloud servers as well as edge devices. Utilizing a familiar spreadsheet interface, you don't need to be a programmer; instead, you can simply drag and drop data, enter formulas into cells, and create charts in an intuitive manner. All the essential protocols required for connecting to sensors and machinery, such as MQTT, REST, and OPC UA, are readily available. Streamsheets specializes in processing streaming data, including formats like MQTT and Kafka. You can select a topic stream, modify it as needed, and send it back into the vast world of streaming data. With REST, you gain access to a multitude of web services, while Streamsheets enables seamless connections both ways. Not only do Streamsheets operate in the cloud and on your servers, but they can also be deployed on edge devices, including Raspberry Pi, expanding their versatility to various environments. This flexibility allows businesses to adapt their systems according to their specific operational needs.

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

VIA offers enhanced visibility throughout data and various organizational barriers, fostering operational efficiency across multiple sectors. With this tool, your team can swiftly identify issues, automate responses when feasible, and mitigate the risks that could adversely affect service and customer satisfaction. Through its proactive analytic value chain and focus on customer needs, VIA not only uncovers necessary actions but also ranks them according to their potential impact on customers, allowing you to make informed decisions that enhance business outcomes. Additionally, VIA Solution Templates streamline the implementation and customization of the Platform to align with your specific business needs, facilitating a smoother transition and greater adaptability. Ultimately, leveraging VIA can lead to more responsive and effective operational strategies.

Gravio offers innovative methods to engage with your surroundings by harnessing the capabilities of IoT, sensors, edge computing, computer vision, and AI, all without requiring any programming expertise. This user-friendly software platform is compatible with Windows, macOS, and Linux systems. It allows seamless connectivity to various inputs and outputs, including integral IoT sensors, AI-driven cameras, and APIs such as MQTT and HTTP. With its straightforward interface, Gravio can be utilized effectively without any software development skills. By linking sensors, input devices, cameras, and APIs, Gravio captures and disseminates information, paving the way for novel interactions and insights that enrich physical spaces. The platform empowers entrepreneurs and organizations from diverse sectors to design tailored, connected experiences in both new and existing environments by providing a robust low-code/no-code framework. Ultimately, Gravio stands as a gateway to unlocking the full potential of interconnected technologies for users of all backgrounds.

Data Collection Core is a software solution from Iotsmart that facilitates the real-time gathering of data from OPC Servers and various devices, processes it, and allows for output to multiple storage solutions simultaneously, consolidating information from all connected devices in one centralized location. You can operate the DCC in the cloud or on-premises, utilizing platforms like Azure IoT Edge, AWS IoT Edge, or virtual machines with a containerized setup. This ensures you receive accurate data directly from your sensors while connecting seamlessly with OPC UA and HTTPS outputs, allowing for the integration of numerous devices with performance that surpasses standard client solutions. The system also supports server redundancy for OPC UA and MQTT, ensuring reliability and continuity. Our team of IoT specialists is available for support, providing troubleshooting assistance and tailored customer service to enhance your experience. With our focus on managing your digital solutions, you can concentrate on running your business effectively. The entire system is packaged using Docker images, making it easy to deploy across various cloud platforms, including Azure and AWS, ensuring flexibility and scalability for your operations.

The Datacake platform enables you to implement various Industrial IoT applications, including condition monitoring, data logging, real-time dashboards, and comprehensive data analytics. You can easily connect devices and gateways using LoRaWAN or NB-IoT protocols. With options like MQTT and other interfaces, the platform offers flexibility in integration. Utilizing the Datacake IoT platform along with Ready-to-Use LoRaWAN sensors, you can effectively monitor water levels in various settings, whether in flowing streams, stagnant ponds, or storage containers. Additionally, the platform features modern online mapping tools that allow you to visualize the real-time locations of your IoT assets, such as sensors and machines, on Interactive Maps. You can also track the historical routes traversed by these devices, providing valuable insights directly on the map. Furthermore, you have the capability to upload images and position sensors within detailed floor plans, hall layouts, or other relevant diagrams. This functionality allows you to present on-site conditions to your customers in an intuitive manner. Data can be sent to your devices on Datacake using webhooks, and there are also payload decoders available for handling HTTP requests. By leveraging these features, businesses can enhance their operational efficiency and improve decision-making processes.

Tatsoft's FactoryStudio provides the tools you need to quickly design secure and powerful industrial applications. Features include real-time data modeling and data logging, MQTT client/spB broker/spB, audit trails, alarms & incidents, visual SQL query gateway, high-performance smart screens, HTML5 dashboards. WPF drawing tools. iOS app, trends, annotations, reporting & much more! Programming scripts can be done in C#, VB.NET or JavaScript. You can get up and running in no time with ZERO client install and just 2 minutes server side installation. It includes many native protocol drivers for PLCs, DCSs, as well as support for other industry standards like OPC, MQTT, and more. Are you looking for a driver that we don't yet have? We also have a toolkit to help you develop protocol drivers! FactoryStudio is your data hub for your industrial ecosystem. It can be your link between IT, OT, real-time devices and your SQL data sources.

Apache Flink serves as a powerful framework and distributed processing engine tailored for executing stateful computations on both unbounded and bounded data streams. It has been engineered to operate seamlessly across various cluster environments, delivering computations with impressive in-memory speed and scalability. Data of all types is generated as a continuous stream of events, encompassing credit card transactions, sensor data, machine logs, and user actions on websites or mobile apps. The capabilities of Apache Flink shine particularly when handling both unbounded and bounded data sets. Its precise management of time and state allows Flink’s runtime to support a wide range of applications operating on unbounded streams. For bounded streams, Flink employs specialized algorithms and data structures optimized for fixed-size data sets, ensuring remarkable performance. Furthermore, Flink is adept at integrating with all previously mentioned resource managers, enhancing its versatility in various computing environments. This makes Flink a valuable tool for developers seeking efficient and reliable stream processing solutions.

ScaleOut Digital Twin Streaming Service™ allows for the seamless creation and deployment of real-time digital twins for advanced streaming analytics. With the ability to connect to numerous data sources such as Azure and AWS IoT hubs, Kafka, and others, it enhances situational awareness through live, aggregate analytics. This innovative cloud service is capable of tracking telemetry from millions of data sources simultaneously, offering immediate and in-depth insights with state-tracking and focused real-time feedback for a multitude of devices. The user-friendly interface streamlines deployment and showcases aggregate analytics in real time, which is essential for maximizing situational awareness. It is suitable for a diverse array of applications, including the Internet of Things (IoT), real-time monitoring, logistics, and financial services. The straightforward pricing structure facilitates a quick and easy start. When paired with the ScaleOut Digital Twin Builder software toolkit, the ScaleOut Digital Twin Streaming Service paves the way for the next generation of stream processing, empowering users to leverage data like never before. This combination not only enhances operational efficiency but also opens new avenues for innovation across various sectors.

DeltaStream is an integrated serverless streaming processing platform that integrates seamlessly with streaming storage services. Imagine it as a compute layer on top your streaming storage. It offers streaming databases and streaming analytics along with other features to provide an integrated platform for managing, processing, securing and sharing streaming data. DeltaStream has a SQL-based interface that allows you to easily create stream processing apps such as streaming pipelines. It uses Apache Flink, a pluggable stream processing engine. DeltaStream is much more than a query-processing layer on top Kafka or Kinesis. It brings relational databases concepts to the world of data streaming, including namespacing, role-based access control, and enables you to securely access and process your streaming data, regardless of where it is stored.

Evam's Continuous Intelligence Platform integrates various products aimed at the processing and visualization of real-time data streams. It operates machine learning models in real time while enhancing the data with an advanced in-memory caching system. By doing so, EVAM allows companies in telecommunications, financial services, retail, transportation, and travel sectors to fully leverage their business potential. This platform's machine learning capabilities facilitate the processing of live data, enabling the visual design and orchestration of customer journeys through sophisticated analytical models and AI algorithms. Furthermore, EVAM helps businesses connect with their customers across various channels, including legacy systems, in real time. With the ability to collect and process billions of events instantaneously, companies can gain valuable insights into each customer’s preferences, allowing them to attract, engage, and retain clients more efficiently. The effectiveness of such a system not only enhances operational capabilities but also fosters deeper customer relationships.

Azure Data Explorer is an efficient and fully managed analytics service designed for swift analysis of vast amounts of data that originate from various sources such as applications, websites, and IoT devices. Users can pose questions and delve into their data in real-time, allowing for enhancements in product development, customer satisfaction, device monitoring, and overall operational efficiency. This service enables quick detection of patterns, anomalies, and emerging trends within the data landscape. Users can formulate and receive answers to new inquiries within minutes, and the framework allows for unlimited queries thanks to its cost-effective structure. With Azure Data Explorer, organizations can discover innovative ways to utilize their data without overspending. By prioritizing insights over infrastructure, users benefit from a straightforward, fully managed analytics platform. This service is adept at addressing the challenges posed by fast-moving and constantly evolving data streams, making analytics more accessible and efficient for all types of streaming information. Ultimately, Azure Data Explorer empowers businesses to leverage their data in transformative ways.

Utilize a comprehensive, AI-integrated solution to access, organize, select, and transform data from the Internet of Things. SAS Analytics for IoT encompasses the entire analytics life cycle related to IoT, featuring a streamlined and extensible ETL process, a data model focused on sensors, and an advanced analytics framework supported by a premier streaming execution engine that facilitates complex multi-phase analytics. Powered by SAS® Viya®, this solution operates efficiently within a fast, in-memory distributed setting. Discover how to create SAS Event Stream Processing applications capable of handling high-volume and high-velocity data streams, delivering real-time responses while retaining only the essential data elements. This course introduces fundamental principles of event stream processing, detailing the various component objects that can be utilized to construct effective event stream processing applications. Our commitment to curiosity drives innovation, as SAS analytics solutions convert raw data into actionable insights, empowering customers globally to embark on bold new ventures that foster advancement. Embrace the future of data analytics and unlock limitless possibilities with SAS.

Empower individuals to explore and analyze streaming data effectively. By sharing, documenting, and organizing your data, you can boost productivity by as much as 95%. Once you have your data, you can create applications tailored for real-world use cases. Implement a security model focused on data to address the vulnerabilities associated with open source technologies, ensuring data privacy is prioritized. Additionally, offer secure and low-code data pipeline functionalities that enhance usability. Illuminate all hidden aspects and provide unmatched visibility into data and applications. Integrate your data mesh and technological assets, ensuring you can confidently utilize open-source solutions in production environments. Lenses has been recognized as the premier product for real-time stream analytics, based on independent third-party evaluations. With insights gathered from our community and countless hours of engineering, we have developed features that allow you to concentrate on what generates value from your real-time data. Moreover, you can deploy and operate SQL-based real-time applications seamlessly over any Kafka Connect or Kubernetes infrastructure, including AWS EKS, making it easier than ever to harness the power of your data. By doing so, you will not only streamline operations but also unlock new opportunities for innovation.

An MQTT Broker designed with enthusiasm to meet all your requirements for deploying and scaling IoT applications. It features a REST API, a comprehensive dashboard with customizable widgets, and an extensive data storage solution, among other capabilities. Users can quickly visualize a snapshot of their IoT devices, monitoring client connections and disconnections, as well as critical data through various dashboard widgets. The system also provides alerts and color-coded indicators based on different value triggers. A robust rules engine is included to convert MQTT messages, facilitating streamlined M2M communication automation. This engine supports event and timer-based rules, enabling users to define data patterns and automate corresponding actions. For secure device communication, a publish and subscribe messaging model is implemented with dual layers of security, employing SSL/TLS for connectivity and optional username/password authentication. Additionally, web security measures are in place for data viewing. To ensure high availability, the broker can operate multiple message brokers simultaneously, guaranteeing efficient message collection and publication from devices. This architecture assures a remarkable 99.99% success rate in data collection, ensuring reliability regardless of software challenges. Moreover, the system's flexibility allows for seamless integration with various IoT applications and services.

Keen is a fully managed event streaming platform. Our real-time data pipeline, built on Apache Kafka, makes it easy to collect large amounts of event data. Keen's powerful REST APIs and SDKs allow you to collect event data from any device connected to the internet. Our platform makes it possible to securely store your data, reducing operational and delivery risks with Keen. Apache Cassandra's storage infrastructure ensures data is completely secure by transferring it via HTTPS and TLS. The data is then stored with multilayer AES encryption. Access Keys allow you to present data in an arbitrary way without having to re-architect or re-architect the data model. Role-based Access Control allows for completely customizable permission levels, down to specific queries or data points.

You may not be aware of your own knowledge gaps. Stratifyd is specifically crafted to uncover the trends and irregularities that signal necessary adjustments in your customer, product, and employee interactions. It consolidates and integrates voice of the customer information from diverse sources—such as first- and third-party data, social media, chat interactions, spoken communication, reviews, and beyond—into a unified, secure, and reliable Experience Analytics Platform, utilizing an extensive library of experience, operational, behavioral, public data, and open API integrations. By leveraging the capabilities of Smart AI, you can swiftly focus on the critical moments that matter most. Take control of a continuous flow of customer experience, behavioral, and operational data to disclose and foresee essential themes, irregularities, sentiments, and trends without needing any expertise in data science or coding. Demonstrating that you genuinely value customer feedback is crucial. Enhance customer retention, foster loyalty, and streamline operations by proactively responding to the insights that hold significance. Furthermore, this approach empowers organizations to make informed decisions that ultimately lead to improved overall performance.

The Waylay platform is a modular IoT solution that offers top-tier OEM technology for backend development and operational processes, facilitating the rapid delivery of IoT solutions on a large scale. It features sophisticated rule logic modeling, execution capabilities, and comprehensive lifecycle management. This platform allows for the automation of various data workflows, regardless of their complexity. Designed to seamlessly handle the diverse data patterns found in IoT, OT, and IT, Waylay integrates both streaming and time series analytics into a single, collaborative intelligence environment. By providing non-developer teams with user-friendly, self-service apps focused on key performance indicators, it significantly shortens the time to market for IoT products. Users can identify the most effective automation tools for their specific IoT applications and evaluate them against established benchmarks. Additionally, developing IoT applications diverges significantly from traditional IT development, as it entails connecting the physical realm of Operations Technology, which involves sensors and actuators, with the digital landscape of Information Technology, encompassing databases and software systems. This bridging of worlds highlights the unique challenges and opportunities presented by IoT application development.

Eclipse Kura™ is a flexible and open-source framework designed for IoT Edge applications, built on Java/OSGi. It provides developers with API access to various hardware interfaces found in IoT gateways, such as serial ports, GPS, watchdog timers, GPIOs, and I2C. Among its features, Kura includes pre-configured field protocols like Modbus, OPC-UA, and S7, an application container, and a web-based visual programming tool that facilitates data acquisition from the field, edge processing, and efficient publishing to prominent IoT cloud platforms via MQTT. The rise of an IoT service gateway model utilizing contemporary software architectures at the edge of IoT implementations acts as a unifying controller and aggregator, enabling the integration of advanced enterprise technologies into IoT gateways. By utilizing sophisticated software frameworks that simplify the complexities of hardware and networking, the development and reusability of combined hardware and software solutions are significantly transformed, fostering innovation and efficiency in IoT projects. This shift empowers developers to focus more on application logic rather than underlying technical challenges.

Dash & Dash Enterprise allow you to build and deploy analytic web applications using Python, R, or Julia. No JavaScript or DevOps are required. The world's most successful companies offer AI, ML and Python analytics at a fraction of the cost of full-stack development. Dash is the way they do it. Apps and dashboards that run advanced analytics such as NLP, forecasting and computer vision can be delivered. You can work in Python, R, or Julia. Reduce costs by migrating legacy per-seat license software to Dash Enterprise's unlimited end-user pricing model. You can deploy and update Dash apps faster without an IT or DevOps staff. You can create pixel-perfect web apps and dashboards without having to write any CSS. Kubernetes makes it easy to scale. High availability support for mission-critical Python apps

Ayla adopts a genuinely agnostic strategy, facilitating device connectivity through various widely-used transport protocols, connectivity methods, and cloud infrastructure solutions. Compatible with standards such as HTTPS, MQTT, and CoAP, Ayla offers a comprehensive selection of pre-configured agents designed for embedded systems, gateways, Android, Linux, BLE/phones, and cloud connectivity. The company’s Virtualization Engine creates a powerful 'digital twin' of each physical device, establishing a strong groundwork for managing devices at a large scale within the IoT ecosystem. With proven functionalities like a rules engine, firmware Over-The-Air (OTA) updates, and data policies, Ayla's Device Management system ensures thorough support for connected products throughout their entire lifecycle. Additionally, Ayla's application enablement capabilities allow businesses to derive significant value from their data in numerous ways. By providing both a Web Framework and a Mobile Platform SDK, Ayla accelerates the development of consumer and business applications. Furthermore, they offer services such as Customer Care, Field Service, and Asset Tracking, enhancing the overall user experience and operational efficiency.

Jaspersoft® commercial edition has everything you need to design and deliver any report you need. We’ve spent over two decades perfecting our platform so you can deliver the data visualizations and analytics your customers want, from high volumes of pixel perfect reports to self-service ad hoc reports and more. Jaspersoft helps you deliver the reporting and analytics your customers want, without burdening your development team.

HULFT IoT serves as a robust managed file transfer middleware tailored for IoT devices, effectively safeguarding against data loss in essential scenarios like payment processing, security, and monitoring. While utilizing protocols like MQTT or HTTPS for IoT data gathering demands a learning curve for users, HULFT IoT simplifies the process by requiring only the installation of its software, thus enabling swift data collection. Additionally, with the integration of DataSpider Servista, our enterprise application integration (EAI) tool, users can seamlessly connect multiple applications to the data gathered by HULFT IoT without any coding, as the setup process is entirely based on drag-and-drop functionality. A machine tool manufacturer previously conducted on-site inspections and maintenance for their customers, during which each device generated operational log data. By analyzing this data, they were able to forecast maintenance needs effectively. To enhance their operational efficiency, the company sought to implement remote monitoring of devices and schedule maintenance personnel as needed. However, the challenge arose with each device producing approximately 10GB of log data daily, complicating their data management efforts further. To address this, they recognized the necessity of a streamlined solution that could handle such vast amounts of data efficiently.

Enlighted and its partners develop applications that significantly enhance operational efficiencies and improve the experiences of occupants, while also boosting productivity and maximizing the utilization of resources and assets. The system employs sensors capable of detecting motion, temperature, and ambient light levels. Additionally, asset tags and badges utilize Bluetooth technology to communicate with these sensors, enabling the precise tracking of both assets and individuals. Users can manually adjust lighting or rely on automated systems for room controls. This technology includes the industry's most advanced software-defined sensors, which capture and integrate various data streams. Moreover, a gateway transmits the information collected by the sensors to the energy manager for comprehensive analysis and reporting. With just a push of a button, occupants have the flexibility to modify preset lighting levels and configurations, ensuring that their comfort and preferences are prioritized. This functionality empowers users to create personalized environments that cater to their specific needs.

IBM Streams analyzes a diverse array of streaming data, including unstructured text, video, audio, geospatial data, and sensor inputs, enabling organizations to identify opportunities and mitigate risks while making swift decisions. By leveraging IBM® Streams, users can transform rapidly changing data into meaningful insights. This platform evaluates various forms of streaming data, empowering organizations to recognize trends and threats as they arise. When integrated with other capabilities of IBM Cloud Pak® for Data, which is founded on a flexible and open architecture, it enhances the collaborative efforts of data scientists in developing models to apply to stream flows. Furthermore, it facilitates the real-time analysis of vast datasets, ensuring that deriving actionable value from your data has never been more straightforward. With these tools, organizations can harness the full potential of their data streams for improved outcomes.

An entirely managed cloud-based solution that facilitates device registration, connectivity, control, quick visualization, and data storage. By integrating chip, app, and cloud technologies, users can fully leverage Watson's cognitive APIs, feature-rich dashboards, extensive developer tools, and top-tier security measures to enhance insights in enterprise IoT. This service provides predictive, real-time, and edge analysis of user, machine, and environmental data, utilizing machine learning and cognitive APIs. It enables governance over applications and devices within an IoT framework, monitoring usage and performance trends, detecting anomalies, and validating data and transactions. The platform connects IoT devices, networks, and gateways through an expanding ecosystem that employs open standards-based communications such as MQTT and HTTPS. Furthermore, it allows for the identification, aggregation, and transformation of data from various IoT sources into structured asset-based data. Users can harness their IoT data to gain insights into current conditions and trends, analyze unstructured data from videos and images, and extract valuable information from unstructured textual data. Ultimately, this service empowers organizations to make informed decisions based on comprehensive data analysis and visualization.

Informatica's AI-driven Data Engineering Streaming empowers data engineers to efficiently ingest, process, and analyze real-time streaming data, offering valuable insights. The advanced serverless deployment feature, coupled with an integrated metering dashboard, significantly reduces administrative burdens. With CLAIRE®-enhanced automation, users can swiftly construct intelligent data pipelines that include features like automatic change data capture (CDC). This platform allows for the ingestion of thousands of databases, millions of files, and various streaming events. It effectively manages databases, files, and streaming data for both real-time data replication and streaming analytics, ensuring a seamless flow of information. Additionally, it aids in the discovery and inventorying of all data assets within an organization, enabling users to intelligently prepare reliable data for sophisticated analytics and AI/ML initiatives. By streamlining these processes, organizations can harness the full potential of their data assets more effectively than ever before.

BlackLynx's accelerators offer analytics capabilities exactly where they are required, eliminating the need for specialized expertise. Regardless of the components of your analytics framework, you can harness data-driven insights through robust and user-friendly heterogeneous computing solutions. The integration of BlackStack software with electronic systems significantly enhances processing speeds for sensors utilized across various platforms, including terrestrial, maritime, aerospace, and aerial assets. Our innovative software empowers clients to optimize essential AI/ML algorithms and other computational tasks, specifically targeting real-time sensor data processing, which encompasses signal detection, video analytics, missile tracking, radar operations, thermal imaging, and other object detection functionalities. Additionally, BlackStack software substantially improves the speed of processing for real-time data analytics. We enable our clients to delve into enterprise-level unstructured data, providing the tools necessary to gather, filter, and systematically arrange extensive intelligence or cybersecurity forensic data sets, ultimately transforming how they manage and respond to vast streams of information. This capability allows organizations to make informed decisions that drive efficiency and innovation.

Oracle Stream Analytics empowers users to handle and evaluate vast amounts of real-time data through advanced correlation techniques, enrichment capabilities, and machine learning integration. This platform delivers immediate, actionable insights for businesses dealing with streaming information, facilitating automated responses that support the needs of modern agile enterprises. It features Visual GEOProcessing with GEOFence relationship spatial analytics, enhancing location-based decision-making. Additionally, the introduction of a new Expressive Patterns Library encompasses various categories, such as Spatial, Statistical, General industry, and Anomaly detection, alongside streaming machine learning functionalities. With an intuitive visual interface, users can seamlessly explore live streaming data, enabling effective in-memory analytics that enhance real-time business strategies. Overall, this powerful tool significantly improves operational efficiency and decision-making processes in fast-paced environments.