Alternatives to Azure Time Series Insights

Statseeker is a powerful network performance monitor solution. It's fast, scalable, and cost-effective. Statseeker requires only one server or virtual machine to be up and running in minutes. It can also discover your entire network in under an hour without any significant impact on your bandwidth availability. It can monitor networks of all sizes, polling upto one million interfaces every sixty second, and collecting network data like SNMP, ping, NetFlow (sFlow, and J-Flow), sylog and trap messages, SDN configuration, and health metrics. Statseeker performance data are never averaged or rolled up. This eliminates the guesswork when it comes to identifying over- and underestimated infrastructure, root cause analysis, capacity planning, and other tasks. Statseeker's complete data retention means the in-built analytic engine can accurately detect anomalies in performance and forecast network behaviour months in advance. This allows network admins to plan and perform cost-effective, preventative maintenance, instead of fire-fighting problems as they occur. Statseeker's dashboards and out-of-the box reports allow you to troubleshoot and fix problems in your network before users are aware.

It works: Codeless testing Give your entire team the ability to create and maintain automated tests. Not just developers. Meet your testing demands fast. You can get full coverage of your tests in days and not months. Our natural-language tests are very resistant to code changes. Our AI will quickly repair any test failures. Continuous Testing is a key component of Agile/DevOps. Push features to production in the same day. Boozang supports the following test approaches: - Codeless Record/Replay interface - BDD / Cucumber - API testing - Model-based testing - HTML Canvas testing The following features makes your testing a breeze - In-browser console debugging - Screenshots to show where test fails - Integrate to any CI server - Test with unlimited parallel workers to speed up tests - Root-cause analysis reports - Trend reports to track failures and performance over time - Test management integration (Xray / Jira)

Harness the power of AI for anomaly detection and root cause analysis focused on the key metrics that impact your business. Avora employs machine learning to oversee your business metrics around the clock, promptly notifying you of critical incidents so you can respond within hours instead of waiting for days or weeks. By continuously examining millions of records every hour for any signs of unusual activity, it reveals both potential threats and new opportunities within your organization. The root cause analysis feature helps you identify the elements influencing your business metrics, empowering you to implement swift, informed changes. You can integrate Avora’s machine learning features and notifications into your applications through our comprehensive APIs. Receive alerts about anomalies, shifts in trends, and threshold breaches via email, Slack, Microsoft Teams, or any other platform through Webhooks. Additionally, you can easily share pertinent insights with your colleagues and invite them to monitor ongoing metrics, ensuring they receive real-time notifications and updates. This collaborative approach enhances decision-making across the board, fostering a proactive business environment.

Our namesake product, Minitab Statistical Software, leads the way in data analysis with the power to visualize, analyze and harness your data to gain insights and solve your toughest challenges. Access trusted, proven and modern analytics combined with dynamic visualizations to empower you and your decisions. The latest version of Minitab Statistical Software includes access to Minitab on the cloud so you can analyze from anywhere, and Graph Builder, our new interactive tool to instantly create multiple graph options at once. Minitab offers modules for Predictive Analytics and Healthcare to boost your analytics even further. Available in 8 languages: English, Chinese, French, German, Japanese, Korean, Spanish, and Portuguese. For 50 years, Minitab has helped thousands of companies and institutions spot trends, solve problems, and discover valuable insights in their data through our comprehensive, best-in-class suite of data analysis and process improvement tools.

Amazon Timestream is an efficient, scalable, and serverless time series database designed for IoT and operational applications, capable of storing and analyzing trillions of events daily with speeds up to 1,000 times faster and costs as low as 1/10th that of traditional relational databases. By efficiently managing the lifecycle of time series data, Amazon Timestream reduces both time and expenses by keeping current data in memory while systematically transferring historical data to a more cost-effective storage tier based on user-defined policies. Its specialized query engine allows users to seamlessly access and analyze both recent and historical data without the need to specify whether the data is in memory or in the cost-optimized tier. Additionally, Amazon Timestream features integrated time series analytics functions, enabling users to detect trends and patterns in their data almost in real-time, making it an invaluable tool for data-driven decision-making. Furthermore, this service is designed to scale effortlessly with your data needs while ensuring optimal performance and cost efficiency.

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

Plutoshift’s Operational Data Platform (ODP) offers automated performance tracking and predictive analysis aimed at optimizing physical infrastructure, enhancing efficiency, minimizing costs and waste, and fostering the development of more sustainable and resilient businesses. The most significant hurdle in extracting value often lies in the initial stages of data extraction and processing. To address this, Plutoshift effectively ingests, processes, and organizes all data from infrastructure, business operations, and even external sources, thereby establishing a solid foundation for actionable insights. The platform fully automates and manages the entire data pipeline, eliminating the need for extra IT personnel. With Plutoshift, organizations gain a continuous and comprehensive view of their operations at various levels, including workflow, site, and enterprise. Operators can instantly access trends and key performance indicators (KPIs) for all processes and assets, enabling swift decision-making. Additionally, the system features customizable alerts, response tracking, and detailed contextual reports, empowering teams to quickly spot issues, avert potential downtimes, and identify the underlying causes of problems. This proactive approach not only enhances operational efficiency but also supports strategic decision-making for long-term success.

TrendMiner is an advanced industrial analytics platform that is fast, powerful, and intuitive. It was designed to monitor and troubleshoot industrial processes in real-time. It allows for robust data collection, analysis and visualization, allowing everyone in industrial operations to make smarter data-driven decision efficiently. TrendMiner is a Proemion Company founded in 2008. Our global headquarters are located in Belgium and we have offices in the U.S.A., Germany, Spain, and the Netherlands. TrendMiner has strategic alliances with major players like Amazon, Microsoft and SAP. It also offers standard integrations for a variety of historians, including Honeywell PHD and GE Proficy Historian.

Detecting anomalies in time series data is critical for the daily functions of numerous organizations. The Timeseries Insights API Preview enables you to extract real-time insights from your time-series datasets effectively. It provides comprehensive information necessary for interpreting your API query results, including details on anomaly occurrences, projected value ranges, and segments of analyzed events. This capability allows for the real-time streaming of data, facilitating the identification of anomalies as they occur. With over 15 years of innovation in security through widely-used consumer applications like Gmail and Search, Google Cloud offers a robust end-to-end infrastructure and a layered security approach. The Timeseries Insights API is seamlessly integrated with other Google Cloud Storage services, ensuring a uniform access method across various storage solutions. You can analyze trends and anomalies across multiple event dimensions and manage datasets that encompass tens of billions of events. Additionally, the system is capable of executing thousands of queries every second, making it a powerful tool for real-time data analysis and decision-making. Such capabilities are invaluable for businesses aiming to enhance their operational efficiency and responsiveness.

Time-sensitive decisions require immediate attention. With TRND, machine learning projects can be accelerated from lengthy timelines to mere minutes, similar to the efficiency of Google's AI search engine that delivers insights in real time. Financial losses can stem from inaccuracies, and unlike standard KPIs, TRND identifies patterns that uncover critical information hidden from traditional metrics. This tool empowers decision-makers by highlighting trends that signal emerging threats or opportunities. In today's digital landscape, knowledge equates to financial advantage. TRND allows for the creation of shareable pattern libraries, promoting rapid learning and implementation for enhancing business operations. Without comprehensive monitoring, potential profits remain untapped. TRND excels at not only identifying rare insights but also continuously tracking relevant information across all indicators. The myth that scaling efforts must be excessively costly is shattered by our innovative search-based method, which makes extensive micro-monitoring both feasible and economical. In essence, TRND revolutionizes the approach to data utilization, ensuring that businesses stay ahead in a competitive environment.

Analyzing time-series data is crucial for the daily functions of numerous businesses. Common applications involve assessing consumer foot traffic and conversion rates for retailers, identifying anomalies in data, discovering real-time correlations within sensor information, and producing accurate recommendations. With the Cloud Inference API Alpha, businesses can derive real-time insights from their time-series datasets that they input. This tool provides comprehensive details about API query results, including the various groups of events analyzed, the total number of event groups, and the baseline probability associated with each event returned. It enables real-time streaming of data, facilitating the computation of correlations as events occur. Leveraging Google Cloud’s robust infrastructure and a comprehensive security strategy that has been fine-tuned over 15 years through various consumer applications ensures reliability. The Cloud Inference API is seamlessly integrated with Google Cloud Storage services, enhancing its functionality and user experience. This integration allows for more efficient data handling and analysis, positioning businesses to make informed decisions faster.

Kibana serves as a free and open user interface that enables the visualization of your Elasticsearch data while providing navigational capabilities within the Elastic Stack. You can monitor query loads or gain insights into how requests traverse your applications. This platform offers flexibility in how you choose to represent your data. With its dynamic visualizations, you can start with a single inquiry and discover new insights along the way. Kibana comes equipped with essential visual tools such as histograms, line graphs, pie charts, and sunbursts, among others. Additionally, it allows you to conduct searches across all your documents seamlessly. Utilize Elastic Maps to delve into geographic data or exercise creativity by visualizing custom layers and vector shapes. You can also conduct sophisticated time series analyses on your Elasticsearch data using our specially designed time series user interfaces. Furthermore, articulate queries, transformations, and visual representations with intuitive and powerful expressions that are easy to master. By employing these features, you can uncover deeper insights into your data, enhancing your overall analytical capabilities.

Anodot uses AI to deliver autonomous analytics at enterprise scale across all data types and in real-time. We provide business analysts with the ability to control their business, without the limitations of traditional Business Intelligence. Our self-service AI platform runs continuously to eliminate blind spots and alert incidents, and investigate root cause. Our platform uses machine learning algorithms that are patent-pending to identify issues and correlate them across multiple parameters. This eliminates business insight latency and supports quick, smart business decision-making. Anodot serves over 100 customers in the digital transformation industry, including eCommerce, FinTech and AdTech, Telco and Gaming. This includes Microsoft, Lyft and Waze. Anodot was founded in 2014 in Silicon Valley and Israel. There are also sales offices around the world.

Every event, from transactions to meetings, occurs at a specific moment or over a span of time, making it essential for successful investigations to grasp the sequence and connections of these events. KronoGraph stands out as the pioneering toolkit designed for scalable timeline visualizations that uncover trends within temporal data. Create engaging timeline tools that allow for the exploration of how events and relationships progress over time. Whether you're examining communication between two individuals or analyzing IT traffic across an entire enterprise, KronoGraph delivers a comprehensive and interactive representation of the information. The tool enables a seamless transition from a broad overview to detailed individual occurrences, enhancing the investigative process as it develops. Often, investigations hinge on pinpointing critical elements like a person, an event, or a connection. With the dynamic interface of KronoGraph, you can navigate through time, revealing anomalies and trends while zooming in on specific entities that elucidate the deeper narrative contained within your data. This capability not only simplifies complex analyses but also empowers users to draw insights that would otherwise remain obscured.

IBM® Z® Operations Analytics is a powerful tool designed to facilitate the searching, visualization, and analysis of extensive structured and unstructured operational data within IBM Z environments, encompassing log files, event records, service requests, and performance metrics. By utilizing your analytics platform alongside machine learning, you can enhance enterprise visibility, pinpoint workload issues, uncover hidden challenges, and expedite root cause analysis. Machine learning aids in establishing a baseline of typical system behavior, enabling the detection of operational anomalies efficiently. Additionally, you can identify nascent issues across various services, allowing for proactive alerts and cognitive adjustments to evolving conditions. This tool offers expert recommendations for corrective measures, enhancing overall service assurance. Furthermore, it helps in spotting atypical workload patterns and reveals common problems that may be obscured in operational datasets. Ultimately, it significantly diminishes the time needed for root cause analysis, thereby capitalizing on the extensive domain knowledge of IBM Z and applying its insights effectively within your analytics framework. By harnessing these capabilities, organizations can achieve a more resilient and responsive operational environment.

Nazar was developed to address the challenges of managing several databases across multi-cloud or hybrid settings. Fully equipped for the primary database engines, it effectively removes the necessity for juggling multiple tools. By providing a standardized and user-friendly method for establishing new servers on the platform, it significantly reduces setup time. Users can obtain a cohesive overview of their database performance on a singular dashboard, eliminating the hassle of interfacing with various tools that offer inconsistent views and metrics. The real competition lies not in the tedious setup, log tracing, or querying of data dictionaries; rather, Nazar leverages the inherent capabilities of the DBMS for monitoring, thus eliminating the need for additional agents. Furthermore, Nazar automates both anomaly detection and root-cause analysis, which leads to a decrease in mean time to resolution (MTTR) while proactively identifying issues to prevent incidents, ensuring optimal application and business performance. With its comprehensive approach, Nazar not only enhances efficiency but also empowers users to focus on strategic initiatives rather than mundane tasks.

Experience the power of advanced computing right at your fingertips. With the capabilities of parallel computing and innovative algorithms, there's no reason to hesitate any longer. Created specifically for data scientists in the business realm, this all-inclusive time-series platform delivers the fastest computing available. Shapelets offers a suite of analytical tools, including causality analysis, discord detection, motif discovery, forecasting, and clustering, among others. You can also run, expand, and incorporate your own algorithms into the Shapelets platform, maximizing the potential of Big Data analysis. Seamlessly integrating with various data collection and storage systems, Shapelets ensures compatibility with MS Office and other visualization tools, making it easy to share insights without requiring extensive technical knowledge. Our user interface collaborates with the server to provide interactive visualizations, allowing you to fully leverage your metadata and display it through a variety of modern graphical representations. Additionally, Shapelets equips professionals in the oil, gas, and energy sectors to conduct real-time analyses of their operational data, enhancing decision-making and operational efficiency. By utilizing Shapelets, you can transform complex data into actionable insights.

Empower your teams to take initiative in recognizing potential risks by enhancing the incident reporting process and offering a real-time overview of safety throughout the organization. Scout enables all employees, including those who do not have user accounts, to report injuries, incidents, near misses, and safety observations from any device they choose. To facilitate this, dedicated QR codes can be placed on posters or stickers for easy access to reporting. After incidents are reported, safety leaders can work together on investigations and conduct Root Cause Analysis (RCA) activities. Scout’s innovative data exploration tools shift incident management from a reactive stance to a proactive approach. This allows safety leaders to analyze trends, identify troubling areas, and disseminate insights across various locations. Additionally, site leaders can efficiently meet OSHA Recordkeeping requirements while generating essential reports like 300, 300a, and others. Through email notifications and time-stamped event logs, Scout ensures that accountability and transparency are upheld at every level of the organization. Ultimately, this comprehensive approach fosters a culture of safety and vigilance among all team members.

A Revenue Operations Platform that increases revenue results. Automated CRM updates Check. Time series analysis? Check. Clari offers more than just innovative features. Clari solves the real problem by combining revenue intelligence, forecasting, and execution insights. It is efficient and predictable in hitting your targets every quarter. Clari's Revenue Operations Platform is purpose-built to increase revenue predictability. It takes previously untapped data, such as call logs, CRM, email, and CRM, and turns it into execution insights that you can use for your entire revenue team. Clari combines AI insights with human intuition to enable your team to forecast with greater accuracy and foresight. It uses a consistent, automated process that can be used to manage all businesses in your company. You can collect valuable activity data from prospects, customers, and reps so you are always up to date on what's happening in your deals, in your business, and with your team.

The TIARA Assessment is a streamlined security posture evaluation service aimed at assisting clients in swiftly identifying the threat level of their entire network. Accompanying the assessment, TIARA Recommendations offer strategic improvement plans and remediation support to elevate the overall security posture. This turnkey service encompasses both Sangfor hardware and software, enabling customers to rapidly acquire a comprehensive understanding of their existing threat landscape. On the other hand, the MTR service is an ongoing initiative focused on thorough threat analysis and asset identification, which enhances the effectiveness and efficiency of daily security operations. Additionally, the MTR services contribute to the improvement of the organization's overall security posture and support the evolution of security operations. Furthermore, as part of the MTR Root-Cause Analysis, Sangfor's security experts perform in-depth investigations to identify the origins of security issues and provide actionable long-term recommendations for enhancement. This dual approach ensures that clients not only understand their current vulnerabilities but also receive the guidance necessary to strengthen their defenses over time.

Komodor simplifies the troubleshooting process for Kubernetes, equipping you with all the essential tools to resolve issues confidently. It oversees your entire Kubernetes ecosystem, detects problems, reveals their underlying causes, and provides the necessary context for effective and independent troubleshooting. The platform automatically identifies anomalies, deployment failures, misconfigurations, bottlenecks, and various health-related issues. It enables you to recognize potential problems before they escalate and impact end-users. By utilizing pre-designed playbooks, you can enhance root cause analysis, avoid disruptive escalations, and conserve valuable developer time. Moreover, it offers clear remediation guidance that empowers every team member to act like a seasoned troubleshooting expert, fostering a more resilient operational environment. This proactive approach not only enhances team efficiency but also significantly improves overall system reliability.

Revolutionizing observability brings context and performance into a unified space, suitable for any stack and scale. Achieve thorough end-to-end visibility by effortlessly monitoring applications, infrastructure, databases, and more from a single, user-friendly dashboard. With just a few clicks, trace and analyze digital journeys seamlessly from browsers and applications to the infrastructure layer. Discover invaluable insights into user experiences, identify where dropouts occur, and highlight critical aspects of business transactions through in-depth user analytics and real user monitoring (RUM). This allows for quick adaptation, optimization, and innovation powered by real-time visibility and swift root-cause analysis. Additionally, our dedicated team of experts is available 24/7, 365 days a year, ensuring you receive prompt assistance and tailored support for your unique requirements, which further enhances your operational efficiency. The combination of these features empowers businesses to stay ahead in a rapidly evolving digital landscape.

TimescaleDB is the most popular open-source relational database that supports time-series data. Fully managed or self-hosted. You can rely on the same PostgreSQL that you love. It has full SQL, rock-solid reliability and a huge ecosystem. Write millions of data points per node. Horizontally scale up to petabytes. Don't worry too much about cardinality. Reduce complexity, ask more questions and build more powerful applications. You will save money with 94-97% compression rates using best-in-class algorithms, and other performance improvements. Modern cloud-native relational database platform that stores time-series data. It is based on PostgreSQL and TimescaleDB. This is the fastest, easiest, and most reliable way to store all of your time-series information. All observability data can be considered time-series data. Time-series problems are those that require efficient solutions to infrastructure and application problems.

Instant access to systems containing representative performance data is crucial. Establish and monitor weekly, monthly, and quarterly goals for representatives proactively. Automatic identification of the root causes of performance challenges or successes is essential. Designed for fast-paced managers who require quick answers rather than becoming overwhelmed by excessive dashboards, Atrium ensures that surprises from representative issues are minimized before they escalate. With the insights provided by Atrium, managers can anticipate potential challenges and address them proactively, allowing for more effective coaching and resolution instead of merely searching for problems. This platform enables timely detection and alerts for managers, operational staff, and leaders, ensuring that issues are identified early on to prevent them from developing into significant complications. Unlike complex business intelligence tools that cater to data analysts, Atrium is tailored for Sales Development Representatives, Account Executives, Account Managers, and Customer Success Managers, as well as the leaders and operational personnel who support them in their endeavors. By streamlining these processes, managers can focus on what truly matters—developing their teams and achieving outstanding results.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

Enhance your metrics and alerting capabilities using a top-tier open-source monitoring tool. Prometheus inherently organizes all data as time series, which consist of sequences of timestamped values associated with the same metric and a specific set of labeled dimensions. In addition to the stored time series, Prometheus has the capability to create temporary derived time series based on query outcomes. The tool features a powerful query language known as PromQL (Prometheus Query Language), allowing users to select and aggregate time series data in real time. The output from an expression can be displayed as a graph, viewed in tabular format through Prometheus’s expression browser, or accessed by external systems through the HTTP API. Configuration of Prometheus is achieved through a combination of command-line flags and a configuration file, where the flags are used to set immutable system parameters like storage locations and retention limits for both disk and memory. This dual method of configuration ensures a flexible and tailored monitoring setup that can adapt to various user needs. For those interested in exploring this robust tool, further details can be found at: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fsourceforge.net%2Fprojects%2Fprometheus.mirror%2F

VictoriaMetrics is a cost-effective, scalable monitoring solution that can also be used as a time series database. It can also be used to store Prometheus' long-term data. VictoriaMetrics is a single executable that does not have any external dependencies. All configuration is done using explicit command-line flags and reasonable defaults. It provides global query view. Multiple Prometheus instances, or other data sources, may insert data into VictoriaMetrics. Later this data may be queried via a single query. It can handle high cardinality and high churn rates issues by using a series limiter.

QuestDB is an advanced relational database that focuses on column-oriented storage optimized for time series and event-driven data. It incorporates SQL with additional features tailored for time-based analytics to facilitate real-time data processing. This documentation encompasses essential aspects of QuestDB, including initial setup instructions, comprehensive usage manuals, and reference materials for syntax, APIs, and configuration settings. Furthermore, it elaborates on the underlying architecture of QuestDB, outlining its methods for storing and querying data, while also highlighting unique functionalities and advantages offered by the platform. A key feature is the designated timestamp, which empowers time-focused queries and efficient data partitioning. Additionally, the symbol type enhances the efficiency of managing and retrieving frequently used strings. The storage model explains how QuestDB organizes records and partitions within its tables, and the use of indexes can significantly accelerate read access for specific columns. Moreover, partitions provide substantial performance improvements for both calculations and queries. With its SQL extensions, users can achieve high-performance time series analysis using a streamlined syntax that simplifies complex operations. Overall, QuestDB stands out as a powerful tool for handling time-oriented data effectively.

Introducing a robust cross-platform columnar database designed for high-performance historical time-series data, which includes: - A compute engine optimized for in-memory operations - A streaming processor that functions in real time - A powerful query and programming language known as q Kdb+ drives the kdb Insights portfolio and KDB.AI, offering advanced time-focused data analysis and generative AI functionalities to many of the world's top enterprises. Recognized for its unparalleled speed, kdb+ has been independently benchmarked* as the leading in-memory columnar analytics database, providing exceptional benefits for organizations confronting complex data challenges. This innovative solution significantly enhances decision-making capabilities, enabling businesses to adeptly respond to the ever-evolving data landscape. By leveraging kdb+, companies can gain deeper insights that lead to more informed strategies.

InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge. To get started, InfluxData offers free training through InfluxDB University.

A Time Series Database (TSDB) is designed for rapid data input and output, allowing for swift reading and writing of information. It achieves impressive compression rates that lead to economical data storage solutions. Moreover, this service facilitates visualization techniques, such as precision reduction, interpolation, and multi-metric aggregation, alongside the processing of query results. By utilizing TSDB, businesses can significantly lower their storage expenses while enhancing the speed of data writing, querying, and analysis. This capability allows for the management of vast quantities of data points and enables more frequent data collection. Its applications span various sectors, including IoT monitoring, enterprise energy management systems (EMSs), production security oversight, and power supply monitoring. Additionally, TSDB is instrumental in optimizing database structures and algorithms, capable of processing millions of data points in mere seconds. By employing an advanced compression method, it can minimize each data point's size to just 2 bytes, leading to over 90% savings in storage costs. Consequently, this efficiency not only benefits businesses financially but also streamlines operational workflows across different industries.

Proficy Historian stands out as a premier historian software solution designed to gather industrial time-series and A&E data at remarkable speeds, ensuring secure and efficient storage, distribution, and rapid access for analysis, ultimately enhancing business value. With a wealth of experience and a track record of thousands of successful implementations globally, Proficy Historian transforms how organizations operate and compete by making critical data accessible for analyzing asset and process performance. The latest version of Proficy Historian offers improved usability, configurability, and maintainability thanks to significant advancements in its architecture. Users can leverage the solution's powerful yet straightforward features to derive new insights from their equipment, process data, and business strategies. Additionally, the remote collector management feature enhances user experience, while horizontal scalability facilitates comprehensive data visibility across the enterprise, making it an essential tool for modern businesses. By adopting Proficy Historian, companies can unlock untapped potential and drive operational excellence.

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.

Amazon FinSpace streamlines the deployment of kdb Insights applications on AWS, making the process significantly easier. By automating the routine tasks necessary for provisioning, integrating, and securing the infrastructure needed for kdb Insights, Amazon FinSpace simplifies operations for its users. Furthermore, it offers intuitive APIs that enable customers to set up and initiate new kdb Insights applications in just a matter of minutes. This platform allows users the flexibility to transition their existing kdb Insights applications to AWS, harnessing the advantages of cloud computing without the burden of managing complex and expensive infrastructure. KX's kdb Insights serves as a robust analytics engine, tailored for the examination of both real-time and extensive historical time-series data. Frequently utilized by clients in Capital Markets, kdb Insights supports essential business functions such as options pricing, transaction cost analysis, and backtesting. Additionally, it eliminates the need to integrate more than 15 AWS services for the deployment of kdb, streamlining the entire process further. Overall, Amazon FinSpace empowers organizations to focus on their analytics while minimizing operational overhead.

Amazon Forecast is an entirely managed service that employs machine learning techniques to provide exceptionally precise predictions. In the contemporary business landscape, organizations utilize a range of tools, from basic spreadsheets to intricate financial planning applications, in their quest to accurately project future outcomes such as product demand, resource allocation, and overall financial results. These forecasting tools generate predictions by analyzing historical data known as time series data. For instance, they might estimate future demand for raincoats based solely on past sales figures, operating under the premise that future performance will mirror historical trends. However, this methodology can falter when tasked with managing extensive datasets that exhibit irregular patterns. Moreover, it often struggles to seamlessly integrate evolving data streams—like pricing, discounts, web traffic, and workforce numbers—with pertinent independent variables, such as product specifications and retail locations. As a result, businesses seeking reliable forecasts may find themselves facing significant challenges in adapting to the complexities of their data.

kdb Insights is an advanced analytics platform built for the cloud, enabling high-speed real-time analysis of both live and past data streams. It empowers users to make informed decisions efficiently, regardless of the scale or speed of the data, and boasts exceptional price-performance ratios, achieving analytics performance that is up to 100 times quicker while costing only 10% compared to alternative solutions. The platform provides interactive data visualization through dynamic dashboards, allowing for immediate insights that drive timely decision-making. Additionally, it incorporates machine learning models to enhance predictive capabilities, identify clusters, detect patterns, and evaluate structured data, thereby improving AI functionalities on time-series datasets. With remarkable scalability, kdb Insights can manage vast amounts of real-time and historical data, demonstrating effectiveness with loads of up to 110 terabytes daily. Its rapid deployment and straightforward data ingestion process significantly reduce the time needed to realize value, while it natively supports q, SQL, and Python, along with compatibility for other programming languages through RESTful APIs. This versatility ensures that users can seamlessly integrate kdb Insights into their existing workflows and leverage its full potential for a wide range of analytical tasks.

InsightFinder Unified Intelligence Engine platform (UIE) provides human-centered AI solutions to identify root causes of incidents and prevent them from happening. InsightFinder uses patented self-tuning, unsupervised machine learning to continuously learn from logs, traces and triage threads of DevOps Engineers and SREs to identify root causes and predict future incidents. Companies of all sizes have adopted the platform and found that they can predict business-impacting incidents hours ahead of time with clearly identified root causes. You can get a complete overview of your IT Ops environment, including trends and patterns as well as team activities. You can also view calculations that show overall downtime savings, cost-of-labor savings, and the number of incidents solved.

With ServerInternals, users have immediate access to all critical information, facilitating swift diagnostics that lead directly to identifying the underlying issues and implementing appropriate solutions. There's no longer a necessity to utilize Performance Monitor and ponder which counter values to gather, nor to check Services for failures, or to delve into Event Viewer and create intricate filters to sift through extraneous data. Additionally, connecting to the server to examine CPU usage, memory consumption, and running processes via Task Manager is rendered unnecessary. The integration of performance metrics, event logs, service statuses, and process details, paired with intuitive drill-down navigation, ensures a streamlined and effective root-cause analysis of any issues that arise. If needed, corrective measures can be executed straight from the ServerInternals interface. The use of color-coded status indicators, gauges, charts, and lists allows for a comprehensive presentation of a wide array of information, enhancing user experience and operational efficiency. This holistic approach not only saves time but also empowers users to manage server performance proactively.

You can quickly and easily examine machine data to identify the root cause of IT problems faster. Log aggregation, filtering, filtering, alerting, and tagging are all part of this intuitive and powerfully designed system. Integrated with Orion Platform products, it allows for a single view of IT infrastructure monitoring logs. Because we have experience as network and system engineers, we can help you solve your problems. Log data is generated by your infrastructure to provide performance insight. Log Analyzer log monitoring tools allow you to collect, consolidate, analyze, and combine thousands of Windows, syslog, traps and VMware events. This will enable you to do root-cause analysis. Basic matching is used to perform searches. You can perform searches using multiple search criteria. Filter your results to narrow down the results. Log monitoring software allows you to save, schedule, export, and export search results.

Cornerstone data analysis software enhances the efficiency of designing experiments and exploring data while allowing users to analyze dependencies and derive actionable insights immediately and interactively, all without requiring programming skills. It facilitates an engineer-friendly approach to executing statistical tasks, freeing users from the complexities of statistical intricacies. The software enables quick detection of correlations within data, even when operating within a Big Data framework. By employing statistically optimized experimental designs, it minimizes the number of experiments needed and accelerates the overall development process. Additionally, it supports rapid identification of usable process models and root-cause analysis through exploratory and visual data examination. Structured planning, efficient data collection, and thorough result analysis further optimize the experiments conducted. Users can easily investigate the impact of noise in process variables on the corresponding responses, and the software automatically captures compact, reusable workflows for future use, making it an invaluable tool for data-driven decision-making. Ultimately, Cornerstone empowers users to streamline their data analysis and experiment processes significantly.

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

A parallel query engine designed for efficient access to time- and symbol-indexed data. It incorporates an extended SQL syntax that allows for sophisticated filtering and aggregation capabilities. Users can unify quotes, trades, snapshots, and reference data within a single environment. The platform supports strategy backtesting using high-frequency data for enhanced analysis. It facilitates quantitative research and insights into market microstructure. Additionally, it offers detailed transaction cost analysis and comprehensive rollup reporting features. Market surveillance mechanisms and anomaly detection capabilities are also integrated into the system. The decomposition of non-transparent ETF/ETN instruments is supported, along with the utilization of FAST, SBE, and proprietary communication protocols. A plain text protocol is available alongside consolidated and direct data feeds. The system includes built-in tools for monitoring latency and provides end-of-day archival options. It can perform ETL processes from both institutional and retail financial data sources. Designed with a parallel SQL engine that features syntax extensions, it allows advanced filtering by trading session, auction stage, and index composition for precise analysis. Optimizations for aggregates related to OHLCV and VWAP calculations enhance performance. An interactive SQL console with auto-completion improves user experience, while an API endpoint facilitates seamless programmatic integration. Scheduled SQL reporting options are available, allowing delivery via email, file, or web. JDBC and ODBC drivers ensure compatibility with various applications, making this system a versatile tool for financial data handling.

Eugenie's robust decision-making framework empowers industrial companies to extract maximum value from their assets and processes. At Eugenie, we seamlessly integrate AI as a powerful yet invisible force that enhances operational efficiency and dependability in industrial settings. Our platform is designed to foster a harmonious blend of technology, efficiency, and trust. With a distinctive framework centered on Explainable AI, Eugenie provides decision-makers with actionable, data-driven insights. Equipped with thorough root-cause analysis and predictive capabilities, the digital ecosystem of Eugenie facilitates informed decision-making processes. The collaborative environment within Eugenie harmonizes human abilities with machine intelligence. By adopting an AI-first strategy, Eugenie prioritizes user-centric design to enhance the reliability of both machines and processes. We view technology as a vital partner in boosting human productivity. Additionally, Eugenie's agile digital infrastructure is tailored to rapidly generate insights for industrial applications, ensuring that organizations can adapt swiftly to changing conditions. This commitment to innovation positions Eugenie as a leader in transforming industrial operations for the better.

Crafted by pharmacy experts for the benefit of healthcare practitioners, Pharmapod stands out as the premier cloud-based software dedicated to enhancing operational efficiencies while minimizing Patient Safety Incidents (PSIs) within community pharmacies, long-term care facilities, and hospitals. As the first of its kind, this innovative platform facilitates the aggregation and exchange of patient safety data across different regions, allowing for the identification of trends and underlying factors behind medication errors, thereby equipping local healthcare professionals to enhance their practices effectively. Driven by a team of professionals, including pharmacists, Pharmapod emphasizes a collaborative approach, having evolved to also cater to the requirements of other healthcare providers, such as doctors and nurses. The Pharmapod Solution is not only smart and user-friendly but also tailored specifically to the profession, enabling pharmacists to methodically document medication-related incidents and risks while conducting thorough root-cause analyses to foster continuous improvement in patient safety standards. This comprehensive approach ensures that all healthcare professionals can contribute to a safer medication management environment.

Sightline EDM: Improved Operations, Right Out of the Box Predictive analytics and performance and risk-based monitoring used to be a complicated process. Between endless Excel files and disjointed communication between departments, a lot of information was lost. When you switch to Sightline EDM, you can start making the best decisions for your operations, prepare for the future, and begin saving time and money immediately in one easy-to-use platform. One Easy-to-Use Dashboard Data from multiple monitoring tools can be consolidated into a single display: a uniform, easy-to-use dashboard with drill-down details. Real-Time OT & IT Intelligence With configurable notifications to any errors or anomalies, visualize and analyze production and operations in minutes, not months. Scalable Usability for All Organizations & Teams Proven, enterprise-grade, scalable software solution with role-based access controls, security, and user views that works with all web browsers and mobile devices. Pre-Built Integrations Across Systems Data from PLCs, CNC machines, process equipment, ERP/MES systems, and other vital data sources is gathered in minutes, not months, using open, agent, and agentless interfaces.