
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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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.
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Google Cloud Timeseries Insights API
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.
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Avora
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.
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