RTView vs. Axibase Time Series Database

Assessing the health status of your applications serves as a vital indicator of the entire application ecosystem, encompassing aspects from physical infrastructure to middleware and the final user experience. By integrating health metrics from diverse technologies, you can achieve a more lucid understanding of the system's performance. Proactive monitoring should be implemented to detect stress points before they escalate into serious issues. It's crucial to establish correlations between performance metrics and the overall health of the applications. Make sure that this crucial information is easily accessible to facilitate collaboration among various teams. Are you still depending on separate management consoles for each product to monitor your middleware platforms? Such complexity is redundant and can hinder efficiency. Instead, you should be able to access all your middleware technologies through a single, unified interface. This approach allows you to gather data effectively without compromising performance. Make connections between performance metrics and key components such as hosts, networks, databases, and application servers. Start with a manageable scope and gradually expand as your requirements evolve. You can either utilize our packaged solutions for real-time monitoring of your applications and their underlying technologies or develop a customized real-time monitoring system using our high-performance integrated development environment (IDE). This streamlined methodology not only simplifies the monitoring process but can also lead to a significant enhancement in your overall operational efficiency. Additionally, ensuring that your monitoring tools are adaptable will allow for continuous improvement as your application landscape evolves.

An advanced parallel query engine enables efficient access to both time- and symbol-indexed data. It incorporates an upgraded SQL syntax that facilitates complex filtering and extensive aggregations. This innovative system merges diverse financial data types, including market quotes, trade transactions, snapshots, and reference information, into a unified database. Users can perform strategy backtesting with high-frequency datasets, engage in quantitative research, and analyze market microstructure dynamics. The platform offers in-depth transaction cost analysis alongside rollup reporting, which ensures a comprehensive understanding of trading activities. With integrated market surveillance features and anomaly detection tools, it enhances overall monitoring capabilities. It also has the capacity to break down opaque ETFs and ETNs while employing FAST, SBE, and proprietary protocols to boost performance. A straightforward text protocol simplifies usage, and both consolidated and direct data feeds are provided for seamless data ingestion. Additionally, built-in latency monitoring tools and extensive end-of-day data archives are part of the offering. The engine supports ETL processes from both institutional and retail financial data sources, and its parallel SQL engine comes with syntax extensions that allow for advanced filtering based on various parameters, such as trading sessions and auction stages. It further provides optimized calculations for OHLCV and VWAP metrics, enhancing analytical precision. An interactive SQL console with auto-completion features improves user interaction, while an API endpoint supports programmatic integration. Scheduled SQL reports can be generated with delivery options via email, file, or web, complemented by JDBC and ODBC drivers for wider accessibility.