### Contents - [**Discussions**](#resources-discussions) # Other Analytics Software Resources ##### Discussions to expand your knowledge on Other Analytics Software Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find [discussions](#resources-discussions) from users like you. [ContentsExpand/Collapse Contents](#) - [**Discussions**](#resources-discussions) ## Other Analytics Software Discussions 0 Question on: SolarWinds Database Observability [How does SolarWinds Database Observability perform in terms of analytics depth and total cost of ownership?](/discussions/how-does-solarwinds-database-observability-perform-in-terms-of-analytics-depth-and-total-cost-of-ownership) One of SolarWinds’ standout strengths is how quickly and clearly it surfaces performance issues across various database environments. Its support for SQL Server, Oracle, PostgreSQL, MySQL, and others is robust, with deep visibility into query performance, wait events, and resource bottlenecks. The real-time analytics are actionable and easy to navigate, and I’ve found the historical performance trending and anomaly detection surprisingly powerful, even compared to some newer platforms. For teams dealing with mission-critical, high-throughput databases, SolarWinds offers the level of insight you need without overwhelming complexity. The platform also benefits from tight integration with the broader SolarWinds ecosystem, making it easy to correlate database behavior with app and infrastructure telemetry if you’re using other SolarWinds tools. I’ve had a positive experience so far, but I’d love to hear from others: - How has SolarWinds performed for your team at scale, especially in hybrid or multi-cloud environments? - Any tips on getting the most out of its analytics and alerting capabilities? - If you’ve compared TCO across observability platforms, how does SolarWinds stack up? Oh, I forgot to mention—one thing I’ve really come to appreciate is how intuitive the UI is, even for folks who aren’t deep DBAs. It makes collaboration with devs and SREs smoother since they can jump in and interpret performance data without needing a ton of training. Also, the alerts are surprisingly easy to tune—you’re not stuck drowning in noise like with some other platforms. Definitely a plus I should’ve called out earlier. Answered: Ross Briggs on June 26, 2025 [Your answer](/discussions/how-does-solarwinds-database-observability-perform-in-terms-of-analytics-depth-and-total-cost-of-ownership/comments/new?remote=true) 0 Question on: esProc SPL Community [Macros in SPL](/discussions/macros-in-spl) refers http://c.raqsoft.com/article/1687916213139 In addition to common static code, sometimes dynamic code is also needed to solve problems, such as generating code (or part of code) based on parameters and dynamically executing it. For programming languages that lack dynamic coding mechanisms, it is usually necessary to write the variable parts of the code in string form. For example, when referencing dataset field names in Python, it is necessary to write them as strings to achieve the effect of dynamic code. However, this will make it inconvenient to read and write more common static code. SQL, on the other hand, can directly write field names (as well as filter conditions, grouping expressions, etc.) in the code without having to write them into strings, making it easier to read and write static code, but it is difficult to handle dynamic code. SPL inherits the SQL style of static code, allowing for direct writing of code parts, such as field names, without the need to be written as strings. In addition, SPL also provides macros to achieve dynamic code effects. Example 1: Dynamically sort the order table based on the parameter pSortList, which contains an indefinite number of sorting fields separated by commas. This dynamic code can be implemented using SPL macros: T("Orders.txt").sort(${pSortList}) "Hadoop/Spark is too heavy, esProc SPL is light", refer to refer to http://c.raqsoft.com/article/1665212186752 With the advent of the era of big data, the amount of data continues to grow. In this case, it is difficult and costly to expand the capacity of database running on a traditional small computer, making it hard to support business development. In order to cope with this problem, many users begin to turn to the distributed computing route, that is, use multiple inexpensive PC servers to form a cluster to perform big data computing tasks. Hadoop/Spark is one of the important software technologies in this route, which is popular because it is open source and free. After years of application and development, Hadoop has been widely accepted, and not only can it be applied to data computing directly, but many new databases are developed based on it, such as Hive and Impala. Answered: Jason King on October 15, 2023 Integrate SPL and SQL. SQL and SPL are both general-purpose processing technologies for structured data, and each has its own characteristics. Specifically, SQL is highly popularized and widely used, many users have a natural ability to query data with SQL, and it is easy for them to get started once the data engine supports SQL; it is relatively easy to migrate historical programs. SPL is concise and efficient, providing more agile syntax that can simplify complex calculations, while supporting the procedural computing and naturally supporting step-wise coding; the computing system of SPL is more open, making it possible to perform mixed computing for multiple data sources at the same time, and easily obtain higher computing performance with built-in high-performance storage and high-performance algorithms; it is more flexible to utilize, enabling it to be used independently or integrated into applications. Refer to http://c.raqsoft.com/article/1672969702567 Answered: Jason King on November 16, 2023 Usually, the streaming data sources are dynamic and unbounded, and appear quite different from the static and bounded batch data source. For framework reasons, it is difficult for traditional database technologies to directly process streaming data source, so programmers have to resort to later technologies. The computing frameworks such as heron\samza\storm\spark\flink were the first to make breakthroughs and gained first-mover advantage in stream computing technology. These frameworks are so successful that as soon as a stream computing is involved, the application programmers will naturally turn to one of them. On the contrary, for those computing technologies that do not claim to be a certain framework, they are generally considered unsuitable for implementing stream computing. Refer to http://c.raqsoft.com/article/1693970501878 Answered: Jason King on September 15, 2023 [See more answers (2)](javascript:void(0);) [Your answer](/discussions/macros-in-spl/comments/new?remote=true) 0 Question on: Apache log4php [What is Apache log4php used for?](/discussions/what-is-apache-log4php-used-for) What is Apache log4php used for? It help to debug your code faster using the better log. it have several log levels, etc Answered: Nilaj Gupta on September 29, 2023 We use it as a company mainly as a library that helps us generate logs within our applications, internal developments, or in testing of them. Answered: Edwards Rafael Ortiz Arias on July 18, 2023 [See more answers (1)](javascript:void(0);) [Your answer](/discussions/what-is-apache-log4php-used-for/comments/new?remote=true) - ‹ Prev‹ Prev - 1 - [2](/categories/other-analytics/resources?discussions_page=2) - [3](/categories/other-analytics/resources?discussions_page=3) - [4](/categories/other-analytics/resources?discussions_page=4) - [5](/categories/other-analytics/resources?discussions_page=5) - … - [11](/categories/other-analytics/resources?discussions_page=11) - [12](/categories/other-analytics/resources?discussions_page=12) - [Next ›Next ›](/categories/other-analytics/resources?discussions_page=2)