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What is waiting?

Waiting is a lightweight library crafted to simplify the task of waiting for certain conditions to be fulfilled. It essentially halts execution until a specified function evaluates to True, providing a variety of operational modes to choose from. Furthermore, Waiting integrates smoothly with flux for simulating timelines, making it even more versatile. The most straightforward way to use it involves supplying a function for monitoring, and it is easy to wait indefinitely; if your predicate produces a result, that result becomes the output of wait(). Additionally, you can establish a timeout period, and if this time elapses without the predicate being satisfied, an exception will be raised. By default, the library checks the predicate every second, but this interval can be modified using the sleep_seconds parameter. When working with multiple predicates, Waiting presents two effective aggregation methods: any and all. These methods resemble Python's built-in any() and all(), but they ensure that a predicate is not called more often than necessary, which is especially advantageous for predicates that are resource-heavy and time-consuming. By optimizing these functions, Waiting significantly improves both the efficiency of asynchronous operations and the overall user experience, making it an essential tool for developers. In summary, this library not only simplifies waiting processes but also enhances performance through its thoughtful design.

What is SQL Workload Analysis?

Keep an eye on and assess wait states in databases along with transaction specifics. The efficiency of SQL Server and the vital applications it underpins can be greatly hindered by inefficient SQL queries. The SQL Workload Analysis add-on facilitates ongoing monitoring and assessment of server load. It boasts an intuitive user interface that emphasizes application performance and wait states exclusively. Additionally, you have the capability to troubleshoot modifications in SQL code for database applications. With continuous SQL sampling intervals, real-time analysis becomes possible, enabling you to quickly spot where databases allocate their time. You can swiftly pinpoint sluggish SQL statements and delve deeper for practical insights. Moreover, you can explore historical trends in query plans. Utilizing automated suggestions can significantly enhance query performance and optimize overall database efficiency. Leveraging these tools empowers teams to proactively manage database health and ensure optimal application performance.

Media

Media

Integrations Supported

Python

Integrations Supported

Amazon EC2
Azure Virtual Machines
SQL Server

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

$400 per instance
USD 400 per instance with first year maintenance included; add-on to SQL Diagnostic Manager for SQL Server, together with SQL Query Tuner
Free Trial Offered?

Supported Platforms

Windows
Mac
Linux

Supported Platforms

Windows

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Python Software Foundation

Company Location

United States

Company Website

pypi.org/project/waiting/

Company Facts

Organization Name

IDERA, an Idera, Inc. company

Date Founded

2004

Company Location

United States of America

Company Website

www.idera.com/productssolutions/sqlserver/sql-workload-analysis

Categories and Features

Component Libraries

Not specified

Categories and Features

Database

Monitoring
Performance Analysis
Queries

Database Monitoring

Anomaly Detection
Capacity Planning
Dashboard
Historical Trend Analysis
Notifications / Alerts
Performance Monitoring
Query Analysis
Resource Optimization
Troubleshooting

SQL Server

CPU Monitoring
History Tracking
User Activity Monitoring

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