
NetCrunch is commercial, self-hosted, agentless network and IT infrastructure monitoring software for Windows Server. It monitors network devices, servers, virtualization platforms, cloud services including AWS, Azure, and Google Cloud, applications, websites, logs, telemetry, and custom data using technologies such as SNMP, WMI, REST APIs, and scripts.
NetCrunch supports 680+ monitoring targets and provides 270+ ready-to-use Monitoring Packs for devices, applications, and operating systems. Policy-based monitoring automatically applies monitoring settings, Monitoring Packs, thresholds, and alerts to matching devices and systems. Licensing is based on monitored nodes and network interfaces rather than individual sensors, checks, or metrics.
Real-time dashboards and automatic Layer 2 and routing topology maps provide visibility into network status and performance. NetCrunch supports event correlation, dependency-aware alert suppression, predictive thresholds, escalation, and 40+ automated response actions, including script execution, notifications, webhooks, and integrations with external IT and collaboration tools.
NetCrunch also provides hardware and software inventory, network device configuration backup and change tracking, bandwidth monitoring, and network traffic analysis using NetFlow, sFlow, IPFIX, and other flow technologies. Distributed Monitoring Probes extend monitoring to remote and isolated locations, while REST APIs support integration and automation with external systems.
NetCrunch is self-hosted on Windows Server and can monitor on-premises, air-gapped, cloud, and hybrid IT environments.
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RaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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PawSQL
PawSQL represents the forefront of query optimization techniques within the database industry, providing advanced SQL rewriting capabilities and sophisticated index recommendations designed to tackle slow-running queries. With the backing of a robust optimization engine and a community of over 10,000 database professionals worldwide, PawSQL offers a comprehensive suite of SQL enhancement strategies along with intelligent index suggestions. It also includes a versatile audit rule framework compatible with a variety of database systems such as MySQL, PostgreSQL, openGauss, and Oracle, guaranteeing a consistent auditing process across different database environments. This rule-based SQL analysis zeroes in on identifying potential correctness issues and areas ripe for performance improvement. In addition to its rich rewrite optimization capabilities, PawSQL proposes semantically equivalent but more efficient SQL statements, while a cost-based validation process ensures that the alternatives generated from SQL rewrites and index suggestions offer better performance results. As a result, PawSQL's intelligent index recommendation feature empowers users to fine-tune their query performance significantly, making it an indispensable tool for database optimization. Ultimately, this combination of features not only enhances the efficiency of database operations but also contributes to a more streamlined user experience.
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dbForge Index Manager
dbForge Index Manager for SQL Server is an intuitive tool crafted for database professionals to identify and rectify index fragmentation problems. It compiles statistics on index fragmentation, presents comprehensive data through a visual interface, pinpoints indexes requiring maintenance, and offers actionable advice for remediation.
Notable Features:
- Comprehensive insights into all indexes within the database
- Adjustable thresholds for both rebuilding and reorganizing indexes
- Automatic resolution of index fragmentation challenges
- Script generation for the rebuilding and reorganizing of indexes, with options for saving and reusing
- Capability to export index analysis findings as in-depth reports
- Ability to scan across multiple databases for fragmented indexes
- Streamlined index analysis through sorting and searching functionalities
- Automation of tasks for regular index analysis and defragmentation via a command-line interface
Additionally, dbForge Index Manager integrates effortlessly with Microsoft SQL Server Management Studio (SSMS), enabling users to quickly familiarize themselves with its capabilities and seamlessly incorporate it into their existing workflows. This seamless integration enhances productivity and ensures that database maintenance can be managed efficiently.
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