
Most finance teams run two systems: one for lease accounting, one for treasury, reconciled by hand. ZenTreasury runs both as one governed subledger, because the ERP that posts the journal entry does not know the contract behind it. ZenTreasury does.
Add a lease and the platform generates the full schedule automatically: right of use asset, lease liability, depreciation, interest, and balance carry forward, all following the standard from the moment the lease is saved. Index-linked remeasurement is handled automatically, with index rates, base values, and next indexation dates tracked per contract. Every later change, such as a scope change, term extension, rate revision, or partial termination, recalculates the schedule and logs it with a timestamp and user, so auditors get the before and after picture without asking.
On the treasury side: centralised FX position management across forwards, swaps, and cross currency instruments with mark-to-market valuations; internal and external loan tracking with valuation against yield curves and automated interest accrual; trade finance and guarantee monitoring with fee and exposure tracking; and group wide cash flow forecasting with scenario modelling, all multi entity and multi currency. Direct bank connectivity included.
One platform, accounting included, priced to the scope you run. Every customer gets a dedicated, isolated database. Lease calculations are independently reviewed by an international audit firm. Connect Claude, ChatGPT, or any MCP client directly to your contract data.
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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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dbForge Index Manager
dbForge Index Manager for SQL Server is a user-friendly tool designed to help database specialists detect and resolve index fragmentation issues. It gathers index fragmentation statistics, displays detailed information in a visual interface, identifies indexes in need of maintenance, and provides recommendations for addressing these issues.
Key Features:
- Detailed information about all database indexes
- Customizable thresholds for rebuilding and reorganizing indexes
- Automatic resolving index fragmentation issues
- Generation of scripts for index rebuilding and reorganization with options to save and reuse them
- Exporting index analysis results as detailed reports
- Scanning multiple databases for fragmented indexes
- Efficient index analysis with sorting and searching through
- Task automation for regular index analysis and defragmentation via the command-line interface
dbForge Index Manager integrates seamlessly into Microsoft SQL Server Management Studio (SSMS), allowing users to quickly master its functionality and incorporate it into their workflows.
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SQL Defrag Manager
Automatically detect and fix fragmentation in your database index. SQL Server database administrators must ensure high availability and performance for their databases. Indexes that are out of cluster and fragmented are key areas that can dramatically impact the performance of SQL Server. SQL Defrag Manager is an innovative solution to defragment SQL Server indexes. It automates the tedious task of finding fragmented tables based on the policies specified for the databases.
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