Compare the Top In-Memory Databases that integrate with XML as of September 2025

This a list of In-Memory Databases that integrate with XML. Use the filters on the left to add additional filters for products that have integrations with XML. View the products that work with XML in the table below.

What are In-Memory Databases for XML?

In-memory databases store data directly in a system’s main memory (RAM) rather than on traditional disk-based storage, enabling much faster data access and processing. This approach significantly reduces latency and increases performance, making in-memory databases ideal for real-time analytics, high-frequency transactions, and applications requiring rapid data retrieval. They are often used in industries like finance, telecommunications, and e-commerce, where speed and scalability are critical. In-memory databases support both SQL and NoSQL models and typically include features for data persistence to avoid data loss during system shutdowns. Ultimately, they provide high-speed performance for time-sensitive applications while ensuring data availability and integrity. Compare and read user reviews of the best In-Memory Databases for XML currently available using the table below. This list is updated regularly.

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    Perst

    Perst

    McObject

    Perst is McObject’s open source, dual license, object-oriented embedded database system (ODBMS). It is available in one edition developed as an all-Java embedded database, and another implemented in C# (for Microsoft .NET Framework applications). Perst gives developers the ability to store, sort, and retrieve objects in their applications with maximum speed and with low memory and storage overhead while leveraging the object-oriented paradigm of Java and C#. In the TestIndex and PolePosition benchmarks, Perst displays one of its strongest features: its significant performance advantage over Java and .NET embedded database alternatives. Perst stores data directly in Java and .NET objects, eliminating the translation required for storage in relational and object-relational databases. This boosts run-time performance. Perst’s core consists of only five thousand lines of code. The small footprint imposes minimal demands on system resources.
    Starting Price: Free
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