Compare the Top In-Memory Databases for Windows as of May 2025

What are In-Memory Databases for Windows?

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 Windows currently available using the table below. This list is updated regularly.

  • 1
    RaimaDB

    RaimaDB

    Raima

    RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.
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  • 2
    SQL Server

    SQL Server

    Microsoft

    Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.
    Starting Price: Free
  • 3
    SAP HANA
    SAP HANA in-memory database is for transactional and analytical workloads with any data type — on a single data copy. It breaks down the transactional and analytical silos in organizations, for quick decision-making, on premise and in the cloud. Innovate without boundaries on a database management system, where you can develop intelligent and live solutions for quick decision-making on a single data copy. And with advanced analytics, you can support next-generation transactional processing. Build data solutions with cloud-native scalability, speed, and performance. With the SAP HANA Cloud database, you can gain trusted, business-ready information from a single solution, while enabling security, privacy, and anonymization with proven enterprise reliability. An intelligent enterprise runs on insight from data – and more than ever, this insight must be delivered in real time.
  • 4
    QuasarDB

    QuasarDB

    QuasarDB

    Quasar's brain is QuasarDB, a high-performance, distributed, column-oriented timeseries database management system designed from the ground up to deliver real-time on petascale use cases. Up to 20X less disk usage. Quasardb ingestion and compression capabilities are unmatched. Up to 10,000X faster feature extraction. QuasarDB can extract features in real-time from the raw data, thanks to the combination of a built-in map/reduce query engine, an aggregation engine that leverages SIMD from modern CPUs, and stochastic indexes that use virtually no disk space. The most cost-effective timeseries solution, thanks to its ultra-efficient resource usage, the capability to leverage object storage (S3), unique compression technology, and fair pricing model. Quasar runs everywhere, from 32-bit ARM devices to high-end Intel servers, from Edge Computing to the cloud or on-premises.
  • 5
    H2

    H2

    H2

    Welcome to H2, the Java SQL database. In embedded mode, an application opens a database from within the same JVM using JDBC. This is the fastest and easiest connection mode. The disadvantage is that a database may only be open in one virtual machine (and class loader) at any time. As in all modes, both persistent and in-memory databases are supported. There is no limit on the number of database open concurrently, or on the number of open connections. The mixed mode is a combination of the embedded and the server mode. The first application that connects to a database does that in embedded mode, but also starts a server so that other applications (running in different processes or virtual machines) can concurrently access the same data. The local connections are as fast as if the database is used in just the embedded mode, while the remote connections are a bit slower.
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