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In-Memory Databases
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.
Key-Value Databases
Key-value databases are a type of NoSQL database that store data as pairs, where each unique key is associated with a value. This structure is simple and highly flexible, making key-value databases ideal for scenarios requiring fast access to data, such as caching, session management, and real-time applications. In these databases, the key acts as a unique identifier for retrieving or storing the value, which can be any type of data—strings, numbers, objects, or even binary data. Key-value stores are known for their scalability, performance, and ability to handle high volumes of read and write operations with low latency. These databases are particularly useful for applications that require quick lookups or high availability, such as online retail platforms, social networks, and recommendation systems.
XML Databases
XML databases are a type of database that stores, manages, and retrieves data in the XML (Extensible Markup Language) format. These databases are designed to handle semi-structured data, where data is stored in a tree-like structure using tags, making it more flexible than traditional relational databases. XML databases support querying and manipulating XML data using specialized languages such as XPath, XQuery, and XML Schema. They are commonly used in applications that require complex data structures, such as content management systems, document storage, and web services. XML databases allow for efficient handling of large and dynamic datasets while maintaining the hierarchical relationships between elements, making them suitable for applications that need to store and retrieve structured or semi-structured data efficiently.
Database Software
Database software and database management systems are a type of software designed to store, manage and retrieve data. It is used to organize all kinds of information in an efficient manner, allowing users to quickly access the data they need. Many databases are tailored for specific purposes and applications, ranging from transaction processing systems to large-scale analytics platforms. Database software may be used on its own or connected with other software services for complex operations.
AI Memory Layers
AI memory layers refer to specialized components within artificial intelligence architectures that store and retrieve contextual information to improve decision-making and learning. These layers enable models to remember past interactions, patterns, or data points, enhancing continuity and relevance in tasks like natural language processing or reinforcement learning. By incorporating memory layers, AI systems can better handle complex sequences, adapt to new inputs, and maintain state over longer durations. Memory layers can be implemented using techniques such as attention mechanisms, recurrent networks, or external memory modules. This capability is crucial for building more sophisticated, human-like AI that can learn from experience and context over time.
Graph Databases
Graph databases are specialized databases designed to store, manage, and query data that is represented as graphs. Unlike traditional relational databases that use tables to store data, graph databases use nodes, edges, and properties to represent and store data. Nodes represent entities (such as people, products, or locations), edges represent relationships between entities, and properties store information about nodes and edges. Graph databases are particularly well-suited for applications that involve complex relationships and interconnected data, such as social networks, recommendation engines, fraud detection, and network analysis.
Database Security Software
Database security software tools enable organizations to secure their databases, and ensure security compliance with database operations.
Columnar Databases
Columnar databases, also known as column-oriented databases or column-store databases, are a type of database that store data in columns instead of rows. Columnar databases have some advantages over traditional row databases including speed and efficiency.
Database Monitoring Tools
Database monitoring tools help businesses and IT teams track, analyze, and optimize the performance of their databases to ensure smooth operation, prevent downtime, and maintain data integrity. These tools typically provide features for real-time monitoring of database metrics such as query performance, response times, CPU and memory usage, and disk space utilization. Database monitoring software often includes alerting mechanisms for detecting issues such as slow queries or resource bottlenecks, as well as detailed reporting and analytics to improve database efficiency and scalability. By using these tools, organizations can proactively manage database health, troubleshoot problems, and optimize system performance.
Relational Database
Relational database software provides users with the tools to capture, store, search, retrieve and manage information in data points related to one another.
Database Backup Software
Database backup software solutions enable organizations to back up their databases so that they can restore the databases if necessary. Database backup software is essential for companies of all kinds that want to protect against corrupted data, broken hardware, or employee missteps.
Time Series Databases
Time series databases (TSDB) are databases designed to store time series and time-stamped data as pairs of times and values. Time series databases are useful for easily managing and analyzing time series.
NoSQL Database
NoSQL database software provides the tools to store, capture and retrieve of big data through the use of non tabular databases.
Distributed Databases
Distributed databases store data across multiple physical locations, often across different servers or even geographical regions, allowing for high availability and scalability. Unlike traditional databases, distributed databases divide data and workloads among nodes in a network, providing faster access and load balancing. They are designed to be resilient, with redundancy and data replication ensuring that data remains accessible even if some nodes fail. Distributed databases are essential for applications that require quick access to large volumes of data across multiple locations, such as global eCommerce, finance, and social media. By decentralizing data storage, they support high-performance, fault-tolerant operations that scale with an organization’s needs.
Database Virtualization Software
Database virtualization software provides IT professionals a solution for virtualization databases in order to allow the pooling and usage of resources to be allocated when needed.
Database Design Software
Database design software is a type of computer program used to create, modify and manage databases. It enables users to define the structure of a database and the relationships between different data fields. It also allows the user to perform various operations on existing databases such as editing, backing up, transferring data and creating reports.
Vector Databases
Vector databases are a type of database that use vector-based data structures, rather than the traditional relational models, to store information. They are used in artificial intelligence (AI) applications such as machine learning, natural language processing and image recognition. Vector databases support fast and efficient data storage and retrieval processes, making them an ideal choice for AI use cases. They also enable the integration of structured and unstructured datasets into a single system, offering enhanced scalability for complex projects.
Document Databases
Document databases are a type of NoSQL database designed to store, manage, and retrieve semi-structured data in the form of documents, typically using formats like JSON, BSON, or XML. Unlike traditional relational databases, document databases do not require a fixed schema, allowing for greater flexibility in handling diverse and evolving data structures. Each document in the database can contain different fields and data types, making it ideal for applications where data is complex and varied. These databases excel at scaling horizontally, making them well-suited for handling large volumes of data across distributed systems. Document databases are commonly used in modern web and mobile applications, where they provide efficient storage and fast access to rich, nested data structures.
OLAP Databases
OLAP (Online Analytical Processing) databases are designed to support complex queries and data analysis, typically for business intelligence and decision-making purposes. They enable users to interactively explore large volumes of multidimensional data, offering fast retrieval of insights across various dimensions such as time, geography, and product categories. OLAP databases use specialized structures like cubes to allow for rapid aggregation and calculation of data. These databases are highly optimized for read-heavy operations, making them ideal for generating reports, dashboards, and analytical queries. Overall, OLAP databases help organizations quickly analyze data to uncover patterns, trends, and insights for better decision-making.
SQL Databases
SQL databases are structured systems that use the Structured Query Language (SQL) to store, retrieve, and manage data. They organize data into tables with rows and columns, ensuring that information is easily accessible, consistent, and scalable. SQL databases are widely used in applications that require complex queries, transactions, and data integrity, making them essential for web applications, financial systems, and enterprise environments. These databases offer robust features for security, data normalization, and maintaining relationships between different datasets. Overall, SQL databases are fundamental to managing relational data efficiently and reliably across various industries.
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  • 1
    Dragonfly

    Dragonfly

    DragonflyDB

    Dragonfly is a drop-in Redis replacement that cuts costs and boosts performance. Designed to fully utilize the power of modern cloud hardware and deliver on the data demands of modern applications, Dragonfly frees developers from the limits of traditional in-memory data stores. The power of modern cloud hardware can never be realized with legacy software. Dragonfly is optimized for modern cloud computing, delivering 25x more throughput and 12x lower snapshotting latency when compared to...
    16 Ratings
    Starting Price: Free
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  • 2
    MongoDB Atlas
    The most innovative cloud database service on the market, with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. MongoDB Atlas is the global cloud database service for modern applications. Deploy fully managed MongoDB across AWS, Google Cloud, and Azure with best-in-class automation and proven practices that guarantee availability, scalability, and compliance with the most demanding data...
    1,650 Ratings
    Starting Price: $0.08/hour
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  • 3
    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.
    12 Ratings
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  • 4
    Google Compute Engine
    ...General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. ...
    1,163 Ratings
    Starting Price: Free ($300 in free credits)
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  • 5
    Oracle Database
    Oracle database products offer customers cost-optimized and high-performance versions of Oracle Database, the world's leading converged, multi-model database management system, as well as in-memory, NoSQL, and MySQL databases. Oracle Autonomous Database, available on-premises via Oracle Cloud@Customer or in the Oracle Cloud Infrastructure, enables customers to simplify relational database environments and reduce management workloads. ...
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  • 6
    Apache Geode
    ...Take advantage of Apache Geode's unique technology that blends advanced techniques for data replication, partitioning and distributed processing. Apache Geode provides a database-like consistency model, reliable transaction processing and a shared-nothing architecture to maintain very low latency performance with high concurrency processing. Data can easily be partitioned (sharded) or replicated between nodes allowing performance to scale as needed. Durability is ensured through redundant in-memory copies and disk-based persistence. ...
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  • 7
    Percona Server for MongoDB
    ...Built on the MongoDB Community Edition, Percona Server for MongoDB provides flexible data structure, native high availability, easy scalability, and developer-friendly syntax. It also includes an in-memory engine, hot backups, LDAP authentication, database auditing, and log redaction.
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    50 Ratings
    Starting Price: Free
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  • 8
    Amazon MemoryDB
    Valkey- and Redis OSS-compatible, durable, in-memory database service for ultra-fast performance. Scale to hundreds of millions of requests per second and over one hundred terabytes of storage per cluster. Stores data durably using a multi-AZ transaction log for 99.99% availability and near-instantaneous recovery without data loss. Secure your data with encryption at rest and in transit, private VPC endpoints, and multiple authentication mechanisms, including IAM authentication. ...
    Starting Price: $0.2163 per hour
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  • 9
    Starcounter

    Starcounter

    Starcounter

    ...Full Visual Studio support including IntelliSense, debugger, and performance profiler. All the things you like, minus the headache. Write regular C# syntax with MVVM pattern to leverage ACID in-memory technology and thin client UI for extreme performance. Starcounter technology adds business value from day one. We leverage technology that’s already developed and in production, processing millions of business transactions for high-demand customers. Starcounter combines ACID in-memory database and application server into a single platform unmatched in performance, simplicity, and price.
    Starting Price: Free
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  • 10
    Oracle TimesTen
    Oracle TimesTen In-Memory Database (TimesTen) delivers real time application performance (low response time and high throughput) by changing the assumptions around where data resides at runtime. By managing data in memory, and optimizing data structures and access algorithms accordingly, database operations execute with maximum efficiency achieving dramatic gains in responsiveness and throughput.
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  • 11
    Symas LMDB

    Symas LMDB

    Symas Corporation

    Symas LMDB is an extraordinarily fast, memory-efficient database we developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases. Bottom line, with only 32KB of object code, LMDB may seem tiny. But it’s the right 32KB. Compact and efficient are two sides of a coin; that’s part of what makes LMDB so powerful.
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  • 12
    HyperSQL DataBase

    HyperSQL DataBase

    The hsql Development Group

    HSQLDB (HyperSQL DataBase) is the leading SQL relational database system written in Java. It offers a small, fast multithreaded and transactional database engine with in-memory and disk-based tables and supports embedded and server modes. It includes a powerful command line SQL tool and simple GUI query tools. HSQLDB supports the widest range of SQL Standard features seen in any open source database engine: SQL:2016 core language features and an extensive list of SQL:2016 optional features. ...
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  • 13
    memcached

    memcached

    memcached

    You can think of it as a short-term memory for your applications. memcached allows you to take memory from parts of your system where you have more than you need and make it accessible to areas where you have less than you need. The first scenario illustrates the classic deployment strategy, however you'll find that it's both wasteful in the sense that the total cache size is a fraction of the actual capacity of your web farm, but also in the amount of effort required to keep the cache...
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  • 14
    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#.
    Starting Price: Free
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  • 15
    Exasol

    Exasol

    Exasol

    With an in-memory, columnar database and MPP architecture, you can query billions of rows in seconds. Queries are distributed across all nodes in a cluster, providing linear scalability for more users and advanced analytics. MPP, in-memory, and columnar storage add up to the fastest database built for data analytics. With SaaS, cloud, on premises and hybrid deployment options you can analyze data wherever it lives.
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  • 16
    Amazon ElastiCache
    Amazon ElastiCache allows you to seamlessly set up, run, and scale popular open-Source compatible in-memory data stores in the cloud. Build data-intensive apps or boost the performance of your existing databases by retrieving data from high throughput and low latency in-memory data stores. Amazon ElastiCache is a popular choice for real-time use cases like Caching, Session Stores, Gaming, Geospatial Services, Real-Time Analytics, and Queuing.
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  • 17
    PowerOLAP

    PowerOLAP

    PARIS Technologies International

    Tap into timely and accurate data available across your organization, synchronized and delivered in real-time to the right people. Access through Excel, live information from your organization’s data sources, which have been connected through PowerOLAP’s in-memory database. Significantly reduce current reporting time and effort, and see dramatic increases in staff productivity. Enable faster budgeting cycles, dynamic report building, and advanced analytics through “multidimensional” views of your company’s business structure and performance. Ability to unite disparate systems for aggregated data from all key sources. ...
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  • 18
    Database Mart

    Database Mart

    Database Mart

    Database Mart offers a comprehensive suite of server hosting solutions tailored for diverse computing needs. Their VPS hosting provides isolated CPU, memory, and disk resources with full root or admin access, supporting various applications such as database hosting, mail servers, file sharing, SEO tools, and script testing. These VPS plans come with SSD storage, automated backups, and an intuitive control panel, making them ideal for individuals and small businesses seeking cost-effective solutions. ...
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  • 19
    Brytlyt

    Brytlyt

    Brytlyt

    Advanced GPU accelerated database for data performance at scale. With AI capabilities and an analytics visualisation workbench, you can generate smarter intelligence, quicker. Brytlyt are market leaders with a global vision. We understand the importance of data-driven business and can help you achieve it with rapidly accelerated analytics for millisecond performance. With Brytlyt, you can find meaning in massive amounts of data, at the speed of thought. Our end-to-end platform delivers...
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  • 20
    Lenovo ThinkAgile HX Series
    ...Now enhanced with new second-generation Intel processors for even faster performance, the ThinkAgile HX portfolio is optimized for a broad set of virtualized workloads, including Remote Office Branch Office; file, print, and email applications; analytics; and in-memory databases. Lenovo platforms hold the highest number of performance world records and have ranked #1 in reliability for six consecutive years.
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  • 21
    GridGain

    GridGain

    GridGain Systems

    The enterprise-grade platform built on Apache Ignite that provides in-memory speed and massive scalability for data-intensive applications and real-time data access across datastores and applications. Upgrade from Ignite to GridGain with no code changes and deploy your clusters securely at global scale with zero downtime. Perform rolling upgrades of your production clusters with no impact on application availability. Replicate across globally distributed data centers to load balance...
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  • 22
    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.
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  • 23
    AsparaDB

    AsparaDB

    Alibaba

    ApsaraDB for Redis is an automated and scalable tool for developers to manage data storage shared across multiple processes, applications or servers. As a Redis protocol compatible tool, ApsaraDB for Redis offers exceptional read-write capabilities and ensures data persistence by using memory and hard disk storage. ApsaraDB for Redis provides data read-write capabilities at high speed by retrieving data from in-memory caches and ensures data persistence by using both memory and hard disk storage mode. ApsaraDB for Redis supports advanced data structures such as leaderboard, counting, session, and tracking, which are not readily achievable through ordinary databases. ...
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  • 24
    Hazelcast

    Hazelcast

    Hazelcast

    In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record.
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  • 25
    Oracle Coherence
    Oracle Coherence is the industry leading in-memory data grid solution that enables organizations to predictably scale mission-critical applications by providing fast access to frequently used data. As data volumes and customer expectations increase, driven by the “internet of things”, social, mobile, cloud and always-connected devices, so does the need to handle more data in real-time, offload over-burdened shared data services and provide availability guarantees. The latest release of...
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  • 26
    eXtremeDB

    eXtremeDB

    McObject

    How is platform independent eXtremeDB different? - Hybrid data storage. Unlike other IMDS, eXtremeDB can be all-in-memory, all-persistent, or have a mix of in-memory tables and persistent tables - Active Replication Fabric™ is unique to eXtremeDB, offering bidirectional replication, multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more - Row & Columnar Flexibility for Time Series Data supports database designs that combine row-based and column-based layouts, in order to best leverage the CPU cache speed - Embedded and Client/Server. ...
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  • 27
    kdb+

    kdb+

    KX Systems

    A high-performance cross-platform historical time-series columnar database featuring: - An in-memory compute engine - A real-time streaming processor - An expressive query and programming language called q kdb+ powers kdb Insights portfolio and KDB.AI, together delivering time-oriented data insights and generative AI capabilities to the world’s leading enterprise organizations. Independently benchmarked* as the fastest in-memory, columnar analytics database available, kdb+ delivers unmatched value to businesses operating in the toughest data environments. kdb+ improves decision-making processes to help navigate rapidly changing data landscapes​.
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  • 28
    VertiPaq Analyzer
    ...Added measures for segments and partitions: pageable, resident, refresh date, last access. Analysis Services provides many Dynamic Management Views (DMV) to collect information about memory used by a data model. For example, DISCOVER_OBJECT_MEMORY_USAGE is a DMV that provides information about all the objects in memory. You can use such a DMV also to monitor a Multidimensional instance of Analysis Services. Kasper de Jonge created a sample model (BISM Memory Report) that organizes this data in a hierarchical way, making it easy to find the most expensive databases, tables, and columns on a server. ...
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  • 29
    TcaplusDB

    TcaplusDB

    Tencent

    TcaplusDB is a distributed NoSQL data storage service designed for games. Combining high-speed memory and SSDs, TcaplusDB enables games on global and regional servers to scale and merge with no downtime, making it suitable for sustaining rapid business growth and long-tail OPS. It also comes equipped with a comprehensive set of features, including high availability, disaster recovery, backup, and rollback, ensuring 24/7 data storage with 99.999% reliability. TcaplusDB features LRU-based...
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  • 30
    Altibase

    Altibase

    Altibase

    Altibase is an enterprise-grade, high-performance and relational open source database. A single database that delivers high-intensity data processing through an in-memory database portion and large storage capacity through an on-disk database portion. 10 times faster than conventional on-disk databases. Clients have consistently chosen Altibase over Oracle, IBM, Microsoft, and others. Altibase has replaced many traditional on-disk databases in various industries that require real time solutions since 1999. ...
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