Alternatives to FairCom DB

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.

Amazon ElastiCache enables users to effortlessly establish, operate, and expand widely-used open-source compatible in-memory data stores in the cloud environment. It empowers the development of data-driven applications or enhances the efficiency of existing databases by allowing quick access to data through high throughput and minimal latency in-memory stores. This service is particularly favored for various real-time applications such as caching, session management, gaming, geospatial services, real-time analytics, and queuing. With fully managed options for Redis and Memcached, Amazon ElastiCache caters to demanding applications that necessitate response times in the sub-millisecond range. Functioning as both an in-memory data store and a cache, it is designed to meet the needs of applications that require rapid data retrieval. Furthermore, by utilizing a fully optimized architecture that operates on dedicated nodes for each customer, Amazon ElastiCache guarantees incredibly fast and secure performance for its users' critical workloads. This makes it an essential tool for businesses looking to enhance their application's responsiveness and scalability.

Redis Labs is the home of Redis. Redis Enterprise is the best Redis version. Redis Enterprise is more than a cache. Redis Enterprise can be free in the cloud with NoSQL and data caching using the fastest in-memory database. Redis can be scaled, enterprise-grade resilience, massive scaling, ease of administration, and operational simplicity. Redis in the Cloud is a favorite of DevOps. Developers have access to enhanced data structures and a variety modules. This allows them to innovate faster and has a faster time-to-market. CIOs love the security and expert support of Redis, which provides 99.999% uptime. Use relational databases for active-active, geodistribution, conflict distribution, reads/writes in multiple regions to the same data set. Redis Enterprise offers flexible deployment options. Redis Labs is the home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.

SAP HANA Cloud serves as a fully managed in-memory database as a service (DBaaS) that operates in the cloud. Functioning as the essential data backbone for the SAP Business Technology Platform, it assimilates information from various sectors of the organization, allowing for quicker decision-making based on real-time data. This platform empowers users to construct data solutions using contemporary architectures, yielding actionable insights instantly. As the cloud variant of SAP HANA, it provides the same robust capabilities while being scalable to fit specific requirements, allowing for the processing of diverse business data and facilitating advanced analytics on live transactions with minimal need for optimization. Users can effortlessly connect to distributed data through native integrations, develop applications and tools both in the cloud and on-premises, and manage transient data efficiently. By establishing a singular source of truth, enterprises can access reliable information while ensuring security, privacy, and data anonymization, all upheld by a foundation of enterprise-grade reliability. Furthermore, SAP HANA Cloud supports the evolving needs of businesses as they adapt to dynamic market conditions.

Amazon DynamoDB is a versatile key-value and document database that provides exceptional single-digit millisecond performance, regardless of scale. As a fully managed service, it offers multi-region, multimaster durability along with integrated security features, backup and restore capabilities, and in-memory caching designed for internet-scale applications. With the ability to handle over 10 trillion requests daily and support peak loads exceeding 20 million requests per second, it serves a wide range of businesses. Prominent companies like Lyft, Airbnb, and Redfin, alongside major enterprises such as Samsung, Toyota, and Capital One, rely on DynamoDB for their critical operations, leveraging its scalability and performance. This allows organizations to concentrate on fostering innovation without the burden of operational management. You can create an immersive gaming platform that manages player data, session histories, and leaderboards for millions of users simultaneously. Additionally, it facilitates the implementation of design patterns for various applications like shopping carts, workflow engines, inventory management, and customer profiles. DynamoDB is well-equipped to handle high-traffic, large-scale events seamlessly, making it an ideal choice for modern applications.

What makes eXtremeDB platform independent? - Hybrid storage of data. Unlike other IMDS databases, eXtremeDB databases are all-in-memory or all-persistent. They can also have a mix between persistent tables and in-memory table. eXtremeDB's Active Replication Fabric™, which is unique to eXtremeDB, offers bidirectional replication and multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more. - Row and columnar flexibility for time series data. eXtremeDB supports database designs which combine column-based and row-based layouts in order to maximize the CPU cache speed. - Client/Server and embedded. eXtremeDB provides data management that is fast and flexible wherever you need it. It can be deployed as an embedded system and/or as a clients/server database system. eXtremeDB was designed for use in resource-constrained, mission-critical embedded systems. Found in over 30,000,000 deployments, from routers to satellites and trains to stock market world-wide.

Utilize Ignite as a conventional SQL database by employing JDBC drivers, ODBC drivers, or the dedicated SQL APIs that cater to Java, C#, C++, Python, and various other programming languages. Effortlessly perform operations such as joining, grouping, aggregating, and ordering your distributed data, whether it is stored in memory or on disk. By integrating Ignite as an in-memory cache or data grid across multiple external databases, you can enhance the performance of your existing applications by a factor of 100. Envision a cache that allows for SQL querying, transactional operations, and computational tasks. Develop contemporary applications capable of handling both transactional and analytical workloads by leveraging Ignite as a scalable database that exceeds the limits of available memory. Ignite smartly allocates memory for frequently accessed data and resorts to disk storage when dealing with less frequently accessed records. This allows for the execution of kilobyte-sized custom code across vast petabytes of data. Transform your Ignite database into a distributed supercomputer, optimized for rapid calculations, intricate analytics, and machine learning tasks, ensuring that your applications remain responsive and efficient even under heavy loads. Embrace the potential of Ignite to revolutionize your data processing capabilities and drive innovation within your projects.

Oracle Coherence stands out as the premier in-memory data grid solution, empowering organizations to effectively scale their critical applications by offering rapid access to often-used data. With the growth of data volumes and the rising expectations of customers—propelled by the internet of things, social media, mobile technology, cloud computing, and the prevalence of always-connected devices—there is an escalating demand for real-time data management, relief for overloaded shared data services, and assurance of availability. The recent update, version 14.1.1, introduces a unique scalable messaging feature, enables polyglot programming on GraalVM at the grid level, incorporates distributed tracing within the grid, and ensures certification with JDK 11. Coherence manages data by storing each item across several members, including one primary and multiple backup copies, and it does not deem any modification complete until the backups are securely created. This design guarantees that your data grid remains resilient to failures, whether they affect a single JVM or an entire data center, thereby enhancing reliability and performance. Ultimately, Oracle Coherence facilitates a robust framework for organizations to thrive in a data-driven world.

In-Memory Computing Platform. Digital world is different. Microseconds are important. The world's most important organizations rely on us for powering their most sensitive applications at scale. If they meet the current requirement for immediate access, new data-enabled apps can transform your business. Hazelcast solutions can be used to complement any database and deliver results that are much faster than traditional systems of record. Hazelcast's distributed architecture ensures redundancy and continuous cluster up-time, as well as always available data to support the most demanding applications. The capacity grows with demand without compromising performance and availability. The cloud delivers the fastest in-memory data grid and third-generation high speed event processing.

Oracle TimesTen In-Memory Database (TimesTen) enhances real-time application performance by rethinking the runtime data storage approach, resulting in reduced response times and increased throughput. By utilizing in-memory data management and refining data structures alongside access algorithms, TimesTen maximizes the efficiency of database operations, leading to significant improvements in both responsiveness and transaction throughput. The launch of TimesTen Scaleout introduces a shared-nothing architecture that builds on the existing in-memory capabilities, enabling seamless scaling across numerous hosts, accommodating vast data volumes of hundreds of terabytes, and processing hundreds of millions of transactions per second, all without requiring manual sharding or workload distribution. This innovative approach not only streamlines performance but also simplifies the overall database management experience for users.

VMware Tanzu GemFire is a high-speed, distributed in-memory key-value storage solution that excels in executing read and write operations. It provides robust parallel message queues, ensuring continuous availability and an event-driven architecture that can be dynamically scaled without any downtime. As the demand for data storage grows to accommodate high-performance, real-time applications, Tanzu GemFire offers effortless linear scalability. Unlike traditional databases, which may lack the necessary reliability for microservices, Tanzu GemFire serves as an essential caching solution in modern distributed architectures. This platform enables applications to achieve low-latency responses for data retrieval while consistently delivering up-to-date information. Furthermore, applications can subscribe to real-time events, allowing them to quickly respond to changes as they occur. Continuous queries in Tanzu GemFire alert your application when new data becomes accessible, significantly reducing the load on your SQL database and enhancing overall performance. By integrating Tanzu GemFire, organizations can achieve a seamless data management experience that supports their growing needs.

Develop high-speed, data-centric applications that can dynamically adapt to performance needs regardless of scale. Leverage the distinctive technology of Apache Geode, which integrates sophisticated methods for data replication, partitioning, and distributed processing. With a database-like consistency model, Apache Geode guarantees dependable transaction handling and employs a shared-nothing architecture that supports remarkably low latency, even under high concurrency. The platform allows for seamless data partitioning (sharding) and replication across nodes, enabling performance to grow in accordance with demand. Reliability is bolstered by maintaining redundant in-memory copies along with disk-based persistence. Additionally, it features rapid write-ahead logging (WAL) persistence, optimized for quick parallel recovery of individual nodes or the entire cluster, ensuring robust performance even during failures. This combination of features not only enhances efficiency but also significantly improves overall system resilience.

SAP HANA is an in-memory database designed to handle both transactional and analytical workloads using a single copy of data, regardless of type. It effectively dissolves the barriers between transactional and analytical processes within organizations, facilitating rapid decision-making whether deployed on-premises or in the cloud. This innovative database management system empowers users to create intelligent, real-time solutions, enabling swift decision-making from a unified data source. By incorporating advanced analytics, it enhances the capabilities of next-generation transaction processing. Organizations can build data solutions that capitalize on cloud-native attributes such as scalability, speed, and performance. With SAP HANA Cloud, businesses can access reliable, actionable information from one cohesive platform while ensuring robust security, privacy, and data anonymization, reflecting proven enterprise standards. In today's fast-paced environment, an intelligent enterprise relies on timely insights derived from data, emphasizing the need for real-time delivery of such valuable information. As the demand for immediate access to insights grows, leveraging an efficient database like SAP HANA becomes increasingly critical for organizations aiming to stay competitive.

Aerospike is the global leader for next-generation, real time NoSQL data solutions at any scale. Aerospike helps enterprises overcome seemingly impossible data bottlenecks and compete with other companies at a fraction of the cost and complexity of legacy NoSQL databases. Aerospike's Hybrid Memory Architecture™ is a patented technology that unlocks the full potential of modern hardware and delivers previously unimaginable value. It does this by delivering unimaginable value from huge amounts of data at both the edge, core, and in the cloud. Aerospike empowers customers with the ability to instantly combat fraud, dramatically increase shopping cart sizes, deploy global digital payment networks, and provide instant, one-to-1 personalization for millions. Aerospike customers include Airtel and Banca d'Italia as well as Snap, Verizon Media, Wayfair, PayPal, Snap, Verizon Media, and Nielsen. The company's headquarters is in Mountain View, California. Additional locations are in London, Bengaluru, India, and Tel Aviv in Israel.

This robust enterprise platform, built on Apache Ignite, delivers lightning-fast in-memory performance and extensive scalability for data-heavy applications, ensuring real-time access across various datastores and applications. Transitioning from Ignite to GridGain requires no code modifications, allowing for secure deployment of clusters on a global scale without experiencing any downtime. You can conduct rolling upgrades on your production clusters without affecting application availability, and replicate data across geographically dispersed data centers to balance workloads and mitigate the risk of outages in specific regions. Your data remains secure both at rest and in transit, while compliance with security and privacy regulations is guaranteed. Seamless integration with your organization’s existing authentication and authorization frameworks is straightforward, and comprehensive auditing of data and user activities can be enabled. Additionally, you can establish automated schedules for both full and incremental backups, ensuring that restoring your cluster to its most stable state is achievable through snapshots and point-in-time recovery. This platform not only promotes efficiency but also enhances resilience and security for all data operations.

GridDB utilizes multicast communication to form its cluster, so it's essential to configure the network for this purpose. Start by verifying the host name and IP address; you can do this by running the command “hostname -i” to check the host's IP address configuration. If the reported IP address matches the specified value below, you can proceed directly to the next section without any further network adjustments. GridDB is a database designed to manage a collection of data entries, each consisting of a key paired with several values. In addition to functioning as an in-memory database that organizes all data within the memory, it also supports a hybrid architecture that combines both memory and disk storage, which can include solid-state drives (SSDs). This flexibility allows for efficient data management and retrieval, catering to various application needs.

Oracle's database offerings provide clients with cost-effective and high-efficiency options, including the renowned multi-model database management system, as well as in-memory, NoSQL, and MySQL databases. The Oracle Autonomous Database, which can be accessed on-premises through Oracle Cloud@Customer or within the Oracle Cloud Infrastructure, allows users to streamline their relational database systems and lessen management burdens. By removing the intricacies associated with operating and securing Oracle Database, Oracle Autonomous Database ensures customers experience exceptional performance, scalability, and reliability. Furthermore, organizations concerned about data residency and network latency can opt for on-premises deployment of Oracle Database. Additionally, clients who rely on specific versions of Oracle databases maintain full authority over their operational versions and the timing of any updates. This flexibility empowers businesses to tailor their database environments according to their unique requirements.

Our cutting-edge in-memory technology, alongside our application server, allows you to create exceptionally fast enterprise software without the need for custom tools or unfamiliar syntax. Starcounter applications can deliver performance improvements ranging from 50 to 1000 times while maintaining simplicity and ease of use. You can develop these applications using standard C#, LINQ, and SQL, with ACID transactions also implemented in familiar C# code. The platform provides full support for Visual Studio, including features like IntelliSense, a debugger, and a performance profiler—everything you love about development, but without unnecessary complications. By employing standard C# syntax and the MVVM pattern, you can harness our ACID in-memory technology alongside a lightweight client UI to achieve remarkable performance. Starcounter's technology starts delivering business value right from the outset, utilizing proven solutions that are already handling millions of transactions for high-demand clients. This integration of the ACID in-memory database and an application server into a single platform offers unmatched performance, simplicity, and affordability. Ultimately, Starcounter empowers developers to build robust applications that not only meet but exceed modern business demands.

Couchbase distinguishes itself from other NoSQL databases by delivering an enterprise-grade, multicloud to edge solution that is equipped with the powerful features essential for mission-critical applications on a platform that is both highly scalable and reliable. This distributed cloud-native database operates seamlessly in contemporary dynamic settings, accommodating any cloud environment, whether it be customer-managed or a fully managed service. Leveraging open standards, Couchbase merges the advantages of NoSQL with the familiar structure of SQL, thereby facilitating a smoother transition from traditional mainframe and relational databases. Couchbase Server serves as a versatile, distributed database that integrates the benefits of relational database capabilities, including SQL and ACID transactions, with the adaptability of JSON, all built on a foundation that is remarkably fast and scalable. Its applications span various industries, catering to needs such as user profiles, dynamic product catalogs, generative AI applications, vector search, high-speed caching, and much more, making it an invaluable asset for organizations seeking efficiency and innovation.

Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.

ScyllaDB serves as an ideal database solution for applications that demand high performance and minimal latency, catering specifically to data-intensive needs. It empowers teams to fully utilize the growing computing capabilities of modern infrastructures, effectively removing obstacles to scaling as data volumes expand. Distinct from other database systems, ScyllaDB stands out as a distributed NoSQL database that is completely compatible with both Apache Cassandra and Amazon DynamoDB, while incorporating significant architectural innovations that deliver outstanding user experiences at significantly reduced costs. Over 400 transformative companies, including Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung, rely on ScyllaDB to tackle their most challenging database requirements. Furthermore, ScyllaDB is offered in various formats, including a free open-source version, a fully-supported enterprise solution, and a fully managed database-as-a-service (DBaaS) available across multiple cloud platforms, ensuring flexibility for diverse user needs. This versatility makes it an attractive choice for organizations looking to optimize their database performance.

SingleStore, previously known as MemSQL, is a highly scalable and distributed SQL database that can operate in any environment. It is designed to provide exceptional performance for both transactional and analytical tasks while utilizing well-known relational models. This database supports continuous data ingestion, enabling operational analytics critical for frontline business activities. With the capacity to handle millions of events each second, SingleStore ensures ACID transactions and allows for the simultaneous analysis of vast amounts of data across various formats, including relational SQL, JSON, geospatial, and full-text search. It excels in data ingestion performance at scale and incorporates built-in batch loading alongside real-time data pipelines. Leveraging ANSI SQL, SingleStore offers rapid query responses for both current and historical data, facilitating ad hoc analysis through business intelligence tools. Additionally, it empowers users to execute machine learning algorithms for immediate scoring and conduct geoanalytic queries in real-time, thereby enhancing decision-making processes. Furthermore, its versatility makes it a strong choice for organizations looking to derive insights from diverse data types efficiently.

RocksDB is a high-performance database engine that employs a log-structured design and is entirely implemented in C++. It treats keys and values as byte streams of arbitrary sizes, allowing for flexibility in data representation. Specifically designed for rapid, low-latency storage solutions such as flash memory and high-speed disks, RocksDB capitalizes on the impressive read and write speeds provided by these technologies. The database supports a range of fundamental operations, from basic tasks like opening and closing a database to more complex functions such as merging and applying compaction filters. Its versatility makes RocksDB suitable for various workloads, including database storage engines like MyRocks as well as application data caching and embedded systems. This adaptability ensures that developers can rely on RocksDB for a wide spectrum of data management needs in different environments.

Valkey is a robust, in-memory database service that is compatible with Redis OSS, delivering exceptional speed and performance. It can efficiently handle hundreds of millions of requests per second and supports over one hundred terabytes of storage within a single cluster. The service ensures data durability via a multi-AZ transaction log, providing an impressive 99.99% availability and the capability for nearly instantaneous recovery without any data loss. To protect your data, it offers encryption both at rest and in transit, as well as private VPC endpoints and various authentication options, including IAM authentication. Developers can quickly create applications utilizing Valkey and Redis OSS data structures along with a comprehensive open-source API, allowing for seamless integration with other AWS services. By leveraging this powerful infrastructure, you can deliver real-time, personalized experiences with top-notch relevancy and the quickest semantic search capabilities found among leading vector databases on AWS. This service not only streamlines application development but also enhances time-to-market by providing easy access to versatile data structures inherent in Valkey and Redis OSS, thus enabling developers to focus on innovation rather than infrastructure.

Altibase stands out as a robust, high-performance relational database, designed for enterprise use and available as an open-source solution. It combines the speed of in-memory processing with the extensive storage capabilities of on-disk databases, achieving performance that is tenfold faster than traditional on-disk systems. Businesses have consistently favored Altibase over major competitors like Oracle, IBM, and Microsoft due to its effectiveness. Since its inception in 1999, Altibase has successfully transitioned numerous conventional on-disk databases in various sectors that demand real-time data solutions. The platform boasts over 650 enterprise clients globally, including 8 companies from the Fortune Global 500, and supports thousands of critical deployments across the world. With a wealth of mature features and functionalities, Altibase's open-source nature is complemented by its advanced scale-out technology, known as sharding. Additionally, it offers a cost-effective alternative with no licensing fees, alongside flexible subscription options. With two decades of expertise, Altibase has effectively addressed more than 6,000 mission-critical use cases, affirming its reliability in high-stakes environments.

ApsaraDB for Redis is a highly automated and scalable solution designed for developers to efficiently manage shared data storage across various applications, processes, or servers. Compatible with the Redis protocol, this tool boasts impressive read-write performance and guarantees data persistence by utilizing both memory and hard disk storage options. By accessing data from in-memory caches, ApsaraDB for Redis delivers rapid read-write capabilities while ensuring that data remains reliable and persistent through its dual storage modes. It also supports sophisticated data structures like leaderboards, counters, sessions, and tracking, which are typically difficult to implement with standard databases. Additionally, ApsaraDB for Redis features an enhanced version known as "Tair." Tair has been effectively managing data caching for Alibaba Group since 2009, showcasing remarkable performance during high-demand events like the Double 11 Shopping Festival, further solidifying its reputation in the field. This makes ApsaraDB for Redis and Tair invaluable tools for developers looking to optimize data handling in large-scale applications.

Businesses require a solution to maintain seamless operations of their systems, enhance data processing speed, and ensure storage reliability. In-memory technologies have emerged as effective tools for addressing these challenges. For over a decade, Tarantool has been assisting organizations globally in creating intelligent caches, data marts, and comprehensive client profiles while optimizing server utilization. This approach not only reduces the expenses associated with storing credentials compared to isolated solutions but also enhances both the service and security of client applications. Furthermore, it lowers the costs of data management by minimizing the number of separate systems that hold customer identities. By analyzing user behavior and data, companies can boost sales through improved speed and accuracy in recommending products or services. Additionally, enhancing the performance of mobile and web channels can significantly reduce user attrition. In the context of large organizations, IT systems often operate within a closed network loop, which poses risks as data circulates without adequate protection. Consequently, it becomes imperative for corporations to adopt robust strategies that not only safeguard their data but also ensure optimal system functionality.

Consider it a temporary memory solution for your applications. Memcached enables you to reallocate memory from areas of your system that have an excess to those that are experiencing a shortfall. While the initial example shows a traditional deployment approach, it is inefficient because the total cache size only represents a small portion of your web farm's true capacity, and maintaining cache consistency across numerous nodes requires significant effort. With memcached, all servers draw from a unified virtual memory pool, simplifying operations. Furthermore, as your application's demand increases, necessitating the addition of more servers, there is typically a corresponding rise in the volume of frequently accessed data. A deployment strategy that allows these two components of your system to scale in tandem is a more logical and efficient approach. This synergy not only optimizes resource use but also enhances overall system performance.

Ehcache is a widely-used open-source caching solution that enhances performance, reduces database load, and makes scaling more straightforward. Its popularity among Java developers stems from its reliability, comprehensive features, and seamless integration with various libraries and frameworks. The cache can accommodate needs ranging from in-process caching to larger mixed deployments that handle terabyte-scale data. With Terracotta overseeing its development, maintenance, and support, Ehcache continues to thrive as a professional open-source project licensed under Apache 2.0. The community encourages contributors to engage and help improve this valuable tool. This collaborative spirit not only strengthens the project but also fosters innovation and growth within the caching ecosystem.

LedisDB is a fast NoSQL database system and library developed in Go. While it shares similarities with Redis, it distinguishes itself by storing data on disk. The library accommodates various data structures such as key-value pairs, lists, hashes, sorted sets, and sets. Additionally, LedisDB has evolved to support multiple backend databases, enhancing its versatility and usability for different applications. This makes it an appealing choice for developers seeking efficient data storage solutions.

Symas LMDB is an incredibly swift and memory-efficient database that we created specifically for the OpenLDAP Project. Utilizing memory-mapped files, it achieves the read speed typical of purely in-memory databases while also providing the durability associated with traditional disk-based systems. In essence, despite its modest size of just 32KB of object code, LMDB packs a significant punch; it is indeed the perfect 32KB. The compact nature and efficiency of LMDB are integral to its remarkable capabilities. For those integrating LMDB into their applications, Symas provides fixed-price commercial support. Development is actively carried out in the mdb.master branch of the OpenLDAP Project’s git repository. Moreover, LMDB has garnered attention across numerous impressive products and publications, highlighting its versatility and effectiveness in various contexts. Its widespread recognition further cements its status as a vital tool for developers.

Introducing an advanced GPU-accelerated database designed to enhance data performance at scale, Brytlyt integrates AI capabilities with an analytics visualization workbench, enabling the generation of smarter intelligence in a fraction of the time. As leaders in the market with a forward-thinking global vision, we recognize the significance of data-driven decision-making and provide rapidly accelerated analytics that deliver millisecond performance. With Brytlyt, you can uncover insights from vast datasets at the speed of thought. Our comprehensive platform ensures that you receive critical business insights and support for your decisions. Built on PostgreSQL, it allows for seamless analysis of larger datasets, facilitating fast and effortless data processing. Extract meaningful intelligence in mere milliseconds while managing extensive data without losing any details. Our system is designed to adapt and customize as your data needs evolve, ensuring smooth integration into your existing infrastructures. Brytlyt not only empowers you to discover value when you need it but also positions you ahead of the competition, making data a true asset for your business. The transformative potential of our platform paves the way for innovative strategies and smarter business operations.

Enhance performance by utilizing a scalable, secure, and highly available in-memory service tailored for Redis and Memcached. Memorystore simplifies complex procedures associated with open source Redis and Memcached, such as ensuring high availability, managing failover, conducting patching, and monitoring, allowing developers to focus more on coding. You can begin with the most basic tier and smallest configuration, gradually expanding your instance with minimal disruption. Memorystore for Memcached has the capacity to manage clusters up to 5 TB, delivering millions of queries per second at remarkably low latency. In contrast, Memorystore for Redis instances are designed to be replicated across two zones, offering a service level agreement of 99.9% availability. Continuous monitoring and automatic failover mechanisms ensure that applications face minimal interruptions. You can select from two of the most widely used open source caching solutions to develop your applications. Memorystore provides full protocol compatibility for both Redis and Memcached, enabling you to choose the caching engine that best aligns with your budget and availability needs while maximizing your application's performance. By leveraging these features, developers can significantly improve their operational efficiency.

Riak is a distributed systems expert and works with Application teams to overcome distributed system challenges. Riak's Riak®, a distributed NoSQL databank, delivers: Unmatched resilience beyond the typical "high availability" offerings - Innovative technology to ensure data accuracy, and never lose a word. - Massive scale for commodity hardware - A common code foundation that supports true multi-model support Riak®, offers all of this while still focusing on ease-of-use. Choose Riak®, KV flexible key value data model for web scale profile management, session management, real time big data, catalog content management, customer 360, digital message and other use cases. Choose Riak®, TS for IoT, time series and other use cases.

Redis for Windows alternative, In Memory Datastore Ready for the most challenging production workloads. Free for testing and development. Redis-compatibility. Memurai's core is based on Redis source code and port to Windows natively. Memurai supports all features that make Redis one of the most popular NoSQL databases, including persistence, replication, transactions and LRU eviction. Redis has many libraries and tools that have been carefully tested to ensure compatibility. You can even replicate data between Memurai or Redis, or both within the same cluster. Integration with Windows infrastructure and workflows is seamless. Memurai seamlessly integrates into Windows best practices, tools, and workflows, regardless of whether it's being used for production or development. Teams of engineers with existing investments in Windows infrastructure will be eligible for this program.

QuasarDB, the core of Quasar's intelligence, is an advanced, distributed, column-oriented database management system specifically engineered for high-performance timeseries data handling, enabling real-time processing for massive petascale applications. It boasts up to 20 times less disk space requirement, making it exceptionally efficient. The unmatched ingestion and compression features of QuasarDB allow for up to 10,000 times quicker feature extraction. This database can perform real-time feature extraction directly from raw data via an integrated map/reduce query engine, a sophisticated aggregation engine that utilizes SIMD capabilities of contemporary CPUs, and stochastic indexes that consume minimal disk storage. Its ultra-efficient resource utilization, ability to integrate with object storage solutions like S3, innovative compression methods, and reasonable pricing structure make it the most economical timeseries solution available. Furthermore, QuasarDB is versatile enough to operate seamlessly across various platforms, from 32-bit ARM devices to high-performance Intel servers, accommodating both Edge Computing environments and traditional cloud or on-premises deployments. Its scalability and efficiency make it an ideal choice for businesses aiming to harness the full potential of their data in real-time.

Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads. Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis. Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps. Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.

Volt Active Data is a sophisticated data platform designed to streamline your entire technology stack, enhancing speed and cost-effectiveness, enabling applications and businesses to effortlessly scale in alignment with the extremely low latency service level agreements (SLAs) demanded by 5G, IoT, edge computing, and future innovations. It is tailored to complement your current big data assets, including NoSQL, Hadoop, Kubernetes, Kafka, and conventional databases or data warehouses, as it replaces the multiple layers usually necessary for making contextual decisions on streaming data with a singular, cohesive layer that facilitates ingestion to action in under 10 milliseconds. The digital landscape is inundated with data that is generated, stored, often overlooked, and ultimately discarded. "Active Data" refers to the information that requires immediate action for businesses to derive value from it. Numerous traditional and NoSQL data storage solutions are available for managing such data; however, there exists also a category of data that can be monetized, provided that swift action is taken to 'influence the moment' before the opportunity slips away. By harnessing the capabilities of Volt Active Data, organizations can ensure they are not merely collecting data but effectively leveraging it for real-time decision-making and strategic advantage.

Welcome to H2, a Java SQL database designed for efficient data management. In its embedded mode, an application can access the database directly within the same Java Virtual Machine (JVM) using JDBC, making it the quickest and simplest connection method available. However, a drawback of this setup is that the database can only be accessed by one virtual machine and class loader at a time. Like other modes, it accommodates both persistent and in-memory databases without restrictions on the number of simultaneous database accesses or open connections. On the other hand, the mixed mode combines features of both embedded and server modes; the initial application that connects to the database operates in embedded mode while simultaneously launching a server to enable other applications in different processes or virtual machines to access the same data concurrently. This allows local connections to maintain the high speed of the embedded mode, whereas remote connections may experience slight delays. Overall, H2 provides a flexible and robust solution for various database needs.

As the volume of traffic and user demands on your application grows, enhance its performance in a straightforward and economical way. Implementing a caching layer within your application architecture can efficiently manage thousands of concurrent users, providing near-instantaneous response times, all while leveraging the advantages of a fully managed service. Achieve remarkable throughput and performance capable of processing millions of requests per second with sub-millisecond latency. This fully managed service includes automatic updates, patching, scaling, and provisioning, allowing you to concentrate on development without distraction. Integration of modules like RedisBloom, RediSearch, and RedisTimeSeries empowers your application with comprehensive capabilities for data analysis, search functionality, and real-time streaming. You will benefit from robust features such as clustering, built-in replication, Redis on Flash, and an impressive availability rate of up to 99.99 percent, ensuring reliability. Furthermore, by complementing services like Azure SQL Database and Azure Cosmos DB, you can enhance your data tier's throughput scalability at a more economical rate compared to merely expanding database instances. Ultimately, these enhancements not only improve the user experience but also position your application for future growth and adaptability.

SQLite is a C-language library that offers a compact, efficient, and reliable SQL database engine that is fully featured. Recognized as the most popular database engine globally, SQLite is embedded in every mobile device and the majority of computers, while also being included in a myriad of applications that are used daily by individuals. Operating as an in-process library, SQLite provides a self-sufficient, serverless, and zero-configuration transactional SQL database engine. The source code of SQLite resides in the public domain, making it available for anyone to use freely, whether for commercial or personal purposes. With its extensive deployment and integration into numerous applications, SQLite stands out as an invaluable tool for developers in various high-profile projects. Its versatility and ease of use contribute to its unmatched popularity in the database landscape.

When seeking a database that ensures both scalability and high availability without sacrificing performance, Apache Cassandra stands out as an ideal option. Its linear scalability paired with proven fault tolerance on standard hardware or cloud services positions it as an excellent choice for handling mission-critical data effectively. Additionally, Cassandra's superior capability to replicate data across several datacenters not only enhances user experience by reducing latency but also offers reassurance in the event of regional failures. This combination of features makes it a robust solution for organizations that prioritize data resilience and efficiency.

Voldemort does not function as a relational database, as it does not aim to fulfill arbitrary relations while adhering to ACID properties. It also does not operate as an object database that seeks to seamlessly map object reference structures. Additionally, it does not introduce a novel abstraction like document orientation. Essentially, it serves as a large, distributed, durable, and fault-tolerant hash table. For applications leveraging an Object-Relational (O/R) mapper such as ActiveRecord or Hibernate, this can lead to improved horizontal scalability and significantly enhanced availability, albeit with a considerable trade-off in convenience. In the context of extensive applications facing the demands of internet-level scalability, a system is often comprised of multiple functionally divided services or APIs, which may handle storage across various data centers with their own horizontally partitioned storage systems. In these scenarios, the possibility of performing arbitrary joins within the database becomes impractical, as not all data can be accessed within a single database instance, making data management even more complex. Consequently, developers must adapt their strategies to navigate these limitations effectively.

InterSystems Cache®, a high-performance database, powers transaction processing applications all over the globe. It's used for everything, from mapping a million stars in the Milky Way to processing a trillion equity trades per day to managing smart energy grids. InterSystems has developed Cache, a multi-model (object-relational, key-value), DBMS and application server. InterSystems Cache offers multiple APIs that allow you to work with the same data simultaneously: key/value, relational/object, document, multidimensional, object, object, and object. Data can be managed using SQL, Java, node.js.NET, C++ and Python. Cache also offers an application server that hosts web apps (CSP, REST, SOAP and other types TCP access for Cache data).

Introducing a versatile, open-source multi-cloud platform for contemporary data applications, built on Apache Cassandra™. Achieve global-scale performance with guaranteed 100% uptime while avoiding vendor lock-in. You have the flexibility to deploy on multi-cloud environments, on-premises infrastructures, or use Kubernetes. The platform is designed to be elastic and offers a pay-as-you-go pricing model to enhance total cost of ownership. Accelerate your development process with Stargate APIs, which support NoSQL, real-time interactions, reactive programming, as well as JSON, REST, and GraphQL formats. Bypass the difficulties associated with managing numerous open-source projects and APIs that lack scalability. This solution is perfect for various sectors including e-commerce, mobile applications, AI/ML, IoT, microservices, social networking, gaming, and other highly interactive applications that require dynamic scaling based on demand. Start your journey of creating modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Leverage REST, GraphQL, and JSON alongside your preferred full-stack framework. This platform ensures that your richly interactive applications are not only elastic but also ready to gain traction from the very first day, all while offering a cost-effective Apache Cassandra DBaaS that scales seamlessly and affordably as your needs evolve. With this innovative approach, developers can focus on building rather than managing infrastructure.

An in-memory, column-oriented database combined with a Massively Parallel Processing (MPP) architecture enables the rapid querying of billions of records within mere seconds. The distribution of queries across all nodes in a cluster ensures linear scalability, accommodating a larger number of users and facilitating sophisticated analytics. The integration of MPP, in-memory capabilities, and columnar storage culminates in a database optimized for exceptional data analytics performance. With various deployment options available, including SaaS, cloud, on-premises, and hybrid solutions, data analysis can be performed in any environment. Automatic tuning of queries minimizes maintenance efforts and reduces operational overhead. Additionally, the seamless integration and efficiency of performance provide enhanced capabilities at a significantly lower cost compared to traditional infrastructure. Innovative in-memory query processing has empowered a social networking company to enhance its performance, handling an impressive volume of 10 billion data sets annually. This consolidated data repository, paired with a high-speed engine, accelerates crucial analytics, leading to better patient outcomes and improved financial results for the organization. As a result, businesses can leverage this technology to make quicker data-driven decisions, ultimately driving further success.

InterSystems IRIS, a cloud-first data platform, is a multi-model transactional database management engine, application development platform, interoperability engine and open analytics platform. InterSystems IRIS offers a variety of APIs that allow you to work with transactional persistent data simultaneously. These include key-value, relational and object, document, and multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS features an Interoperability engine as well as modules for building AI solutions. InterSystems IRIS features horizontal scalability (sharding and ECP), and High Availability features such as Business intelligence, transaction support and backup.

Leverage precise and timely data available within your organization, seamlessly synchronized and provided in real-time to the appropriate stakeholders. Gain access to live insights directly from your organization’s data repositories via Excel, facilitated by PowerOLAP’s in-memory database connections. This approach can significantly minimize the time and effort spent on reporting, leading to remarkable enhancements in employee productivity. Experience quicker budgeting processes, the ability to create dynamic reports, and sophisticated analytics through comprehensive "multidimensional" perspectives of your business's structure and performance metrics. Unify various systems to compile data from all essential sources, fostering collaboration across teams with ease through simple updates. Harness the power of business intelligence analytics to enable informed decision-making based on real-time data, ultimately driving your organization towards greater efficiency and success. Adaptability and a seamless flow of information empower teams to thrive in a data-driven environment.

InfinityDB Embedded is a NoSQL database written in Java, designed as a hierarchical sorted key-value store. Its features include high performance, multi-core capability, flexibility, and a maintenance-free operation. In addition to the embedded version, InfinityDB now offers an Encrypted database and a Client/Server database. Customer feedback and performance evaluations indicate that InfinityDB delivers the highest performance in its class: its multi-core overlapping operations demonstrate nearly linear scalability with thread count, employ fair scheduling, and maintain very low inter-thread interference. Furthermore, random I/O performance improves logarithmically with file size, with no upper limit on size, while caches expand only as necessary and are efficiently packed. Notably, opening the database is instantaneous, even after an unexpected shutdown, ensuring minimal downtime and quick recovery. With these attributes, InfinityDB stands out as a top choice for developers seeking reliability and speed in their database solutions.

Transform and enhance your transaction-driven applications both on-premise and in the cloud by using SAP Adaptive Server Enterprise (SAP ASE). This cutting-edge SQL database server utilizes a relational management framework designed to satisfy the increasing needs for performance, reliability, and efficiency across various sectors. Streamline your operations and cut costs with features like workload analyzer and workload profiler that ensure built-in high availability, effective disaster recovery, and optimal resource management. Expand your capacity for transactions, data, and users while boosting performance with advanced technology solutions, including MemScale and XOLTP. By minimizing overhead on production databases, Q-Free employees can concentrate more on driving innovation and delivering value. You can deploy SAP ASE either on-premise or through infrastructure as a service (IaaS), ensuring high performance and availability essential for executing mission-critical transactions. Additionally, this versatility allows businesses to adapt to evolving market demands swiftly.