Alternatives to VMware Tanzu GemFire

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.

SAP HANA Cloud (DBaaS) is a fully managed, in-memory cloud database. It is the cloud-based data foundation of SAP Business Technology Platform. It integrates data from across enterprises, enabling faster decisions based upon live data. Modern architectures allow you to build data solutions and gain real-time insights that are business-ready. The SAP HANA Cloud database is the data foundation of SAP Business Technology Platform. It offers the power and flexibility of SAP HANA in a cloud environment. Scale to meet your business needs, process all types of business data, and perform advanced analytics on live transactions for faster, better decision-making. Native integration allows you to connect to distributed data, develop tools and applications across clouds and on-premise, as well as store and manage volatile data. You can tap business-ready information by creating a single source of truth. This will enable security, privacy and anonymization with enterprise reliability.

Amazon DynamoDB, a key-value and document databank, delivers single-digit millisecond performance on any scale. It is a fully managed, multiregional, multimaster, durable database that offers built-in security, backup, restore, and in-memory cache for internet-scale apps. DynamoDB can process more than 10 trillion requests per hour and can handle peak requests of more than 20,000,000 requests per second. Many of the fastest-growing businesses in the world, such as Lyft, Redfin, and Airbnb, as well as enterprises like Samsung, Toyota and Capital One, rely on DynamoDB's scale and performance to support mission-critical workloads.

You can use Ignite as a traditional SQL Database by leveraging JDBC drivers or ODBC drivers. Or, you can use the native SQL APIs for Java, C# and C++, Python, or other programming languages. You can easily join, group, aggregate, or order your distributed on-disk and in-memory data. You can accelerate your existing applications up to 100x by using Ignite as an in memory cache or in-memory grid that is deployed over one of several external databases. You can query, transact, and calculate on this cache. Ignite is a database that scales beyond your memory capacity to support modern transactional and analytical workloads. Ignite allocates memory to your hot data and writes to disk when applications query cold records. Execute custom code up to kilobytes in size over petabytes. Your Ignite database can be transformed into a distributed supercomputer that can perform low-latency calculations, complex analysis, and machine learning.

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.

Amazon ElastiCache makes it easy to create, manage, and scale popular open source compatible in-memory cloud data stores. You can build data-intensive apps and improve the performance of existing databases by retrieving data in high-throughput and low latency, in-memory storages. Amazon ElastiCache is popular for real-time applications such as Caching, Session Stores and Gaming, Geospatial Service, Real-Time Analytics and Queuing. Amazon ElastiCache provides fully managed Redis, Memcached and other services for demanding applications that need sub-millisecond response time. Amazon ElastiCache is an in-memory cache and data store that can support the most demanding applications that require sub-millisecond response time. Amazon ElastiCache delivers secure, lightning fast performance by using an optimized stack that runs on customer-dedicated nodes.

The fastest NoSQL database in the world. The fastest NoSQL database available, capable of millions IOPS per node with less than 1 millisecond latency. This database will accelerate your application performance. Scylla, a drop-in Apache Cassandra and Amazon DynamoDB alternative, powers your applications with extreme throughput and ultra-low latency. To power modern, high-performance applications, we used the best features of high availability databases to create a NoSQL database that is significantly more efficient, fault-tolerant, and resource-efficient. This high-availability database is built from scratch in C++ for Linux. Scylla unleashes your infrastructure's true potential for running high-throughput/low-latency workloads.

Apache Ignite is an enterprise-grade platform that offers in-memory speed, massive scalability and real-time access across datastores. You can upgrade from Ignite or GridGain without any code changes and deploy your clusters securely on a global scale with zero downtime. Rolling upgrades can be performed on your production clusters without affecting application availability. To load balance workloads and prevent outages in regional areas, replicate across globally distributed data centres. You can protect your data in motion and at rest, and comply with security and privacy standards. Integrate with your organization's authorization and authentication system. Allow full data and user activity auditing. Automated schedules can be created for incremental and full backups. With snapshots and point in time recovery, restore your cluster to its last stable state.

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.

Oracle database products offer customers cost-optimized, high-performance versions Oracle Database, the world's most popular converged, multi-model database management software. They also include in-memory NoSQL and MySQL databases. Oracle Autonomous Database is available on-premises via Oracle Cloud@Customer and in the Oracle Cloud Infrastructure. It allows customers to simplify relational databases environments and reduce management burdens. Oracle Autonomous Database reduces the complexity of operating and protecting Oracle Database, while delivering the highest levels performance, scalability and availability to customers. Oracle Database can also be deployed on-premises if customers have network latency and data residency concerns. Customers who depend on Oracle database versions for their applications have full control over which versions they use and when they change.

Oracle Coherence, the industry's leading in-memory grid solution, enables organizations to scale mission-critical applications quickly by providing quick access to frequently used data. Data volumes and customer expectations are increasing due to the "internet-of-things", mobile, cloud, social, and cloud. This means that organizations need to be able handle more data in real time, offload redundant shared data services, and ensure availability. The 14.1.1 release of Oracle Coherence adds a patented scalable message implementation, support for polyglot grid side programming on GraalVM and distributed tracing in grid. Coherence stores each piece in multiple members (one primary, one or more backup copies), so that any mutating operation is not considered complete until the backup(s). This ensures that your data grid is resilient to failure at all levels, from a single JVM to a whole data center.

Dragonfly replaces Redis with a plug-and-play solution that reduces costs and improves performance. Dragonfly is designed to take full advantage of the power of cloud hardware, and meet the data needs of modern applications. It frees developers from traditional in-memory databases. Legacy software cannot take advantage of the power of modern cloud hardware. Dragonfly is optimized to work with modern cloud computing. It delivers 25x more throughput, and 12x less snapshotting latency, when compared to traditional in-memory stores like Redis. This makes it easy to provide the real-time experiences your customers expect. Due to Redis' inefficient single-threaded design, scaling Redis workloads can be expensive. Dragonfly has a much higher memory and compute efficiency, resulting in infrastructure costs that are up to 80% less. Dragonfly scales first vertically, and only requires clustering when the scale is extremely high. This results in an operational model that is simpler and more reliable.

FairCom DB is ideal to handle large-scale, mission critical core-business applications that demand performance, reliability, and scalability that cannot easily be achieved with other databases. FairCom DB provides predictable high-velocity transactions with big data analytics and massively parallel big-data processing. It provides developers with NoSQL APIs that allow them to process binary data at machine speed. ANSI SQL allows for simple queries and analysis over the same binary data. Verizon is one of the companies that has taken advantage of FairCom DB's flexibility. Verizon recently selected FairCom DB to be its in-memory database for the Verizon Intelligent Network Control Platform Transaction Server Migrating. FairCom DB, an advanced database engine, gives you a Continuum of Control that allows you to achieve unparalleled performance at a low total cost of ownership (TCO). FairCom DB doesn't conform to you. FairCom DB conforms. FairCom DB doesn't force you to conform to the database's limitations.

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.

Symas LMDB, an extremely fast and memory-efficient database that we created for the OpenLDAP Project, is Symas LMDB. It uses memory-mapped files to provide the same read performance as an in-memory database but retains the persistence of standard disk databases. LMDB is small at 32KB in object code. It's still the right 32KB. LMDB is both compact and efficient. That's why LMDB is so powerful. Symas provides fixed-price commercial support for those who use LMDB in their applications. Development takes place in the OpenLDAP Project's Git repo in mdb.master branch. Symas LMDB has been featured in numerous publications and publications.

It can be thought of as a temporary memory for your applications. memcached allows for you to take memory from areas of your system that have more than you need, and make it available to areas that have less. This is the classic deployment strategy. However, you'll see that it's not only wasteful because the cache size is only a fraction of what your web farm actually has, but also because it takes a lot of effort to maintain consistency across all nodes. You can see that all servers are looking into the exact same virtual memory pool with memcached. You will also notice that as your application demands increase, so does the amount of data that must be accessed. These two aspects of your system should be scaled together in a deployment strategy.

RocksDB uses a log-structured database engine written entirely in C++ for maximum performance. Keys and values can be stored in arbitrarily-sized byte streams. RocksDB is optimized to store flash drives and high speed disk drives in fast, low latency storage. RocksDB makes the most of flash and RAM's high read/write speeds. RocksDB can perform basic operations like opening and closing a table, reading and writing, and more complex operations such as merging or compaction filters. RocksDB can adapt to different workloads. RocksDB can be used to meet a wide range of data needs, including database storage engines like MyRocks and application data caching.

GridDB uses multicast communication in order to create a cluster. To enable multicast communication, set the network. First, verify the host name and IP address. To check the settings for an IP address on the host, run "hostname-i" command. If the IP address of your machine is identical to the below, you don't need to adjust network settings and can skip to the next section. GridDB is a database that manages a group (known as a Row) of data that is composed of multiple values and a key. It can be an in-memory database which arranges all data in the memory. However, it can also use a hybrid composition that uses both a disk (including SSD) and a memory.

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.

High-speed, data-intensive apps that meet all performance requirements can be built. Apache Geode's unique technology combines advanced techniques for data replication and partitioning with distributed processing. Apache Geode offers a database-like consistency model, reliable transactions processing, and a shared nothing architecture to maintain very low latency with high concurrency. Data can be easily partitioned (sharded), or replicated among nodes, allowing for performance scaling as required. Reliable in-memory copies are used to ensure durability. Disk-based persistence is also used to ensure longevity. Super fast write-ahead log (WAL) persistence that uses a shared-nothing architecture optimized for parallel recovery of nodes and entire clusters.

GigaSpaces XAP, an event-driven, distributed development platform, delivers extreme processing for mission-critical applications. XAP provides high availability, resilience and boundless scale under any load. With XAP, the application and the data co-locate in the same memory space, reducing data movement over the network and providing both data and application scalability. XAP Skyline, an in-memory distributed technology for mission-critical applications running in cloud-native environments, unites data and business logic within the Kubernetes cluster. With XAP Skyline, developers can ensure that data-driven applications achieve the highest levels of performance and serve hundreds of thousands of concurrent users while delivering sub-second response times. XAP Skyline delivers the low latency, scalability and resilience that are vital for businesses running time-sensitive apps in distributed Kubernetes clusters. XAP Skyline is used in financial services, retail, and other industries where speed and scalability are critical.

Infinispan, an open-source, in-memory data grid, offers flexible deployment options as well as robust capabilities for managing, storing, and processing data. Infinispan is a key/value storage that can store all types of data, including Java objects and plain text. Infinispan uses elastically scalable clusters to distribute your data, ensuring high availability and fault tolerance. Infinispan boosts applications by storing data closer than processing logic. This reduces latency, increases throughput, and speeds up the process. Infinispan is available as a Java library. Simply add Infinispan as a dependency to your Java application and you are ready to store data within the same memory space that the executing code.

A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.

Scale performance easily and cost-effectively as your app's traffic and demands increase. To handle thousands of simultaneous users at once, add a caching layer to your application architecture. All this while enjoying the benefits of a fully managed service. Superior throughput and performance to handle millions upon millions of requests per seconds with sub-millisecond latency. Fully managed service that provides automatic patching, updates and scaling. This allows you to focus on development. RedisBloom, RediSearch and RedisTimeSeries module integrations, supporting data analysis and search, as well as streaming. You get powerful capabilities like clustering, Redis on Flash, built-in replica, Redis on Flash, availability up to 99.99%, and more. Azure Cosmos DB and Azure SQL Database are available to complement your database services. This allows you to scale throughput at a lower price than expanding database instances.

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.

In-memory database with ultra-fast performance, compatible with Redis and Valkey OSS. Scale up to hundreds of millions requests per second, and more than 100 terabytes per cluster. Data is stored with a multi-AZ log, ensuring 99.99% availability. Near-instantaneous data recovery without loss of data. Secure your data using encryption at rest and during transit, private VPC Endpoints, multiple authentication mechanisms including IAM authentication, and multiple authentication methods. Build applications quickly with Redis and Valkey OSS data structures, a rich API and a rich open-source API. Integrate easily with other AWS Services. Deliver personalized real-time experiences with the fastest and most relevant semantic search among popular vector databases in AWS. Valkey and Redis Open Source Software (OSS) provide flexible data structures to simplify application development and reduce time-to market.

Oracle TimesTen In Memory Database (TimesTen), delivers real-time application performance (low response times and high throughput), by changing the assumptions about where data is located at runtime. Database operations are more efficient when data is managed in memory and access algorithms and data structures are optimized accordingly. This results in dramatic improvements in responsiveness and throughput. TimesTen Scaleout is a shared-nothing scale-out architecture that uses existing in-memory technologies. It allows databases to scale transparently across dozens of hosts, reach hundreds terabytes of size, and support hundreds of million transactions per second without the use of manual workload partitioning or database sharding.

LeanXcale is fast and scalable database that combines SQL and NoSQL. It can ingest large batches of data and make it available via SQL or GIS for any purpose, including operational applications, analytics and dashboarding. No matter which stack you use, LeanXcale offers both SQL and NoSQL interfaces. The KiVi storage engine can be used as a relational key/value data store. The data can be accessed via the standard SQL API or a direct ACID key/value interface. This key-value interface allows users data ingestion at extremely high rates and efficiently, while avoiding SQL processing overhead. High-scalable, efficient, and distributed storage engine distributed data along a cluster to improve performance and increase reliability.

SingleStore (formerly MemSQL), is a distributed, highly-scalable SQL Database that can be run anywhere. With familiar relational models, we deliver the best performance for both transactional and analytical workloads. SingleStore is a scalable SQL database which continuously ingests data to perform operational analysis for your business' front lines. ACID transactions allow you to simultaneously process millions of events per second and analyze billions of rows in relational SQL, JSON geospatial, full-text search, and other formats. SingleStore provides the best data ingestion performance and supports batch loading and real-time data pipelines. SingleStore allows you to query live and historical data with ANSI SQL in a lightning fast manner. You can perform ad-hoc analysis using business intelligence tools, run machine-learning algorithms for real time scoring, and geoanalytic queries in a real time.

We provide a geo-distributed, real-time database, stream processing, and compute runtime for event driven applications across up to 175 global edge data centers. Our platform is loved by API and app developers because it solves the most difficult problems of sharing mutable states across hundreds of locations around the world. We also have high consistency and low latency. Macrometa allows you to surgically expand your existing infrastructure to bring your application closer to your users. This allows you to improve performance and user experience, as well as comply with global data governance laws. Macrometa is a streaming, serverless NoSQL database that can be used for stream data processing, pub/sub, and compute engines. You can create stateful data infrastructure, stateful function & containers for long-running workloads, and process data streams real time. We do the ops and orchestration, you write the code.

FoundationDB supports multiple models, so you can store different types of data in one database. All data can be safely stored, distributed and replicated in Key-Value Store. FoundationDB is easy-to-use, grow, and maintain. It uses a distributed architecture that scales out gracefully and handles faults, while acting as a single ACID database. FoundationDB is extremely fast on commodity hardware and can support very heavy loads at a low cost. FoundationDB has been in production for many years and has learned from its mistakes. FoundationDB is supported by an unmatched testing system that is based on a deterministic simulator engine.

You can query billions upon billions of rows with an in-memory columnar database and MPP architecture. Queries are distributed across all cluster nodes, allowing for linear scaling and advanced analytics. The fastest database for data analytics is made up of MPP, columnar storage, and in-memory. You can analyze data anywhere it is stored, whether you are using SaaS, cloud, hybrid, or on-premises deployments. Automatic query tuning reduces overhead and maintenance. You get more power for a fraction of the normal infrastructure costs with seamless integrations and performance efficiency. This social networking company was able to increase its performance by using smart, in-memory query processing. They processed 10B data sets per year. A single data repository and speed-engine to accelerate critical analytics, improving patient outcomes and the bottom line.

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 data platform that makes your tech stack more efficient, faster, and cheaper. It allows your applications and your company to scale seamlessly to meet the ultra low latency SLAs of 5G and IoT. Volt Active Data is designed to complement your existing big data investments such as NoSQL and Hadoop, Kubernetes and Kafka, as well traditional databases or data warehouses. It replaces the many layers that are required to make contextual decisions about streaming data with one unified layer that can handle everything from ingest to action in less then 10 milliseconds. There is a lot of data in the world. It's all stored, forgotten, then deleted. "Active Data" refers to data that must be acted upon immediately in order to gain business value. You have many options for data storage, both traditional and non-SQL. If you are able to act quickly enough to 'influence' the moment, there is data that you can also make money with.

Modernize and accelerate transaction-based applications both on-premise and in the Cloud. This SQL database server is high-performance and uses a relational management system to meet the rising demand for performance, reliability, efficiency, and productivity in every industry.

upscaledb, a key-value database that optimizes storage and algorithms for specific data types, is fast. Optional compression can further reduce file size and I/O. It can also keep more data in memory to improve performance and scalability for full-table scans to query the data and analyze it. upscaledb is able to create all functions of a typical SQL Database, customized to your application's needs, and can be directly linked to your program. Its database cursors and fast analytical functions make it an ideal choice to process data when a SQL database is slow enough. Applications that use upscaledb can be deployed on millions of desktops as well as cloud instances and embedded devices. This benchmark runs a full table scan of 50 million records and retrieves maximum. These records are configured with uint32 values.

InfinityDB Embedded, a Java NoSQL Java database, is a hierarchical sorted value store. It is flexible, high-performance, multicore, and maintenance-free. InfinityDB Client/Server and InfinityDB Encrypted databases are now also available. According to our customers and provided performance tests, InfinityDB offers the best performance. Multi-core overlapping operations scale almost linearly with thread count. Threads use fair scheduling with very low interthread interference. Random I/O scales logarithmically with file size. Caches grow only as they are used and are packed efficiently. Database open is instantaneous even after abrupt exit.

Terracotta DB, a distributed in-memory database management solution, is a comprehensive and flexible data management tool that caters to both operational storage and caching. It also enables transactional processing and analysis. Ultra-Fast Ram and Big Data = Business Power. BigMemory gives you: Real-time access and control over terabytes in-memory data. High throughput and predictable latency. Support for Java®, Microsoft®,.NET/C# and C++ applications. 99.999 percent uptime. Linear scalability. Data consistency guarantees across multiple servers. Optimized data storage across SSD and RAM. SQL support for querying in memory data. Maximal hardware utilization results in lower infrastructure costs. High-performance persistent storage for durability and fast restart. Advanced monitoring, management, and control. Data storage that is ultra-fast and in-memory, which automatically moves data to the right place. Support for data replication across multiple data centers for disaster recovery. Real-time management of fast-moving data

Speedb is RocksDB-compatible, enhancing stability, efficiency and overall performance. Join the Hive - Speedb's community of open-source users - to share knowledge, improve and interact with each other. Speedb is an alternative to LevelDB and RocksDB for users who want to take their applications to the next stage. Consider using Speedb when using event streaming platforms such as Kafka or Spark. Many applications are experiencing performance issues due to the increase in metadata found in modern data sets. Speedb allows you to keep costs down and ensure that your applications run smoothly, even when under heavy load. Speedb can help you decide whether to upgrade your platform or to deploy a new key value store. You'll feel immediate relief by integrating Speedb’s advanced key-value engine into your projects.

ApsaraDB is an automated and scalable tool that developers can use to manage data storage shared between multiple applications, processes, or servers. ApsaraDB Redis is compatible with Redis protocol and offers exceptional read-write capabilities. It also ensures data persistence through the use of memory and hard disk storage. ApsaraDB Redis offers data read-write capabilities at high speeds by retrieving data in-memory caches. It also ensures data persistence using both memory storage and hard disk storage mode. ApsaraDB Redis supports advanced data structures like session, leaderboard, and tracking that are not possible with ordinary databases. ApsaraDB Redis also offers an enhanced version called "Tair". Since 2009, Tair has been officially handling data caching scenarios for Alibaba Group and has shown outstanding performance in scenarios like Double 11 Shopping Festival.

Berkeley DB is a set of embedded key-value databases libraries that provide high-performance data management services for applications.

Couchbase, unlike other NoSQL database, provides a multicloud to edge enterprise-class database that offers robust capabilities for business-critical apps on a highly available and scalable platform. Couchbase is a distributed cloud native database that runs on any cloud. It can be managed by the customer or fully managed. Couchbase is built using open standards and combines the best of NoSQL and SQL with the power and familiarity that mainframes and relational databases provide. Couchbase Server is an open-source, multipurpose distributed database. It combines the best of relational databases, such as SQL, ACID transactions, and JSON, with a foundation which is fast and scalable. It is used in many industries for things such as user profiles, dynamic catalogs, GenAI applications, vector search, caching at high speed, and more.

Kyoto Tycoon, a lightweight network server built on top of the Kyoto Cabinet key value database, is designed for high-performance concurrency and concurrency. It includes. It comes with a fully-featured protocol that is based on HTTP, as well as a binary protocol that provides even better performance. There are many client libraries that implement them in multiple languages. We have one for Python. You can configure it with simultaneous support for memcached, but there are limitations on the data update commands. This is useful if you wish to replace memcached in larger-than-memory/persistency scenarios. You will find updated versions of the most recent upstream releases. These are intended to be used together in real-world production environments. These changes include bug fixes, minor improvements, and packaging for a few Linux distributions.

Voldemort does not have a relational database. It doesn't attempt to satisfy arbitrary relationships while also satisfying ACID properties. It is not an object database that attempts transparently to map object reference graphs. Nor does it introduce a new abstraction such as document-orientation. It is essentially a large, distributed, persistent, fault-tolerant, hash table. This will allow applications to use O/R maps like active-record and hibernate, which will provide horizontal scaling and greater availability, but with a great loss in convenience. A system may consist of many functionally partitioned APIs or services that can manage storage resources across multiple data centres using storage systems that may be themselves horizontally partitioned. This is useful for large applications that are subject to internet-type scalability. Because all data is not in one database, it is impossible to make arbitrary in-database connections for applications in this space.

IBM Cloud®, purpose-built databases, deliver high availability and enhanced security as well as scalable performance. You can choose from a range of database engines, including relational and NoSQL databases, such as graph, key-value and in-memory databases, and document, key-value and graph databases. You can build distributed, modern applications that are highly scalable and distributed thanks to the support for multiple data models. There is no one size fits all. You can speed up development and meet your business needs by choosing the right database for the job. IBM Cloud DBaaS solutions include hosting, auto provisioning, and 24x7 management with automated backup and restore, version updates, security, and more.

The Open, Multi-Cloud Stack to Modern Data Apps. Built on Apache Cassandra™, an open-source Apache Cassandra™. Global scale and 100% uptime without vendor lock in You can deploy on multi-clouds, open-source, on-prem and Kubernetes. For a lower TCO, use elastic and pay-as you-go. Stargate APIs allow you to build faster with NoSQL, reactive, JSON and REST. Avoid the complexity of multiple OSS projects or APIs that don’t scale. It is ideal for commerce, mobile and AI/ML. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Richly interactive apps that are viral-ready and elastic using REST, GraphQL and JSON. Pay-as you-go Apache Cassandra DBaaS which scales easily and affordably

Tablestore allows seamless expansion of data size, access concurrency, and data sharding technologies. It provides storage and real-time access of massive structured data. Three copies of data with high consistency and full host, high availability, data high reliability, and service high availability. Provides full/incremental data tunnels that seamlessly connect with other products for big-data analysis and real time stream computing. Distributed architecture, single-table auto scaling, support for 10-PB-level data, and 10-million-level access concurrency. Multi-level and multi-level security protection, as well as resource access management, are available to ensure data security. This service's low latency, high concurrency and elastic resources, as well as the Pay-As You-Go billing method, allow your risk control system, which allows you to control transaction risks.

H2, the Java SQL database, is your welcome. An embedded mode allows an application to open a database within the same JVM by using JDBC. This connection mode is the fastest and most convenient. However, a database can only be opened in one virtual machine (and a class loader) at a time. Both in-memory and persistent databases are supported, as in all modes. There is no limit to the number of databases that can be opened simultaneously or the number of connections. Mixed mode is a combination between the server and embedded modes. The first application to connect to a database uses embedded mode. However, it also starts a server so other applications (running in different processes and virtual machines) can simultaneously access the same data. The local connections are just as fast as if the data were used in embedded mode. Remote connections are slightly slower.

With our ACID in-memory technologies and application servers, you can build enterprise software lightning fast. You can build enterprise software without using new syntax or custom tools. Starcounter applications can improve performance by up to 1000 times without adding complexity. Applications are written using regular C#, LINQ and SQL. Even the ACID transactions can be written in C# code. Full Visual Studio support, including IntelliSense and debugger. All the features you love, without the headache. Write regular C# syntax using the MVVM pattern for ACID in-memory and thin client UI to achieve extreme performance. Starcounter technology is a business asset from the first day. We use technology that is already developed and in production to process millions of business transactions. Starcounter combines ACID's in-memory databases and application servers into a single platform that is unmatched for performance, simplicity and price.

Access accurate and timely data from your organization. It's synchronized and delivered to the right people in real-time. Excel allows you to access live data from your organization's sources. These data sources have been connected through PowerOLAP’s in-memory system. You will see a significant reduction in reporting time and effort and a dramatic increase in staff productivity. You can achieve faster budgeting cycles, dynamic reporting building, and advanced analytics via "multidimensional" views of the company's structure and performance. Ability to combine disparate systems to aggregate data from all major sources. Ability to work together across the team on data and analytics updates with a simple refresh. Data-informed decisions can be made with power and business intelligence analytics.