Alternatives to Terracotta

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.

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.

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.

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.

Redis and Memcached are now more reliable, available, and scalable. Memorystore automates complex tasks such as patching, monitoring, failover, and high availability for open-source Redis and Memcached so you can spend more of your time programming. Start small and scale up your instance. Memorystore for Memcached supports clusters up to 5 TB, supporting millions of QPS with very low latency. Redis Memorystore instances are replicated across two zones, providing a 99.9% availability guarantee. Instances are monitored constantly and with automatic failover--applications experience minimal disruption. You can choose from two of the most popular open-source caching engines to build your application. Memorystore is protocol compatible and supports Redis and Memcached. Choose the engine that best suits your needs and budget.

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.

High performance and resource efficiency with embedded persistent and in-memory key value storage engine. It is designed to manage bytes on-disk efficiently and in-memory efficiently by recognising reoccurring pattern in serialised bytes. The core implementation can be restricted to any data model (SQL or NoSQL) or storage type (Disk, RAM). Although the core has many configurations that can easily be tuned for specific use-cases we plan to implement automatic runtime tuning once we are able collect and analyse runtime machine statistics and read-write patterns. You can manage data by creating familiar data structures such as Map, Set, Queue and SetMap. These data structures can be easily converted to native Java or Scala collections. Conditional updates/data modification can be done with any Java, Scala, or any native JVM Code - No query language.

VMware Tanzu GemFire, a distributed key-value store with in-memory key-value storage, performs read-and-write operations at lightning fast speeds. It has high availability parallel message queues, continuous availability, an event-driven architecture that can scale dynamically with no downtime, and an event-driven architecture. Tanzu GemFire scales linearly as your data requirements increase to support high performance, real-time apps. Traditional databases are often too fragile or unreliable to be used with microservices. Every modern distributed architecture requires a cache. Applications can use Tanzu GemFire to get fast responses to data access requests and always receive new data. Applications can subscribe to real time events to respond to changes instantly. Continuous queries from Tanzu GemFire notify your application whenever new data becomes available. This reduces overhead on your SQL database.

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.

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.

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.

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.

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.

Lucid is still in development. However, we want to create a fast, secure, and distributed key-value storage accessible through an HTTP API. We also want to offer persistence, encryption WebSocket streaming and replication, and many other features. Private keys storage, IoT (to collect statistics data and save it), Distributed cache, service discovery distributed configuration, blob storage, replication, etc.

The Apache Cassandra database provides high availability and scalability without compromising performance. It is the ideal platform for mission-critical data because it offers linear scalability and demonstrated fault-tolerance with commodity hardware and cloud infrastructure. Cassandra's ability to replicate across multiple datacenters is first-in-class. This provides lower latency for your users, and the peace-of-mind that you can withstand regional outages.

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.

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.

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.

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.

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.

OrigoDB allows you to create high-quality, mission-critical systems in a fraction of time and cost. This isn't marketing gibberish! For a detailed description of our features, please read on. Contact us if you have any questions. You can also download the software and start it right away! In-memory operations are a lot faster than disk operations. One OrigoDB engine can execute millions upon millions of read transactions per minute and thousands upon thousands of write transactions every second. Asynchronous command journaling to local SSDs is also available. This is why OrigoDB was built. A single object-oriented domain model is much simpler than a full stack that includes a relational model, object/relational map, data access code and views, as well as stored procedures. This is a lot of waste that can easily be eliminated. The OrigoDB engine runs 100% ACID right out of the box. Each command executes one at a moment, transitioning the in memory model from one consistent state into another.

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.

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.

KeyDB is fully compatible with Redis modules API and protocol. You can easily drop in KeyDB to maintain compatibility with existing clients, scripts, and configurations. Multi-Master mode distributes a single replicated dataset across multiple nodes to support both read and writing operations. Nodes can be replicated across regions to provide submillisecond latency to local clients. Cluster mode allows unlimited read/write scaling by splitting the data across multiple shards. This allows unlimited scaling and supports high availability via replica nodes. KeyDB provides new community-driven commands that allow you to do more with data. ModJS module allows you to create your own JavaScript commands and functionality. ModJS allows you to write Javascript functions that can be called directly from KeyBD. The left example shows a Javascript function that would be loaded along with the module. It can then be called from your client.

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.

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.

Azure Cosmos DB, a fully managed NoSQL databank service, is designed for modern app development. It offers guaranteed single-digit millisecond response time and 99.999 percent availability. This service is backed by SLAs and instant scalability. Open source APIs for MongoDB or Cassandra are also available. With turnkey multi-master global distribution, you can enjoy fast writes and readings from anywhere in the world.

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.

Smart DIH is a data management platform that quickly serves applications with accurate, fresh and complete data, delivering high performance, ultra-low latency, and an always-on digital experience. Smart DIH decouples APIs from SoRs, replicating critical data, and making it available using event-driven architecture. Smart DIH enables drastically shorter development cycles of new digital services, and rapidly scales to serve millions of concurrent users – no matter which IT infrastructure or cloud topologies it relies on. XAP Skyline is a distributed in-memory development platform that delivers transactional consistency, combined with extreme event-based processing and microsecond latency. The platform fuels core business solutions that rely on instantaneous data, including online trading, real-time risk management and data processing for AI and large language models.

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.

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.

We are glad you are here! BergDB is a Java/.NET database that is simple and efficient. It was designed for developers who want to concentrate on their specific task and not waste time worrying about database issues. BergDB features include simple key-value storage and ACID transactions, historical queries, efficient concurrency controls, secondary indexes with fast append-only storage, replication, transparent object Serialization, and more. BergDB is an embedded, NoSQL, open-source, schemaless, document-oriented, NoSQL, embedded database. BergDB was built from the ground up to execute transactions extremely quickly. There are no compromises. All writes to the database are done in ACID transactions with the highest level of consistency (in SQL-speak, serializable isolation). Historical queries are useful when there are previous data states that are relevant. They also serve as a quick way to manage concurrency. BergDB does not lock anything when a read operation is performed.

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.

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.

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.

ArcadeDB allows you to manage complex models without any compromises. Polyglot Persistence is gone. There is no need to have multiple databases. ArcadeDB Multi-Model databases can store graphs and documents, key values, time series, and key values. Each model is native to the database engine so you don't need to worry about translations slowing down your computer. ArcadeDB's engine was developed with Alien Technology. It can crunch millions upon millions of records per second. ArcadeDB's traversing speed does not depend on the size of the database. It doesn't matter if your database contains a few records or a billion. ArcadeDB can be used as an embedded database on a single server. It can scale up by using Kubernetes to connect multiple servers. It is flexible enough to run on any platform that has a small footprint. Your data is protected. Our unbreakable fully transactional engine ensures durability for mission-critical production database databases. ArcadeDB uses the Raft Consensus Algorithm in order to maintain consistency across multiple servers.

LevelDB is a fast key/value storage library that Google has created. It provides an ordered mapping of string keys to string value. Keys and values can be stored in arbitrary byte arrays. Data is stored in key order. To override the order of the data, callers can provide a custom comparator function. Multiple changes can be made to an atomic batch. To maintain a consistent view of data, users can create a temporary snapshot. Data can be used for forward and backward iteration. Snappy is used to automatically compress data. External activity (file system operations, etc.) The information is transmitted via a virtual interface to allow users to customize the operating system interactions. A database with over a million entries is used. Each entry is assigned a 16-byte key and a 100-byte value. The benchmark reduces the size of the values to approximately half of their original size. The benchmark lists the performance of sequential reading in the forward and reverse directions, as well as the performance of random lookups.

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.

Ehcache, an open-source, standards-based cache, boosts performance, offloads your databases, and simplifies scaling. It is the most popular Java-based cache. It is robust, reliable, fully-featured and integrates well with other libraries and frameworks. Ehcache scales from in-process caching, all the way to mixed in-process/out-of-process deployments with terabyte-sized caches. Terracotta actively develops and maintains Ehcache under an Apache 2.0 license. We welcome contributors to our community.

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.

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.

Azure Table storage can store petabytes semi-structured data at low costs and keeps costs down. Table storage is able to scale up, unlike many cloud-based or on-premise data stores. Also, availability is not a concern. With geo-redundant storage, data can be replicated three times within one region and three times in another region hundreds of miles away. Flexible data such as web app user data, address books, device data and other metadata can be stored in table storage. You can also use table storage to build cloud applications without having to lock down the data model to specific schemas. Different rows can have different structures in the same table, so you can easily change your application and table schema without having to take it offline. Table storage embraces a strong consistency model.

It is quick and easy to provision an instance with openredis. We do all the heavy lifting. You can choose the plan that suits you best and then upgrade to a larger plan at any time. A new instance will be provisioned and synchronized with your existing one when you upgrade. To ensure minimal downtime, your old instance will continue to run for one hour. We temporarily provide additional replicas in different regions for situations where severe weather or other natural disasters are likely to occur. Our mission is to offer the best hosting service available. All plans include a backup copy. Your backup replica is automatically promoted to the role of master and redundancy restored within minutes.

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

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.

Ledisdb, a high-performance NoSQL server and database library written in Go, is Ledisdb. It is similar to Redis, but stores data on disk. It supports many data structures, including kv and list, hash, set, zset, and zset. LedisDB now supports multiple databases as backends.

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.

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.

Red Hat®, Data Grid is a distributed, in-memory NoSQL datastore. Your applications can access, process and analyze data at high speed to provide a superior user experience. High performance, elastic scaling, always available You can quickly access your data using low latency data processing with memory (RAM), and distributed parallel execution. Linear scaling is possible with data partitioning and distributed across cluster nodes. Data replication across cluster nodes ensures high availability. Cross-datacenter geo-replication, clustering and fault tolerance allow you to be resilient and recover from disasters. A flexible, functionally rich NoSQL database store allows you to develop more efficiently and increase productivity. You can achieve complete data security through encryption and role-based access. Data Grid 7.3.10 offers a security enhancement to fix a CVE. Data Grid 7.3.10 must be upgraded as soon as possible.

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.