Alternatives to ArcadeDB

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.

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.

Natively store data for graphs, documents and search needs. One query language allows for feature-rich access. You can map data directly to the database and access it using the best patterns for the job: traversals, joins search, ranking geospatial, aggregateions - you name them. Polyglot persistence without the cost. You can easily design, scale, and adapt your architectures to meet changing needs with less effort. Combine the flexibility and power of JSON with graph technology to extract next-generation features even from large datasets.

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

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.

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.

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.

Fauna is a data API that supports rich clients with serverless backends. It provides a web-native interface that supports GraphQL, custom business logic, frictionless integration to the serverless ecosystem, and a multi-cloud architecture that you can trust and grow with.

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.

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.

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.

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.

OrientDB is the fastest graph database in the world. Period. A benchmark study by IBM and Tokyo Institute of Technology found that OrientDB is 10x more efficient than Neo4j for graph operations. This applies to all workloads. OrientDB can help you gain competitive advantage and increase innovation through new revenue streams.

BangDB integrates AI, streaming and graph analytics within its DB to allow users to deal complex data of all types, such as text, images and objects. Real-time data processing and analysis Many types of data are required to be ingested and processed simultaneously for today's use cases. BangDB supports almost all the data formats that are useful to users to solve their problem quickly. The rise of real-time data allows for real-time streaming and predictive analytics to optimize business operations.

VictoriaMetrics is a cost-effective, scalable monitoring solution that can also be used as a time series database. It can also be used to store Prometheus' long-term data. VictoriaMetrics is a single executable that does not have any external dependencies. All configuration is done using explicit command-line flags and reasonable defaults. It provides global query view. Multiple Prometheus instances, or other data sources, may insert data into VictoriaMetrics. Later this data may be queried via a single query. It can handle high cardinality and high churn rates issues by using a series limiter.

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.

Real-time analytics on raw data. Live ingest from S3, DynamoDB, DynamoDB and more. Raw data can be accessed as SQL tables. In minutes, you can create amazing data-driven apps and live dashboards. Rockset is a serverless analytics and search engine that powers real-time applications and live dashboards. You can directly work with raw data such as JSON, XML and CSV. Rockset can import data from real-time streams and data lakes, data warehouses, and databases. You can import real-time data without the need to build pipelines. Rockset syncs all new data as it arrives in your data sources, without the need to create a fixed schema. You can use familiar SQL, including filters, joins, and aggregations. Rockset automatically indexes every field in your data, making it lightning fast. Fast queries are used to power your apps, microservices and live dashboards. Scale without worrying too much about servers, shards or pagers.

QuasarDB is Quasar's brain. It is a high-performance distributed, column-oriented, timeseries database management software system that delivers real-time data for petascale use cases. You can save up to 20X on your disk usage Quasardb compression and ingestion are unmatched. Feature extraction can be performed up to 10,000 times faster. QuasarDB is able to extract features from raw data in real-time thanks to a combination of a builtin map/reduce engine, an aggregate engine that leverages SIMD from modern processors, and stochastic indices that consume virtually no disk space.

Realtime, realtime, offline-first, graph database engine. You can store, load, and share the data you need in your app without worrying too much about servers, network calls, database access, or tracking offline changes. GUN is a simple, fast, and easy-to-use data sync and storage tool that runs wherever JavaScript does. GUN's goal is to let you concentrate on the data that must be stored, loaded, shared, and shared in your app. It doesn't need to worry about servers, database calls, tracking offline changes, concurrency conflicts, or monitoring network calls. This allows you to quickly build cool apps. GUN gives you the most powerful tools of the internet, decentralization and privacy. This allows you to reclaim the web and make the internet truly open and free. GUN is a database engine which runs on all JavaScript devices, including mobile devices and servers. It allows you to create the data system that you want.

Hawkular Metrics, a scalable, asynchronous multi-tenant, long term metrics storage engine, uses Cassandra to store the data and REST to interface. This section will provide an overview of Hawkular Metrics' key features. These and other features will be discussed in detail in the following sections. Hawkular Metrics is all based on scalability. A single instance can be backed by one Cassandra node. To handle increasing loads, Cassandra can be scaled to multiple nodes. Hawkular Metrics uses a stateless architecture which makes it easy for you to scale out. This diagram shows the many deployment options that Hawkular Metrics' scalable architecture allows. The top left picture shows the simplest deployment using a single Cassandra and one Hawkular Metrics node. The bottom right image shows that you can run more Hawkular Metrics Nodes than Cassandra.

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).

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.

Powerful graph analytics made easy. Aster SQL-GR™, a native graph processing engine for graph analysis, makes it easy to solve complex business issues such as social network/influencer analysis. It also helps with fraud detection, supply chain management and network analysis. These problems are more impactful than simple graph navigation analysis. SQL-GR is based upon the Bulk Synchronous Process (BSP) model. It uses massively iterative and parallel processing to solve complex graph problems. SQL-GR is extremely scalable because it is based upon the BSP iterative process model. It also takes advantage of Teradata Aster’s massively scalable parallel processor (MPP) architecture to distribute graph processing across multiple servers/nodes. SQL-GR does not have memory limits and is not limited to one server/node. SQL-GR can easily perform complex graph analysis on large data sets with unmatched speed and power.

Companies who choose a DIY approach to their graph database can expect a wait of 2 to 3 months before production-ready implementation. Your production-ready database will be available within minutes with Graph Story's managed services. Learn more about graph use cases and compare self-hosting to managed services. We can deploy your servers where they are already located: AWS, Azure or Google Compute Engine in any region. Do you need VPC peering? Let us know. We are flexible like that. How do you build a proof-of-concept? In just a few clicks, you can fire up one enterprise graph instance. Do you need to move to a cluster that is high-availability and production-ready on-demand? We've got you covered! We created graph db management tools to make it easy for you! You can see CPU, Memory, and Disk utilization in one glance. Access configs, logs and backups of your database.

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.

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.

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.

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.

IBM Informix®, a fast and flexible database that can seamlessly integrate SQL, NoSQL/JSON and time series data, is available. Informix's versatility and ease-of-use make it a popular choice for a wide variety of environments, including enterprise data warehouses and individual application development. Informix is also well-suited for embedded data management solutions due to its small footprint and self-managing capabilities.

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

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

Neo4j's graph platform is designed to help you leverage data and data relationships. Developers can create intelligent applications that use Neo4j to traverse today's interconnected, large datasets in real-time. Neo4j's graph database is powered by a native graph storage engine and processing engine. It provides unique, actionable insights through an intuitive, flexible, and secure database.

Telegraf is an open-source server agent that helps you collect metrics from your sensors, stacks, and systems. Telegraf is a plugin-driven agent that collects and sends metrics and events from systems, databases, and IoT sensors. Telegraf is written in Go. It compiles to a single binary and has no external dependencies. It also requires very little memory. Telegraf can gather metrics from a wide variety of inputs and then write them into a wide range of outputs. It can be easily extended by being plugin-driven for both the collection and output data. It is written in Go and can be run on any system without external dependencies. It is easy to collect metrics from your endpoints with the 300+ plugins that have been created by data experts in the community.

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.

Understanding the relationships between data is key to unlocking the true value of continuously changing business data. A graph database, unlike other databases, puts relationships first. It uses Linear Algebra and graph theory to explore and show how complex data webs, sources, and points relate. TIBCO®, Graph Database allows users to store, transform, and interpret complex dynamic data into meaningful insights. Users can quickly build data and computational models that create dynamic relationships between organizational silos. These knowledge graphs provide value by connecting the vast array of data in your organization and revealing relationships that allow you to optimize assets and processes. OLTP and OLAP features combined in a single enterprise-grade data base. Optimistic ACID-level transaction properties with native storage access.

OneTick Database is embraced by top banks, brokerages and data vendors as well as exchanges, markets, hedge funds, market makers, mutual funds and other financial institutions. OneTick is the best enterprise-wide solution for tick data collection, streaming analytics and data management. OneTick is loved by top hedge funds, mutual funds and banks as well as brokers, banks, brokerages and market makers. OneTick's proprietary time-series database is a unified platform for multi-asset classes. It includes a fully integrated streaming analytics engine, built-in business logic, and eliminates the need to use multiple disparate systems. The system has the lowest total cost-of-ownership.

QuestDB is a relational database that uses column-oriented databases. It can be used for event and time series data. It uses SQL with extensions to time series to aid in real-time analytics. These pages provide information about core concepts of QuestDB. They include setup steps, usage guides, as well as reference documentation for syntax, APIs, and configuration. This section explains the architecture of QuestDB and how it stores and queries data. It also introduces new capabilities and features that are unique to the system. The core feature of QuestDB is the designated timestamp. It enables partitioning and time-oriented language capabilities. The symbol type makes it easy to store and retrieve repetitive strings. QuestDB's storage model describes how it stores records and partitions within tables. Indexes can be used to provide faster access to specific columns. Partitions can be used to provide significant performance improvements in calculations and queries. SQL extensions enable time series analysis that is efficient and concise with a concise syntax.

VelocityDB is a database platform unlike any other. It stores data faster and more efficiently than other databases engines at a fraction the cost. It stores.NET objects in their original form without any mapping to tables, JSON, or XML. VelocityGraph, an open-source property graph database, can be used in conjunction the VelocityDB object data base. Object and graph database engine VelocityDB, a C#.NET NoSQL object database, can be extended to VelocityGraph. World's fastest most scalable & flexible database. A bug reported with a reproducible case is usually fixed within one week. This database system offers the greatest benefit, flexibility. You can fine-tune your application like no other database system. You can choose the most suitable data structure for your application with VelocityDB. You can choose where and how the data is indexed and accessed.

Graph databases are part of Oracle's converged data platform. They eliminate the need for a separate database to store and move data. Analysts and developers are able to detect fraud in banking, locate connections and link data, and improve traceability and smart manufacturing traceability. All this while gaining enterprise-grade security and ease of data ingestion and strong support for data workloads. Oracle Autonomous Database also includes Graph Studio. It offers one-click provisioning, integrated tools, and security. Graph Studio automates graph data administration and simplifies analysis, modeling, and visualization throughout the graph analytics lifecycle. Oracle supports both RDF knowledge graphs and property graphs. It also simplifies the process for modeling relational data as graph structures. Interactive graph queries can be run directly on graph data, or in high-performance, in-memory graph servers.

Titan is a graph database that can store and query graphs with hundreds of billions of edges and vertices distributed across a multi-machine cluster. Titan is a transactional database which can handle thousands of concurrent users performing complex graph traversals in real-time. For a growing user and data base, you can use linear and elastic scaling. Data replication and data distribution for performance and fault tolerance. Hot backups and high availability for multi-datacenters Support for ACID, eventual consistency and other storage backends. Support for Apache Cassandra and Apache HBase storage backends, as well as Oracle BerkeleyDB. Integration with big data platforms such as Apache Spark, Apache Giraph, and Apache Hadoop allows for global graph data analytics, reporting and ETL. Native integration with TinkerPop graph stack to support Gremlin's graph query language, Gremlin's graph server, and Gremlin apps.

The database is the foundation of intelligent systems. Grakn is an intelligent database, a knowledge graph. A data schema that is intuitive and expressive. It can be used to create rich knowledge models by defining hierarchies, hyperentities, hyperrelations, rules, and constructs. Intelligent language that infers data types, relationships and attributes, as well as complex patterns, at runtime and with persistent and distributed data. Accessible through simple queries, out-of-the box distributed analytics (Pregel & MapReduce), are available through the language. Strong abstraction allows for simpler expressions of complex constructs while the system determines the best query execution. Grakn KGMS & Workbase allow you to scale your enterprise Knowledge Graph. A distributed database that can scale across a network of computers by partitioning and replicating.

GraphBase (Graph Database Management System, Graph DBMS), is a Graph Database Management System designed to simplify the creation and maintenance complex data graphs. The Relational Database Management System is challenged by complex and interconnected structures. A graph database offers better modeling utility, performance, and scalability. The triplestores and property diagrams are the most recent graph database products. They have been around for almost two decades. Although they are powerful tools with many uses, they are not well-suited for managing complex data structures. GraphBase was created to make complex data management easier. It could be Knowledge. This was possible by redefining the way graph data should be managed. GraphBase makes the graph a first-class citizen. A graph equivalent to the "rows & tables" paradigm makes it so easy to use a Relational Database.

KgBase (or Knowledge Graph Base) is a robust, collaborative database that allows for versioning, analytics, visualizations, and visualizations. KgBase allows anyone to create knowledge graphs and gain insights about their data. You can import your CSVs or spreadsheets or use our API to collaborate on data. KgBase allows you to create no-code knowledge graphs. Our easy-to-use UI lets users navigate the graph and display the results in tables and charts. You can play with your graph data. You can build your query and watch the results change in real-time. It's similar to writing query code in Cypher and Gremlin, but much easier. It's also fast. You can view your graph as a table. This allows you to view all results, regardless of their size. KgBase is great for large graphs (millions) as well as simple projects. You can either use the cloud or self-hosted and have extensive database support. You can introduce graphs to your organization by seeding graphs from a template. Any query results can be easily converted into a chart visualization.

HyperGraphDB is an open-source, general-purpose data storage system that uses a powerful knowledge management approach called directed hypergraphs. Although it is a persistent memory model, it can also serve as an embedded object-oriented data base for Java projects of any size. Or a graph database or a (non SQLL) relational database. HyperGraphDB is a storage system that uses generalized hypergraphs for its underlying data model. A tuple is a collection of 0 or more tuples. Each atom is a tuple of this type. The data model can be viewed as either relational, where higher-order, non-ary relationships are permitted, or graph-oriented where edges point to an arbitrary set nodes. Each atom is assigned a strongly-typed, arbitrary value. The hypergraph that manages these values is embedded in the type system and can be customized from the ground up.

The graph database is designed for graphs up to super large scale with very low latency. We continue to work with the community to promote, popularize, and prepare the graph database. Nebula Graph allows only authenticated access through role-based access control. Nebula Graph can support multiple storage engines and the query language is extensible to support new algorithms. Nebula Graph offers low latency read/write while maintaining high throughput to simplify complex data sets. Nebula Graph's distributed, shared-nothing architecture allows for linear scaling. Nebula Graph's SQL query language is similar to SQL and can be used to address complex business requirements. Nebula Graph's horizontal scalability, snapshot feature and high availability guarantee that there will be no downtime. Nebula Graph has been used in production environments by large Internet companies such as JD, Meituan and Xiaohongshu.

Amazon Neptune is a fully managed graph database service that allows you to quickly and reliably build applications that can work with highly connected data sets. Amazon Neptune's core is a purpose-built graph database engine that can store billions of relationships and query the graph with only milliseconds latency. Amazon Neptune supports the popular graph models Property Graph, W3C's RDF, as well as their respective query languages Apache TinkerPop Gremlin, SPARQL. This allows you to quickly build queries that efficiently navigate large datasets. Neptune supports graph use cases like recommendation engines, fraud detection and knowledge graphs. It also powers network security and drug discovery.

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.

Data engineers and scientists can be 95% better at their jobs with ready access to the most flexible semantic layer, explainable AI and reusable data modelling. They can create and expand semantic models, understand data interrelationships, and run federated query to speed up time to insight. Stardog's graph data virtualization and high performance graph database are the best available -- at a price that is up to 57x less than competitors -- to connect any data source, warehouse, or enterprise data lakehouse without copying or moving data. Scale users and use cases at a lower infrastructure cost. Stardog's intelligent inference engine applies expert knowledge dynamically at query times to uncover hidden patterns and unexpected insights in relationships that lead to better data-informed business decisions and outcomes.

You can create high-quality, mission-critical applications in a fraction of the time and costs. Memstate is new. It is extremely inefficient to move data between RAM and disk. Additionally, it requires complex software that can be eliminated. Memstate allows you to manage and structure your data in-memory. It also provides transparent persistence, concurrency control, and transactions with strong ACID warranties. This is too technical. Make your applications faster and your developers more productive. Memstate can be used in many ways, but it is designed to handle complex OLTP workloads within an enterprise application. In-memory operations are a factor of ten times faster than disk operations. A single Memstate engine can execute millions upon millions of read transactions, and tens to thousands upon thousands of write transactions per second. All this at submillisecond latency.

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.