Alternatives to Memgraph

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.

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.

StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

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.

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.

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

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.

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.

JanusGraph is an optimized graph database that can store and query graphs with hundreds of billions of edges and vertices distributed across a multi-machine cluster. JanusGraph is a project of The Linux Foundation and includes participants from Expero and Google, GRAKN.AI., Hortonworks. IBM, and Amazon. Linear and elastic scaling for growing data and users. Data replication and data distribution for performance and fault tolerance. Hot backups and high availability for multi-datacenters All functionality is completely free. There is no need to purchase commercial licenses. JanusGraph is completely open source under the Apache 2 License. JanusGraph is an open source transactional database that can handle thousands of concurrent users performing complex graph traversals in real-time. ACID and eventual consistency support. JanusGraph offers online transactional processing (OLTP) and global graph analytics (OLAP), through its Apache Spark integration.

Aiven manages your open-source data infrastructure in the cloud so that you don't have. Developers can do what is best for them: create applications. We do what we love: manage cloud data infrastructure. All solutions are open-source. You can also freely transfer data between clouds and create multi-cloud environments. You will know exactly what you will be paying and why. We combine storage, networking, and basic support costs. We will keep your Aiven software up and running. We will be there to help you if there is ever an issue. In 10 minutes, you can deploy a service on Aiven. 1. Register now - No credit card information required 2. Select your open-source service and choose the region and cloud to deploy to it 3. Select your plan and get $300 in credit 4. Click "Create service" to configure your data sources

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.

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.

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.

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.

*GraphDB allows the creation of large knowledge graphs by linking diverse data and indexing it for semantic search. * GraphDB is a robust and efficient graph database that supports RDF and SPARQL. The GraphDB database supports a highly accessible replication cluster. This has been demonstrated in a variety of enterprise use cases that required resilience for data loading and query answering. Visit the GraphDB product page for a quick overview and a link to download the latest releases. GraphDB uses RDF4J to store and query data. It also supports a wide range of query languages (e.g. SPARQL and SeRQL), and RDF syntaxes such as RDF/XML and Turtle.

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.

Graphlytic is a web-based BI platform that allows knowledge graph visualization and analysis. Interactively explore the graph and look for patterns using the Cypher query language or query templates for non-technical users. Users can also use filters to find answers to any graph question. The graph visualization provides deep insights into industries such as scientific research and anti-fraud investigation. Even users with little knowledge of graph theory can quickly explore the data. Cytoscape.js allows graph rendering. It can render tens to thousands of nodes and hundreds upon thousands of relationships. The application is available in three formats: Desktop, Cloud, or Server. Graphlytic Desktop is a Neo4j Desktop app that can be installed in just a few mouse clicks. Cloud instances are great for small teams who don't want or need to worry about installing and need to be up and running quickly.

Apache TinkerPop™, a graph computing framework, is available for graph databases (OLTP), and graph analytic system (OLAP). Apache TinkerPop's graph traversal language is Gremlin. Gremlin allows users to express complex traversals (or queries) on their application's property diagram in a concise, data-flow language. Each Gremlin traversal consists of a sequence (potentially nested). A graph is a structure that is composed of vertices or edges. Each edge and vertices can have an unlimited number of key/value pairs, called properties. Vertices can be used to denote discrete objects, such as a person or a place or an event. Edges denote relationships between vertices. A person might know another person, be involved in an event, or have been to a specific place recently. If a domain contains a heterogeneous set objects (vertices), that can be linked to one another in many ways (edges), it is called a domain.

Sparksee, formerly known as DEX, is space- and performance-friendly. It has a small footprint and can quickly analyze large networks. It is natively compatible with.Net, C++ and Python and Objective-C. The graph is represented using bitmap data structures, which allow for high compression rates. Each bitmap is divided into chunks that can be placed on disk pages to increase I/O location. Bitmaps allow operations to be computed using binary logic instructions, which simplify execution in pipelined processors. Full native indexing allows for extremely fast access to all graph data structures. Bitmaps are used to represent node adjacencies in order to reduce their footprint. Advanced I/O policies reduce the number of times each page is brought into memory. Each value in the database can only be represented once, which prevents unnecessary replication.

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.

AnzoGraph DB offers a wide range of analytical features that can be used to enhance your analytical framework. This video will show you how AnzoGraph DB, a native graph database for massively parallel processing (MPP), is designed for data harmonization. Horizontally scalable graph database designed for online analytics and harmonization. AnzoGraphDB, a market-leading graph database, can help you tackle linked data problems and data harmonization. AnzoGraph DB offers industrialized online performance for enterprise-scale graph apps. AnzoGraph DB supports Labeled Property Graphs (LPGs) and familiar SPARQL*/OWL semantic graphs. You have access to many data science, machine learning, and analytical capabilities that will help you gain new insights at an unparalleled speed and scale. Your analysis will be more effective if you consider the context and relationships of data. Data loading and queries ultra-fast

RecallGraph is a versioned graph data store. It retains all changes its data (vertices, edges) have undergone to get to their current state. It supports point-in time graph traversals that allow the user to query any past state of a graph as well as the present. RecallGraph can be used in situations where data is best represented using a network of edges and vertices (i.e., as a graph). 1. Both edges and vertices can contain properties in the form attribute/value pairs (equivalent of JSON objects). 2. Documents (vertices/edges), can change throughout their lives (both in their individual attributes/values as well as in their relationships to each other). 3. Documents from the past are just as important as their current states, so it is essential to retain and queryable their change history. Also see this blog post for an intro - https://blog.recallgraph.tech/never-lose-your-old-data-again.

InfiniteGraph is a massively scalable graph database specifically designed to excel at high-speed ingest of massive volumes of data (billions of nodes and edges per hour) while supporting complex queries. InfiniteGraph can seamlessly distribute connected graph data across a global enterprise. InfiniteGraph is a schema-based graph database that supports highly complex data models. It also has an advanced schema evolution capability that allows you to modify and evolve the schema of an existing database. InfiniteGraph’s Placement Management Capability allows you to optimize the placement of data items resulting in tremendous performance improvements in both query and ingest. InfiniteGraph has client-side caching which caches frequently used node and edges. This can allow InfiniteGraph to perform like an in-memory graph database. InfiniteGraph's DO query language enables complex "beyond graph" queries not supported by other graph databases.

A reliable, easy-to-use, and powerful system to process and distribute data. Apache NiFi supports powerful, scalable directed graphs for data routing, transformation, system mediation logic, and is scalable. Apache NiFi's high-level capabilities and goals include a web-based user interface that provides seamless design, control, feedback and monitoring. Highly configurable, loss-tolerant, low latency and high throughput. Dynamic prioritization is also possible. Flow can be modified at runtime by back pressure, data provenance, and track dataflow from start to finish. This is a flexible system that is extensible. You can build your own processors. This allows for rapid development and efficient testing. Secure, SSL, SSH and HTTPS encryption, as well as encrypted content. Multi-tenant authorization, internal authorization/policy administration. NiFi includes a variety of web applications, including web UI, web API, documentation and custom UI's. You will need to map to the root path.

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.

Fluree is an immutable RDF graph database written in Clojure and adhering to W3C standards, supporting JSON and JSON-LD while accommodating various RDF ontologies. It operates with an immutable ledger that secures transactions with cryptographic integrity, alongside a rich RDF graph database capable of various queries. It employs SmartFunctions for enforcing data management rules, including identity and access management and data quality. Additionally, It boasts a scalable, cloud-native architecture utilizing a lightweight Java runtime, with individually scalable ledger and graph database components, embodying a "Data-Centric" ideology that treats data as a reusable asset independent of singular applications.

HugeGraph is a high-speed, highly-scalable graph database. HugeGraph's excellent OLTP capability allows for the storage and querying of billions of edges and vertices. Gremlin, a powerful graph traversal and query language, can handle complex graph queries in compliance with Apache TinkerPop 3. It supports Gremlin and is compliant to Apache TinkerPop 3. Schema Metadata Management includes VertexLabel EdgeLabel PropertyKey and IndexLabel. Multi-type Indexes that support complex combination queries, range query, and exact query. Plug-in Backend Store Driver Framework. Supports RocksDB, Cassandra and ScyllaDB. It is easy to add another backend store driver if necessary. Integration with Hadoop/Spark. HugeGraph is built on the TinkerPop framework. We refer to the storage structure and schema definition of DataStax.

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.

Dgraph is an open-source, low-latency, high throughput native and distributed graph database. DGraph is designed to scale easily to meet the needs for small startups and large companies with huge amounts of data. It can handle terabytes structured data on commodity hardware with low latency to respond to user queries. It addresses business needs and can be used in cases that involve diverse social and knowledge networks, real-time recommendation engines and semantic search, pattern matching, fraud detection, serving relationship information, and serving web applications.

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.

Cayley is an open source database for Linked Data. It was inspired by Google's Knowledge Graph graph database (formerly Freebase). Cayley is an open source graph database that allows you to store complex data and makes it easy to use. Built-in query editor, visualizer, and REPL. Cayley supports multiple query languages, including Gizmo, a query engine inspired by Gremlin and GraphQL-inspired query languages, MQL, a simplified version for Freebase lovers, and MQL. Cayley is modular and easy to connect with your favorite programming languages. It can also be used by back-end stores. Cayley has been well tested and used by many companies for their production workloads. It is also fast and optimized for use in applications. Rough performance testing has shown that on 2014 consumer hardware, 134m quads of LevelDB are not a problem, and a multi-hop intersection query - films starring X or Y - takes 150ms. Cayley is set up to run in memory by default (that's what backendmemstore means).

Time Series Database (TSDB), supports high-speed data writing and reading. It has high compression ratios to ensure data storage costs are low. This service supports visualization of precision reduction and interpolation, multimetric aggregate computing, as well as query results. The TSDB service lowers storage costs and improves data writing, query, analysis efficiency. This allows you to manage large numbers of data points and collect more data. This service is widely used in a variety of industries, including IoT monitoring systems and enterprise energy management systems (EMSs), power supply monitoring systems, production security monitoring systems, and IoT monitoring. Optimizes database architectures. TSDB can read and write millions of data points in seconds. Uses an efficient compression algorithm that reduces the data point's size to 2 bytes. This saves more than 90% on storage costs.

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.

AllegroGraph is a revolutionary solution that allows infinite data integration. It uses a patented approach that unifies all data and siloed information into an Entity Event Knowledge Graph solution that supports massive big data analytics. AllegroGraph uses unique federated sharding capabilities to drive 360-degree insights, and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph offers users an integrated version Gruff, a browser-based graph visualization tool that allows you to explore and discover connections within enterprise Knowledge Graphs. Franz's Knowledge Graph Solution offers both technology and services to help build industrial strength Entity Event Knowledge Graphs. It is based on the best-of-class products, tools, knowledge, skills, and experience.

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.

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.

The TigerGraph™, a graph platform based on its Native Parallel Graph™, technology, represents the next evolution in graph database evolution. It is a complete, distributed parallel graph computing platform that supports web-scale data analytics in real time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you've been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data.

A distributed, fault-tolerant graph database. FlockDB is a distributed graph data base for storing adjancency tables. It has the following goals: support for high rates of add/update/remove operations, potientially complicated set arithmetic query, paging through query results sets containing millions, ability to "archive and later restore archived edges", horizontal scaling, including replication, and online migration. Multi-hop queries (or graph walking queries) and automatic shardmigrations are non-goals. FlockDB is simpler than other graph databases like neo4j, as it attempts to solve fewer problems. It can scale horizontally and is optimized for low latency, high throughput environments like web-sites. FlockDB is used by Twitter to store social graphs (who follows who, who blocks whom) as well as secondary indices. The Twitter FlockDB cluster has 13+ billion edges as of April 2010 and can sustain peak traffic of 20k write/second and 100k readers/second.

Nussknacker allows domain experts to use a visual tool that is low-code to help them create and execute real-time decisioning algorithm instead of writing code. It is used to perform real-time actions on data: real-time marketing and fraud detection, Internet of Things customer 360, Machine Learning inferring, and Internet of Things customer 360. A visual design tool for decision algorithm is an essential part of Nussknacker. It allows non-technical users, such as analysts or business people, to define decision logic in a clear, concise, and easy-to-follow manner. With a click, scenarios can be deployed for execution once they have been created. They can be modified and redeployed whenever there is a need. Nussknacker supports streaming and request-response processing modes. It uses Kafka as its primary interface in streaming mode. It supports both stateful processing and stateless processing.

Apache Doris is an advanced data warehouse for real time analytics. It delivers lightning fast analytics on real-time, large-scale data. Ingestion of micro-batch data and streaming data within a second. Storage engine with upserts, appends and pre-aggregations in real-time. Optimize for high-concurrency, high-throughput queries using columnar storage engine, cost-based query optimizer, and vectorized execution engine. Federated querying for data lakes like Hive, Iceberg, and Hudi and databases like MySQL and PostgreSQL. Compound data types, such as Arrays, Maps and JSON. Variant data types to support auto datatype inference for JSON data. NGram bloomfilter for text search. Distributed design for linear scaling. Workload isolation, tiered storage and efficient resource management. Supports shared-nothing as well as the separation of storage from compute.

No more low-level code or gluing together complex systems. SQL makes it easy to build and deploy pipelines quickly. Data engineering service that allows developers and data engineers to quickly build and deploy data pipelines for data-driven apps. It is easy to connect to and find available data using pre-built connectors for messaging, storage, and database engines. Each connection you make will result in a stream of data to or from the system. You can create your pipelines using SQL with Decodable. Pipelines use streams to send and receive data to and from your connections. Streams can be used to connect pipelines to perform the most difficult processing tasks. To ensure data flows smoothly, monitor your pipelines. Create curated streams that can be used by other teams. To prevent data loss due to system failures, you should establish retention policies for streams. You can monitor real-time performance and health metrics to see if everything is working.

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.

RelationalAI is a next generation database system that allows intelligent data applications to be built on relational knowledge graphs. Data-centric application design combines logic and data into reusable models. Intelligent data applications can understand and make use each relation in a model. Relational provides a knowledge graph system that allows knowledge to be expressed as executable models. These models can easily be extended using declarative, human-readable software. RelationalAI's expressive and declarative language results in a 10-100x decrease in code. By involving non-technical domain specialists in the creation process, and automating complex programming tasks, applications are created faster and with better quality. The extensible graph data model is a foundation for data-centric architecture. Integrate models to uncover new relationships and reduce barriers between applications.

Locstat, a graph intelligence platform, is a graph-based AI platform that integrates analytics, event processing and graph-based AI. It allows organizations to scale up next-generation data-driven solutions quickly. Research shows that adopting innovative AI-supported digitalization strategy can result in significant benefits and gains. We have had great success in improving customer efficiency and delivering significant ROI, as measured by ourselves and confirmed by research firms. This shows the value of advanced analytics technologies to solve today's complex issues more cost-effectively compared to solutions based on relational databases.

In the field of IoT stream processing and analytics, SQLstream ranks #1 according to ABI Research. Used by Verizon, Walmart, Cisco, and Amazon, our technology powers applications on premises, in the cloud, and at the edge. SQLstream enables time-critical alerts, live dashboards, and real-time action with sub-millisecond latency. Smart cities can reroute ambulances and fire trucks or optimize traffic light timing based on real-time conditions. Security systems can detect hackers and fraudsters, shutting them down right away. AI / ML models, trained with streaming sensor data, can predict equipment failures. Thanks to SQLstream's lightning performance -- up to 13 million rows / second / CPU core -- companies have drastically reduced their footprint and cost. Our efficient, in-memory processing allows operations at the edge that would otherwise be impossible. Acquire, prepare, analyze, and act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code, GUI dev environment. Edit scripts instantly and view instantaneous results without compiling. Deploy with native Kubernetes support. Easy installation includes Docker, AWS, Azure, Linux, VMWare, and more

Data collaboration made easy. We make collaboration easy for developers looking to innovate and data people looking for version control. TerminusDB is an open source knowledge graph database that allows for reliable, private and efficient revision control and collaboration. Nothing will make it easier to collaborate with others or create data-intensive apps. TerminusDB offers a full range of revision control features. TerminusHub allows users access to databases and to collaborate on shared resources. Flexible data storage, versioning, and sharing capabilities. Integration into your app or team collaboration. You can work locally and sync your changes when you push them. Easy querying, cleaning, visualization. You can integrate powerful version control and collaboration to your enterprise and individual customers. Remote data teams can collaborate on data projects easily.

Virtuoso, a Data Virtualization platform that enables fast and flexible harmonization between disparate data, increases agility for both individuals and enterprises. Virtuoso Universal server is a modern platform built upon existing open standards. It harnesses the power and flexibility of Hyperlinks (functioning like Super Keys) to break down data silos that hinder both enterprise and user ability. Virtuoso's core SQL & SPARQL powers many Enterprise Knowledge Graph initiatives, just as they power DBpedia. They also power a majority nodes in Linked Open Data Cloud, the largest publicly accessible Knowledge Graph. Allows for the creation and deployment of Knowledge Graphs atop existing data. APIs include HTTP, ODBC and JDBC, OLE DB and OLE DB.

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.

Blazegraph™, a graph database that supports Blueprints and RDF/SPARQL, is an ultra-high-performance graph database. It can support up to 50 Billion edges per machine. It is currently in production for Fortune 500 customers like EMC, Autodesk, among others. It supports key Precision Medicine applications, and is widely used for life sciences applications. It is extensively used to support Cyber analytics in government and commercial applications. It powers Wikidata Query Service, a Wikimedia Foundation project. You can choose an executable jar, war file, or tar.gz distribution. Blazegraph was designed to be simple to use and easy to get started. This is why it ships without SSL and authentication by default. We strongly recommend that you enable SSL, authentication and the appropriate network configurations for production deployments. Below are some useful links to help you do this.