ReGraph Integrations

Titan stands out as a leading investment firm, managing an impressive $500 million for a diverse clientele of 25,000 individuals. While Wall Street tends to prioritize the affluent, we felt this imbalance needed addressing, prompting us to create Titan: an exceptional investment management service tailored for everyone. Our mission is focused on long-term capital growth, grounded in our proven investment philosophy of pinpointing rare stocks known as “compounders” and maintaining our investment positions. We not only manage your investments with expertise but also ensure that you understand every aspect of the process. By offering our clients exclusive insights, they gain knowledge and become more informed investors than ever before. With features ranging from instant investing to direct portfolio manager interactions, we equip our clients with advanced tools that are often unavailable elsewhere, all at no additional cost. Our diverse team consists of seasoned professionals from various sectors, including experienced investors, engineers, operations specialists, and product experts, all dedicated to serving our clients. Our employees and advisors bring a wealth of experience from leading global institutions, ensuring that you receive top-notch service and guidance.

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.

Cloud-based solutions for enterprise search, observability, and security. Effortlessly access information, derive valuable insights, and safeguard your technological assets regardless of whether you utilize Amazon Web Services, Google Cloud, or Microsoft Azure. We take care of all maintenance tasks, allowing you to concentrate on deriving insights that drive your business forward. Setting up configurations and deployments is seamless. With straightforward scaling options, customizable plugins, and a framework tailored for log and time series data, the possibilities are extensive. Experience the full suite of Elastic features, including machine learning, Canvas, APM, index lifecycle management, Elastic App Search, and Elastic Workplace Search, all offered uniquely here. Logging and metrics are merely the beginning; unify your varied data sources to tackle security challenges, enhance observability, and fulfill other essential objectives in your operations. Moreover, our platform empowers you to make data-driven decisions swiftly and effectively.

Azure Cosmos DB offers a fully managed NoSQL database solution tailored for contemporary application development, ensuring single-digit millisecond response times and an impressive availability rate of 99.999 percent, all supported by service level agreements. This service provides automatic, instantaneous scalability and supports open-source APIs for MongoDB and Cassandra, allowing for rapid data operations. With its turnkey multi-master global distribution, users can experience swift read and write operations from any location around the globe. Additionally, Azure Cosmos DB enables organizations to accelerate their decision-making processes by facilitating near-real-time analytics and AI capabilities on the operational data housed within the database. Furthermore, Azure Synapse Link for Azure Cosmos DB integrates effortlessly with Azure Synapse Analytics, ensuring smooth performance without necessitating data movement or compromising the efficiency of the operational data store, enhancing the overall functionality of your data strategy. This integration not only streamlines workflows but also empowers users to derive insights more efficiently.

Amazon Neptune is an efficient and dependable graph database service that is fully managed, facilitating the development and operation of applications that handle intricate, interconnected datasets. At its heart, Amazon Neptune features a specialized, high-performance database engine tailored for the storage of billions of relationships while enabling rapid querying with latency measured in milliseconds. It accommodates widely-used graph models, including Property Graph and W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which simplifies the process of crafting queries for navigating complex datasets. This service supports various graph-based applications, including recommendation systems, fraud detection mechanisms, knowledge graphs, drug discovery initiatives, and enhanced network security protocols. With a proactive approach, it enables the detection and analysis of IT infrastructure threats through a multi-layered security framework. Furthermore, it allows users to visualize their entire infrastructure to effectively plan, forecast, and address potential risks, while also enabling the creation of graph queries for the near-real-time identification of fraudulent patterns in financial and purchasing activities, thereby enhancing overall security and efficiency.

Memgraph offers a light and powerful graph platform comprising the Memgraph Graph Database, MAGE Library, and Memgraph Lab Visualization. Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It comes with a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis, making Memgraph an excellent choice in critical decision-making scenarios such as risk assessment (fraud detection, cybersecurity threat analysis, and criminal risk assessment), 360-degree data and network exploration (Identity and Access Management (IAM), Master Data Management (MDM), Bill of Materials (BOM)), and logistics and network optimization. Memgraph's vibrant open-source community brings together over 150,000 developers in more than 100 countries to exchange ideas and optimize the next generation of in-memory data-driven applications across GenAI/ LLMs and real-time analytics performed with streaming data.

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.

JanusGraph stands out as a highly scalable graph database designed for efficiently storing and querying extensive graphs that can comprise hundreds of billions of vertices and edges, all managed across a cluster of multiple machines. This project, which operates under The Linux Foundation, boasts contributions from notable organizations such as Expero, Google, GRAKN.AI, Hortonworks, IBM, and Amazon. It offers both elastic and linear scalability to accommodate an expanding data set and user community. Key features include robust data distribution and replication methods to enhance performance and ensure fault tolerance. Additionally, JanusGraph supports multi-datacenter high availability and provides hot backups for data security. All these capabilities are available without any associated costs, eliminating the necessity for purchasing commercial licenses, as it is entirely open source and governed by the Apache 2 license. Furthermore, JanusGraph functions as a transactional database capable of handling thousands of simultaneous users performing complex graph traversals in real time. It ensures support for both ACID properties and eventual consistency, catering to various operational needs. Beyond online transactional processing (OLTP), JanusGraph also facilitates global graph analytics (OLAP) through its integration with Apache Spark, making it a versatile tool for data analysis and visualization. This combination of features makes JanusGraph a powerful choice for organizations looking to leverage graph data effectively.

Cayley is an open-source database tailored for Linked Data, drawing inspiration from the graph database that supports Google's Knowledge Graph, previously known as Freebase. This graph database is crafted for user-friendliness and adept at handling intricate data structures, featuring an integrated query editor, a visualizer, and a Read-Eval-Print Loop (REPL). It supports various query languages, including Gizmo, which is influenced by Gremlin, a GraphQL-like query language, and MQL, a streamlined version catering to Freebase enthusiasts. Cayley's modular architecture allows seamless integration with preferred programming languages and backend storage solutions, making it production-ready, thoroughly tested, and utilized by numerous companies for their operational tasks. Additionally, it is optimized for application use, demonstrating impressive performance metrics; for instance, testing has shown that it can effortlessly manage 134 million quads in LevelDB on consumer-grade hardware from 2014, with multi-hop intersection queries—such as finding films featuring both X and Y—executing in about 150 milliseconds. By default, Cayley is set up to operate in-memory, which is what the backend memstore refers to, thereby enhancing its speed and efficiency for data retrieval and manipulation. Overall, Cayley offers a powerful solution for those looking to leverage linked data in their applications.

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

Store data in its native format for graph, document, and search purposes. Leverage a comprehensive query language that allows for rich access to this data. Map the data directly to the database and interact with it through optimal methods tailored for specific tasks, such as traversals, joins, searches, rankings, geospatial queries, and aggregations. Experience the benefits of polyglot persistence without incurring additional costs. Design, scale, and modify your architectures with ease to accommodate evolving requirements, all while minimizing effort. Merge the adaptability of JSON with advanced semantic search and graph technologies, enabling the extraction of features even from extensive datasets, thereby enhancing data analysis capabilities. This combination opens up new possibilities for handling complex data scenarios efficiently.

OrientDB stands out as the fastest graph database globally. An independent benchmarking analysis conducted by IBM alongside the Tokyo Institute of Technology revealed that OrientDB outperforms Neo4j by a factor of ten in graph operations across various workloads. This exceptional speed can help organizations gain a competitive edge and foster innovation, ultimately leading to the development of new revenue opportunities. By leveraging OrientDB, businesses can enhance their operational efficiency and stay ahead in a rapidly evolving market.