Best Graph Databases for Microsoft Azure

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.

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.

PuppyGraph allows you to query multiple data stores in a single graph model. Graph databases can be expensive, require months of setup, and require a dedicated team. Traditional graph databases struggle to handle data beyond 100GB and can take hours to run queries with multiple hops. A separate graph database complicates architecture with fragile ETLs, and increases your total cost ownership (TCO). Connect to any data source, anywhere. Cross-cloud and cross region graph analytics. No ETLs are required, nor is data replication. PuppyGraph allows you to query data as a graph directly from your data lakes and warehouses. This eliminates the need for time-consuming ETL processes that are required with a traditional graph databases setup. No more data delays or failed ETL processes. PuppyGraph eliminates graph scaling issues by separating computation from storage.

Vector search can give you a competitive edge. Streamline your AI/ML workflows, reduce costs and stay ahead with up to a 10x faster time-to market. ApertureDB’s unified multimodal management of data will free your AI teams from data silos and allow them to innovate. Setup and scale complex multimodal infrastructure for billions objects across your enterprise in days instead of months. Unifying multimodal data with advanced vector search and innovative knowledge graph, combined with a powerful querying engine, allows you to build AI applications at enterprise scale faster. ApertureDB will increase the productivity of your AI/ML team and accelerate returns on AI investment by using all your data. You can try it for free, or schedule a demonstration to see it in action. Find relevant images using labels, geolocation and regions of interest. Prepare large-scale, multi-modal medical scanning for ML and Clinical studies.

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.

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.

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

Luna is a subscription for Apache Cassandra support at DataStax. You can enjoy all the benefits offered by open-source Cassandra with the assurance that you have direct access the team that wrote the majority of the code. They also support some of the most important deployments around the globe. You will receive best practices, advice, as well as SLA-based support to maintain your Cassandra deployment. Scale without compromising performance or latency to manage the most complex real-time workloads. You can create highly interactive customer experiences that are real-time and highly interactive. Luna can help you resolve issues and follow best practices for Cassandra clusters. Services can be used to assist with the entire application life cycle. They also allow for deeper integration of your team as they work together on implementation.

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.