TIBCO Graph Database Description
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.
TIBCO Graph Database Alternatives
HugeGraph
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.
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Titan
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.
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Apache TinkerPop
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.
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Memgraph
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.
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Company Details
Company:
TIBCO
Year Founded:
1997
Headquarters:
United States
Website:
www.tibco.com/products/tibco-graph-database
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