Tarantool Graph DB is a graph and vector database
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Tarantool
Graph DB

Is a graph-vector database.Analyze data connections in real time using a high-speed graph and vector storage

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Business tasks solved
by Tarantool Graph DB

Reduce fraud risks during financial operations

Tarantool Graph DB-based solution: Scoring and anti-fraud systems based on the analysis of connections and interactions between people

Increase client loyalty and reduce customer churn

Tarantool Graph DB-based solution: Personalized recommendations and customer churn predictions based on analysis of the clients’ behavior and preferences

Reduce logistics and transport infrastructure management costs

Tarantool Graph DB-based solution: Optimal routes based on supply chain analysis

What is a graph
database?

Graph databases are used to analyze complex relationships between objects.

Data in graph DBMSs is represented as nodes and edges between the nodes. Here, nodes are entities or objects, and edges are relationships and connections between these objects. Graph databases allow you to effectively model complex data structures, including social and semantic networks, geographic maps, relationships between bank clients, etc.

As a rule, graph databases work in conjunction with ML models. Databases provide quick access to big data and parallel processing capabilities. It helps ML models build predictions faster and improves their accuracy.

Tarantool Graph DB
architecture

Tarantool Graph DB works with graph and vector data, integrating with business applications via HTTP and the openCypher API. It provides scaling tools such as clustering, replication, and sharding.

Tarantool Graph DB Capabilities

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Graph data operations

  • Graph analysis: connections and their detailed description
  • Data scheme configuration
  • CRUD operations with graph data
  • API for working with Java, Python, and Go application data
  • OpenCypher language support
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Operation and safety options

  • Role-based access control (RBAC)
  • Safety audit log
  • Automated cluster installation and startup
  • Cluster management options
  • Kubernetes environment deployment
  • Export of monitoring metrics from Prometheus and Grafana
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Additional
features

  • Embedding vectors to graph vertices
  • Interface for working with graphs
  • Graph data sharding
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Benefits of Tarantool Graph DB

Real-time data analysis with in-memory features

Vector analysis for finding similar objects. This can be used, for instance, to increase fraud detection accuracy

High reliability: ACID support

Horizontal scaling with graph data sharding

Solution by a Russian vendor: support and configuration of the product based on your needs

The database is adapted to work on Russian ISs: Astra Linux, REDOS, and Alt.

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