Tentris IDE
& Graph Visualization Tool
Explore, query and visualize your graph data in Tentris with gdotv.
A Purpose-Built IDE for Tentris Developers
If you’re looking to leverage Tentris’s high-performance, vector-enhanced graph workloads, gdotv will make your work go even further.
With gdotv, you have access to all sorts of SPARQL and RDF capabilities such as syntax highlighting, autocomplete suggestions, built-in SPARQL documentation, the best graph visualization along with tabular views, and SPARQL Query Guardrails. In addition, you can extract the ontological data along with your instance-based data model and leverage that for working with complex graph traversals and similarity search patterns.
Whether you’re querying, visualizing, or analyzing interconnected data enriched with vector search, gdotv is designed to align with Tentris’s performance-oriented architecture. With interactive editing of nodes and relationships, alongside efficient rendering of large and dense graph structures, this Tentris IDE is optimized for investigating both structural and semantic relationships within your data.
Navigate your mix of graph and vector data in Tentris while making your experience more manageable and insightful with schema and ontology extraction as well as a uniform data model at all stages from query writing, semantic integrity checking (query guardrails), visual representation of the output graph, no-code data exploration, schema-aware views, and customizable graph visualizations.
An Overview of Tentris
Tentris an efficient disk-based graph database for RDF knowledge graphs.
As a modern graph technology provider, Tentris is focused on enabling ultra-fast querying by combining graph traversal with vector-based similarity search. Its core innovation lies in bridging traditional graph relationships with embedding-based retrieval, making it particularly well-suited for AI-driven and semantic applications.
Tentris is designed to handle complex queries that involve both structural graph patterns and high-dimensional vector similarity, which are increasingly common in modern use cases such as recommendation systems, knowledge graphs, and retrieval-augmented generation (RAG). Its architecture emphasizes performance and scalability, allowing it to efficiently process large datasets with low latency.
Rather than being a traditional transactional graph database, Tentris positions itself as a high performance query engine that can integrate with existing data systems. This makes it especially attractive for teams looking to augment their graph infrastructure with advanced search and AI capabilities without fully replacing their underlying storage layer.
What’s Possible with Tentris + gdotv
Easy Installation & Setup
Effortlessly integrate gdotv with your Tentris graph database with a simplified plug-and-play database connector. The gdotv database client provides straightforward database connection and configuration instructions to get you started in less than a minute.
This Tentris IDE is available to download for Windows, macOS, and Linux with a one-click installer to get you started instantly.
Centralized Connection Management
gdotv can be used to query and compare data from a huge range of graph database vendors – simultaneously! We don’t just work with Tentris: gdotv data visualization tools fully integrate with various other graph technologies, including all Apache TinkerPop™ compatible graph databases and most LPG and RDF providers.
gdotv is fully compatible with query languages like Gremlin, Cypher, Google SQL, SQL:2023, SPARQL and more. Using an intuitive UI, you can switch between your connections and queries seamlessly.
Customizable Data Visualization
You can create custom visualization rules for your Tentris graph database with gdotv to determine the look and feel of your data.
The gdotv database client boasts easy-to-configure style options that you can use to customize vertices and edges based on their labels and property values.
You can choose any color, size, or background image and adjust other elements to match your preference.
No-Code Data Exploration with the gdotv Graph Data Explorer
Use the built-in gdotv Graph Data Explorer to navigate your Tentris data without using queries.
The Graph Data Explorer allows you to define path patterns to query from your data, using filters on both your vertices and edges. Elements in the declared path can be filtering according to their label, direction, and property values, allowing you to perform complex path-pattern searches with no code.
Instantly Load & View Your Data Model
Understanding and verifying your data schema is critical component of graph management. This is why gdotv provides an overview of your data structure with the data model view.
For Tentris, there is no need to provide a data model, as gdotv is able to infer the schema directly from the data itself. This is just a click away, meaning that you always have an bird’s-eye view of your vertices, edges, and properties right at your fingertips.
Modify Your Tentris Graph Data Directly within gdotv
Want to adjust something in your graph? Take a hands-on approach and manage your Tentris graph directly.
Using gdotv, you can directly create, modify, and delete the edges and vertices – as well as modify the properties associated with them – allowing you to make changes on the fly.
Take Advantage of Syntax Validation
Using gdotv language highlighting and syntax checking for SPARQL makes your code easier to understand and visually parse, warning you of any error that would prevent it from executing against your Tentris instance.
Take Control of your Queries with the gdotv SPARQL Guardrails
Since RDF is fundamentally schema-optional, gdotv won’t enforce any schema against your graph. It will, however, check your SPARQL queries against the inferred schema, meaning it will automatically generate warnings if it detects potential ontology clashes.
This gives you additional insight into malformed queries, even when they execute normally against your RDF triplestore.
Visualization Optimized for RDF
gdotv offers graph visualization specially developed for RDF triplestores
The nodes and edges are detected from your query results, and any literals will be interpreted as properties. To improve readability, gdotv has built in IRI shortening and prefix handling. You can customize your graph labels further using inferred schema from the graph, such as via RDFS statements.
State-of-the-Art SPARQL Editor
The gdotv SPARQL code editor is the most powerful available – it offers data schema-accurate auto completion and embedded official documentation for SPARQL to give you all the information and suggestions you need to write your Tentris queries faster and more effectively.
Frequently Asked Questions (FAQs)
gdotv: The Tentris IDE
Turn your graph data into connected insights when you use gdotv to query, explore, and visualize your Tentris graph database.
Sign up for a free trial today and discover how gdotv amps up your productivity as the perfect Tentris IDE and graph visualization tool.
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