Alternatives to GraphAware
Compare GraphAware alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to GraphAware in 2026. Compare features, ratings, user reviews, pricing, and more from GraphAware competitors and alternatives in order to make an informed decision for your business.
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Minitab Statistical Software
Minitab
For 50 years, Minitab has helped thousands of companies and institutions spot trends, solve problems, and discover valuable insights in their data through our comprehensive, best-in-class suite of data analysis and process improvement tools. Our namesake product, Minitab Statistical Software, leads the way in data analysis with the power to visualize, analyze and harness your data to gain insights and solve your toughest challenges. Access trusted, proven and modern analytics combined with dynamic visualizations to empower you and your decisions. The latest version of Minitab Statistical Software includes access to Minitab on the cloud so you can analyze from anywhere, and Graph Builder, our new interactive tool to instantly create multiple graph options at once. Minitab offers modules for Predictive Analytics and Healthcare to boost your analytics even further. Available in 8 languages: English, Chinese, French, German, Japanese, Korean, Spanish, and Portuguese. -
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JMP Statistical Software
JMP Statistical Discovery
JMP, data analysis software for Mac and Windows, combines the strength of interactive visualization with powerful statistics. Importing and processing data is easy. The drag-and-drop interface, dynamically linked graphs, libraries of advanced analytic functionality, scripting language and ways of sharing findings with others, allows users to dig deeply into their data, with greater ease and speed. Originally developed in the 1980’s to capture the new value in GUI for personal computers, JMP remains dedicated to adding cutting-edge statistical methods and special analysis techniques from a variety of industries to the software’s functionality with each release. The organization's founder, John Sall, still serves as Chief Architect.Starting Price: $1320/year/user -
3
i2
N. Harris Computer Corporation
Turn overwhelming and disparate data from multiple sources into actionable intelligence in near-real time to make informed decisions. Quickly find hidden connections and critical patterns buried in internal, external, and open-source data. Experience i2’s world-class intelligence analysis software for yourself. Request an i2 demo and learn how to uncover critical connections and hidden insights faster than ever. Track critical missions across law enforcement, fraud and financial crime, military defense, and national security and intelligence sectors with the i2 intelligence analysis platform. Capture and fuse structured and unstructured data from internal and external sources, including OSINT and dark web data, to provide an expansive data pool to search and discover over. Fuse advanced analytics with sophisticated geospatial, visual, graph, temporal, and social analysis capabilities to give analysts greater situational awareness. -
4
InfiniteGraph
Objectivity
InfiniteGraph is a massively scalable graph database specifically designed to excel at high-speed ingest of massive volumes of data (billions of nodes and edges per hour) while supporting complex queries. InfiniteGraph can seamlessly distribute connected graph data across a global enterprise. InfiniteGraph is a schema-based graph database that supports highly complex data models. It also has an advanced schema evolution capability that allows you to modify and evolve the schema of an existing database. InfiniteGraph’s Placement Management Capability allows you to optimize the placement of data items resulting in tremendous performance improvements in both query and ingest. InfiniteGraph has client-side caching which caches frequently used node and edges. InfiniteGraph's DO query language enables complex "beyond graph" queries not supported by other query languages. -
5
NodeXL
Social Media Research Foundation
NodeXL is a template for Microsoft® Excel® (2007, 2010, 2013 and 2016) on Windows (XP, Vista, 7, 8, 10) that lets you enter a network edge list into a workbook, click a button, see a network graph, and get a detailed summary report, all in the familiar environment of the Excel® spreadsheet application. Customize the network graph's appearance. Zoom, scale and pan the graph. Calculate basic graph metrics. Dynamically filter vertices and edges. Alter the graph's layout. Find clusters of related vertices. The NodeXL Pro application can be licensed for a 12 month period, adding additional features. Calculate advanced graph metrics. Import and export graphs to a variety of file formats. Get social networks using built-in connections to Twitter, Facebook, Flickr, YouTube, Wikis, Blogs, Instagram, Network Surveys, and email. Automate network graph collection and creation. If you use Excel® on Windows you can download and use NodeXL Basic now. Or license NodeXL Pro for additional features.Starting Price: $749 per year -
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Graphlytic
Demtec
Graphlytic is a customizable web platform for knowledge graph visualization and analysis. Users can interactively explore the graph, look for patterns with the Cypher or Gremlin query languages (or query templates for non-tech users), or use filters to find the answers to any graph question. The graph visualization brings deep insights in industries, such as scientific research, anti-fraud investigation, etc. Users with very little graph theory knowledge can start to explore the data in no time. Graph rendering is done with the Cytoscape.js library which allows us to render tens of thousands of nodes and hundreds of thousands of relationships. The application is provided in three ways: Desktop, Cloud, and Server. Graphlytic Desktop is a free Neo4j Desktop application installed in just a few clicks. Cloud instances are ideal for small teams that don't want to worry about the installation and need to get up and running in very little time.Starting Price: 19 EUR/month -
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Anahita
Anahita
Anahita is a platform and framework for developing open science and knowledge sharing applications on a social networking foundation. Use Anahita to build online learning and knowledge sharing networks, information access networks about people, places, and things, open science and open data networks, online collaboration environment and cloud back-end for your mobile apps. Anahita provides a genuine nodes and graphs architecture as well as design patterns for building social networking apps. Anahita’s native framework provides a graph architecture and necessary design patterns that you need for developing social apps that work seamlessly with each other. Unlike conventional web applications, Anahita stores app’s data as a network of interconnected nodes and graphs which makes it ready to be used for real-time analysis. We have developed Anahita using open source technologies that are globally accessible to developers such as the LAMP stack and Javascript. -
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PuppyGraph
PuppyGraph
PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.Starting Price: Free -
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Stardog
Stardog Union
With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.Starting Price: $0 -
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Cayley
Cayley
Cayley is an open-source database for Linked Data. It is inspired by the graph database behind Google's Knowledge Graph (formerly Freebase). Cayley is an open-source graph database designed for ease of use and storing complex data. Built-in query editor, visualizer and REPL. Cayley can use multiple query languages like Gizmo, a query language inspired by Gremlin, GraphQL-inspired query language, MQL a simplified version for Freebase fans. Cayley is modular, easy to connect to your favorite programming languages and back-end stores, production ready, well tested and used by various companies for their production workloads and fast with optimized specifically for usage in applications. Rough performance testing shows that, on 2014 consumer hardware and an average disk, 134m quads in LevelDB is no problem and a multi-hop intersection query- films starring X and Y - takes ~150ms. Cayley is configured by default to run in memory (That's what backend memstore means). -
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Amazon Neptune
Amazon
Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. Proactively detect and investigate IT infrastructure using a layered security approach. Visualize all infrastructure to plan, predict and mitigate risk. Build graph queries for near-real-time identity fraud pattern detection in financial and purchase transactions. -
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Oracle Spatial and Graph
Oracle
Graph databases, part of Oracle’s converged database offering, eliminate the need to set up a separate database and move data. Analysts and developers can perform fraud detection in banking, find connections and link to data, and improve traceability in smart manufacturing, all while gaining enterprise-grade security, ease of data ingestion, and strong support for data workloads. Oracle Autonomous Database includes Graph Studio, with one-click provisioning, integrated tooling, and security. Graph Studio automates graph data management and simplifies modeling, analysis, and visualization across the graph analytics lifecycle. Oracle provides support for both property and RDF knowledge graphs, and simplifies the process of modeling relational data as graph structures. Interactive graph queries can run directly on graph data or in a high-performance in-memory graph server. -
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Grakn
Grakn Labs
Building intelligent systems starts at the database. Grakn is an intelligent database - a knowledge graph. An insanely intuitive & expressive data schema, with constructs to define hierarchies, hyper-entities, hyper-relations and rules, to build rich knowledge models. An intelligent language that performs logical inference of data types, relationships, attributes and complex patterns, during runtime, and over distributed & persisted data. Out-of-the-box distributed analytics (Pregel and MapReduce) algorithms, accessible through the language through simple queries. Strong abstraction over low-level patterns, enabling simpler expressions of complex constructs, while the system figures out the most optimal query execution. Scale your enterprise Knowledge Graph with Grakn KGMS and Workbase. A distributed database designed to scale over a network of computers through partitioning and replication. -
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KronoGraph
Cambridge Intelligence
From transactions to meetings, every event happens at a point or duration in time. Successful investigations need to understand how those events unfold, and how they’re linked. KronoGraph is the first toolkit for scalable timeline visualizations that reveal patterns in time data. Build interactive timeline tools to explore how relationships and events evolve. Whether you need to investigate phone calls between two people or IT traffic across a whole enterprise network, KronoGraph provides a rich, interactive view of the data. Transition smoothly from an aggregated high-level summary to individual events, powering investigations as they grow. Investigations often rely on identifying specific points of interest a person, an event, a connection. With KronoGraph’s interactive view you can scroll through time, uncover anomalies and patterns and zoom into individual entities that reveal the hidden story in your data. -
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AnzoGraph DB
Cambridge Semantics
With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries. -
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GraphQL
The GraphQL Foundation
GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools. Send a GraphQL query to your API and get exactly what you need, nothing more and nothing less. GraphQL queries always return predictable results. Apps using GraphQL are fast and stable because they control the data they get, not the server. GraphQL queries access not just the properties of one resource but also smoothly follow references between them. While typical REST APIs require loading from multiple URLs, GraphQL APIs get all the data your app needs in a single request. Apps using GraphQL can be quick even on slow mobile network connections. -
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KgBase
KgBase
KgBase, or Knowledge Graph Base, is a collaborative, robust database with versioning, analytics & visualizations. With KgBase, any community or individual can create knowledge graphs to build insights about their data. Import your CSVs and spreadsheets, or use our API to work on data together. Build no-code knowledge graphs with KgBase, our easy-to-use UI lets you traverse the graph, show the results as tables and charts, and much more. Play with your graph data. Build your query and see results update in real time. It's like writing query code in Cypher or Gremlin, except easier. And fast. Your graph can be viewed as a table, allowing you to browse all results - no matter the size. KgBase works great with large graphs (millions of nodes), as well as simple projects. In the cloud, or self-hosted, with wide database support. Introduce graphs into your organization by seeding graph from a template. Results of any query can be easily turned into a chart visualization.Starting Price: $19 per month -
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Graphweaver
Exogee
Turn multiple data sources into a single GraphQL API. Features: 📝 Code-first GraphQL API: Save time and code efficiently with our code-first approach. 🚀 Built for Node in Typescript: The power of Typescript combined with the flexibility of Node.js. 🔗 Connect to Multiple Datasources: Seamlessly integrate Postgres, MySql, Sqlite, REST, and more. 🎯 Instant GraphQL API: Get your API up and running quickly with automatic queries and mutations. 🔄 One Command Import: Easily import an existing database with a simple command-line tool.Starting Price: Free -
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GraphDB
Ontotext
*GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.* GraphDB is a highly efficient and robust graph database with RDF and SPARQL support. The GraphDB database supports a highly available replication cluster, which has been proven in a number of enterprise use cases that required resilience in data loading and query answering. If you need a quick overview of GraphDB or a download link to its latest releases, please visit the GraphDB product section. GraphDB uses RDF4J as a library, utilizing its APIs for storage and querying, as well as the support for a wide variety of query languages (e.g., SPARQL and SeRQL) and RDF syntaxes (e.g., RDF/XML, N3, Turtle). -
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Rawcubes
Rawcubes
The only software that combines data intelligence through knowledge Graph with multi cloud data strategies to enable better business insights. Lack of Insightful data preventing you from running successful campaigns? Uncover the intelligence and learn what your customer wants! Get a 360-degree view of the business operations through a single, end-to-end analysis using our proprietary product, DataBlaze. Empower your data experts with data strategies models. No need to write codes, no human errors. Leverage pre-built ML models to aid insurers in accurately evaluating and managing property risk. Rawcubes helps businesses utilize their data by leveraging our data platforms, pre-built domain knowledge graph, and analytical models to enable better business insights. Rawcubes provides world-class data management software, business analytical models, and access to a team of data scientists and data engineers if you need expert advice or just to bounce around an idea or two. -
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FalkorDB
FalkorDB
FalkorDB is an ultra-fast, multi-tenant graph database optimized for GraphRAG, delivering accurate, relevant AI/ML results with reduced hallucinations and enhanced performance. It leverages sparse matrix representations and linear algebra to efficiently handle complex, interconnected data in real-time, resulting in fewer hallucinations and more accurate responses from large language models. FalkorDB supports the OpenCypher query language with proprietary enhancements, enabling expressive and efficient querying of graph data. It offers built-in vector indexing and full-text search capabilities, allowing for complex searches and similarity matching within the same database environment. FalkorDB's architecture includes multi-graph support, enabling multiple isolated graphs within a single instance, ensuring security and performance across tenants. It also provides high availability with live replication, ensuring data is always accessible. -
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Head AI
Head AI
Headai is a decision-intelligence platform that transforms complex, fragmented, and unstructured data into actionable insights through sophisticated AI techniques such as knowledge graphs, predictive signals, and natural language processing. It ingests both structured and unstructured inputs, ranging from databases and APIs to text documents and news media, and constructs interactive knowledge graphs that reveal contextual relationships, emerging trends, and thematic patterns. Core features include extracting metadata and keywords from large text corpora, dynamically adapting and organizing datasets through labeling and topic extension, and generating scorecards for KPI or benchmark comparisons. With its “Compass” tool, users can simulate scenarios, prioritize strategic actions, and guide skills development and decision-making. Insights can be explored via open-source visualizers or seamlessly exported to BI platforms and workflows through JSON/CSV outputs and APIs. -
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Tom Sawyer Perspectives
Tom Sawyer Software
Tom Sawyer Perspectives is a robust platform for building enterprise-class graph and data visualization and analysis applications. It is a complete graph visualization software development kit (SDK) with a graphics-based design and preview environment. The platform integrates enterprise data sources with our powerful graph visualization, layout, and analysis technology to solve big data problems. Tom Sawyer Perspectives enables developers to quickly develop production-quality data-oriented visualization applications. Two graphic modules—the Designer and Previewer—are used to build applications to visualize and analyze the specific data that drives each project. Using the Designer, developers extract or define schema, data sources, bindings, rules, views, filters, and searches. Additionally, they can also use the Designer to specify custom toolbars, tooltips, context menus, and graphical viewing and editing behaviors. -
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RushDB
RushDB
RushDB is an open-source zero-configuration graph database that instantly transforms JSON and CSV into a fully normalized, queryable Neo4j graph - without the overhead of schema design, migrations, or manual indexing. Designed for modern applications, AI, and ML workflows, RushDB provides a frictionless developer experience, combining the flexibility of NoSQL with the structured power of relational databases. With automatic data normalization, ACID compliance, and a powerful API, RushDB eliminates the complexities of data ingestion, relationship management, and query optimization - so you can focus on building, not database administration. Key Features: 1. Zero Configuration, Instant Data Ingestion 2. Graph-Powered Storage & Queries 3. ACID Transactions & Schema Evolution 4. Developer-Centric API: Query Like an SDK 5. High-Performance Search & Analytics 6. Self-Hosted or Cloud-ReadyStarting Price: $9/month -
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Papr
Papr.ai
Papr is an AI-native memory and context intelligence platform that provides a predictive memory layer combining vector embeddings with a knowledge graph through a single API, enabling AI systems to store, connect, and retrieve context across conversations, documents, and structured data with high precision. It lets developers add production-ready memory to AI agents and apps with minimal code, maintaining context across interactions and powering assistants that remember user history and preferences. Papr supports ingestion of diverse data including chat, documents, PDFs, and tool data, automatically extracting entities and relationships to build a dynamic memory graph that improves retrieval accuracy and anticipates needs via predictive caching, delivering low latency and state-of-the-art retrieval performance. Papr’s hybrid architecture supports natural language search and GraphQL queries, secure multi-tenant access controls, and dual memory types for user personalization.Starting Price: $20 per month -
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Dgraph
Hypermode
Dgraph is an open source, low-latency, high throughput, native and distributed graph database. Designed to easily scale to meet the needs of small startups as well as large companies with massive amounts of data, DGraph can handle terabytes of structured data running on commodity hardware with low latency for real time user queries. It addresses business needs and uses cases involving diverse social and knowledge graphs, real-time recommendation engines, semantic search, pattern matching and fraud detection, serving relationship data, and serving web apps. -
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Kibana
Elastic
Kibana is a free and open user interface that lets you visualize your Elasticsearch data and navigate the Elastic Stack. Do anything from tracking query load to understanding the way requests flow through your apps. Kibana gives you the freedom to select the way you give shape to your data. With its interactive visualizations, start with one question and see where it leads you. Kibana core ships with the classics: histograms, line graphs, pie charts, sunbursts, and more. And, of course, you can search across all of your documents. Leverage Elastic Maps to explore location data, or get creative and visualize custom layers and vector shapes. Perform advanced time series analysis on your Elasticsearch data with our curated time series UIs. Describe queries, transformations, and visualizations with powerful, easy-to-learn expressions. -
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Nebula Graph
vesoft
The graph database built for super large-scale graphs with milliseconds of latency. We are continuing to collaborate with the community to prepare, popularize and promote the graph database. Nebula Graph only allows authenticated access via role-based access control. Nebula Graph supports multiple storage engine types and the query language can be extended to support new algorithms. Nebula Graph provides low latency read and write , while still maintaining high throughput to simplify the most complex data sets. With a shared-nothing distributed architecture , Nebula Graph offers linear scalability. Nebula Graph's SQL-like query language is easy to understand and powerful enough to meet complex business needs. With horizontal scalability and a snapshot feature, Nebula Graph guarantees high availability even in case of failures. Large Internet companies like JD, Meituan, and Xiaohongshu have deployed Nebula Graph in production environments. -
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ArangoDB
ArangoDB
Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets. -
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Apache TinkerPop
Apache Software Foundation
Apache TinkerPop™ is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP). Gremlin is the graph traversal language of Apache TinkerPop. Gremlin is a functional, data-flow language that enables users to succinctly express complex traversals on (or queries of) their application's property graph. Every Gremlin traversal is composed of a sequence of (potentially nested) steps. A graph is a structure composed of vertices and edges. Both vertices and edges can have an arbitrary number of key/value pairs called properties. Vertices denote discrete objects such as a person, a place, or an event. Edges denote relationships between vertices. For instance, a person may know another person, have been involved in an event, and/or have recently been at a particular place. If a user's domain is composed of a heterogeneous set of objects (vertices) that can be related to one another in a multitude of ways (edges).Starting Price: Free -
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G.V() Gremlin IDE
gdotv Ltd
G.V() is an all-in-one Gremlin IDE to write, debug, test and analyze results for your Gremlin graph database. It offers rich a UI with smart autocomplete, graph visualization, editing and connection management. G.V() automatically detects your connection setting requirements based on the hostname you provide and prompts you for the next required information for an easy onboarding experience, regardless of which Gremlin database you're using. Load, visualize and draw your graph in true “What You See Is What You Get” fashion to build, test, visualize and query your data easily. Learn Gremlin with the embedded documentation and G.V()'s in-memory graph. View your Gremlin query results in various formats allowing to test, navigate and understand your query results rapidly. Compatible with all major Apache TinkerPop enabled Graph Database Providers: Amazon Neptune, Azure Cosmos DB’s Gremlin API, DataStax Enterprise Graph, JanusGraph, ArcadeDB, Aliyun TairForGraph and Gremlin Server. -
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Sentinel Visualizer
FMS, Inc
Empowering the demanding needs of intelligence analysts, law enforcement, investigators, researchers, and information workers, Sentinel Visualizer is the next generation data visualization and analysis solution for your big data. With cutting edge features and best-of-breed usability, Sentinel Visualizer provides you with insight into patterns and trends hidden in your data. Its database driven data visualization platform lets you quickly see multi-level links among entities and model different relationship types. Advanced drawing and redrawing features generate optimized views to highlight the most important entities. Social Network Analysis (SNA) metrics reveal the most interesting suspects in complex webs. With advanced filtering, squelching, weighted relationship types, shortest path analysis, timelines, and integrated geospatial features, Sentinel Visualizer helps you maximize the value of your data.Starting Price: $2,899 -
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Amazon QuickSight
Amazon
Amazon QuickSight allows everyone in your organization to understand your data by asking questions in natural language, exploring through interactive dashboards, or automatically looking for patterns and outliers powered by machine learning. QuickSight powers millions of dashboard views weekly for customers such as the NFL, Expedia, Volvo, Thomson Reuters, Best Western and Comcast, allowing their end-users to make better data-driven decisions. Ask conversational questions of your data and use Q’s ML-powered engine to receive relevant visualizations without the time-consuming data preparation from authors and admins. Discover hidden insights from your data, perform accurate forecasting and what-if analysis, or add easy-to-understand natural language narratives to dashboards by leveraging AWS' expertise in machine learning. Easily embed interactive visualizations and dashboards, sophisticated dashboard authoring, or natural language query capabilities in your applications. -
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Infutor TrueSource
Infutor TrueSource
The volume of consumer data signals has increased dramatically in recent years. This steep upward trend has amplified the importance for marketers to bring these disparate digital and offline identity markers together in a cohesive way. Identity graphs — a single database that holds this consumer data — now play a vital role, serving as a master source of truth. Infutor’s TrueSource™ Identity Graph is the premier collection of consumer data and intelligence that makes omnichannel engagement personal — and measurably effective. Our secure and privacy-compliant ID graph enables you to create relevant, real-time experiences in whichever channel people engage with your brand. Leverage our TrueSource™ Identity Graph to add considerable value to every engagement with your customers and prospects. Infutor instantly verifies consumer identities via API at the moment of ingestion or inbound engagement. -
35
ent
ent
An entity framework for Go. Simple, yet powerful ORM for modeling and querying data. Simple API for modeling any database schema as Go objects. Run queries, and aggregations and traverse any graph structure easily. 100% statically typed and explicit API using code generation. The latest version of Ent now includes a type-safe API enabling ordering by fields and edges. This API will soon be available in our GraphQL integration too. You can now visualize your Ent schema as an ERD with one command. The API enables you to easily integrate features such as logging, tracing, caching, and even implementing soft deletion with 20 lines of code! The Ent framework supports GraphQL using the 99designs/gqlgen library and provides various integrations. Generating a GraphQL schema for nodes and edges defined in an Ent schema. Efficient field collection to overcome the N+1 problem without requiring data loaders.Starting Price: Free -
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Neo4j
Neo4j
Neo4j’s graph data platform is purpose-built to leverage not only data but also data relationships. Using Neo4j, developers build intelligent applications that traverse today's large, interconnected datasets in real time. Powered by a native graph storage and processing engine, Neo4j’s graph database delivers an intuitive, flexible and secure database for unique, actionable insights. -
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HugeGraph
HugeGraph
HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin (a powerful graph traversal language). Among its features, it provides compliance to Apache TinkerPop 3, supporting Gremlin. Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel. Multi-type Indexes, supporting exact query, range query and complex conditions combination query. Plug-in Backend Store Driver Framework, supporting RocksDB, Cassandra, ScyllaDB, HBase and MySQL now and easy to add other backend store driver if needed. Integration with Hadoop/Spark. HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax. -
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TIBCO Graph Database
TIBCO
To unveil the true value of constantly evolving business data, you need to understand the relationships in data in a much more profound way. Unlike other databases, a graph database puts relationships at the forefront, using Graph theory and Linear Algebra to traverse and show how complex data webs, data sources, and data points relate. TIBCO® Graph Database allows you to discover, store, and convert complex dynamic data into meaningful insights. Enable users to rapidly build data and computational models that establish dynamic relationships among organizational silos. These knowledge graphs deliver value by connecting your organization’s vast array of data and revealing relationships that let you accelerate optimization of assets and processes. Combined OLTP and OLAP features in a single enterprise-grade database. Optimistic ACID level transaction properties with native storage and access. -
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Maltego
Maltego Technologies
Maltego is a Java application that runs on Windows, Mac and Linux. Maltego is used by a broad range of users, ranging from security professionals to forensic investigators, investigative journalists, and researchers. Easily gather information from dispersed data sources. View up to 1 million entities on a graph. Access over 58 data sources in the Maltego transform hub. Connect public (OSINT), commercial and own data sources. Write your own Transforms. Automatically link and combine all information in one graph. Automatically combine disparate data sources in point-and-click logic. Use our regex algorithms to auto-detect entity types. Enrich your data through our intuitive graphical user interface. Use entity weights to detect patterns even in the largest graphs. Annotate your graph and export it for further use.Starting Price: €5000 per user per year -
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Memgraph
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. -
41
FICO® Identity Resolution Engine systematically scans across disparate and siloed data sources to uncover links between people, places, and events that can indicate connected fraud and money-laundering. World class fuzzy matching algorithms enhance detection while graph analytics visualize the connections across accounts in real -time, for both pre- and post-book detection. Use data points in an application to link it to other applications and accounts even when they are several degrees removed. Automate on-going analysis of accounts dependent on their risk profile, to uncover links that become apparent post-book. Proactively identify and prioritize organized fraud and criminal activities using relationship-driven predictive analytics. Conduct federated searches into uncleansed data and perform sophisticated link analysis. Utilize sophisticated query tools and visualize with link charts.
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42
Palturai
Palturai
Insights about millions of companies and people. We have gathered it from reliable sources and organized it with state-of-the-art knowledge graph technology. Our algorithms analyze the relations between all these entities. Match your own business contacts to our BusinessGraph to discover new opportunities and hidden risks connected to your very own ecosystem. Stay one step ahead of your competitors. Respond to changes in management or company status before anybody else. As a German company, we adhere to strict data protection laws. You alone decide what happens to your data. We put a huge international ecosystem at your disposal. With millions of nodes and connections. You provide your business partners and contacts. Today, still largely isolated databases. Our intelligent matching rules create your own BusinessGraph. It can be evaluated by our intelligent algorithms and tools in many different ways. -
43
DataChat
DataChat
Conversational Intelligence is a unique way for the human user to collaborate with a machine. Humans bring to the table their intuition, and the machine comes with its ability to self-drive through data uncovering interesting patterns. Thus, humans and machines play to their strengths and collaborate to discover hidden gems in data. Using the unique Conversational Intelligence technology pioneered by DataChat, now you can carry out a broad range of data analytics functions, including exploratory data analysis, predictive analytics, structured querying, free search querying, visualization and data wrangling in a single platform. And you can do this by simply conversing with the platform in controlled natural language. Do more with less, and faster. Get richer and faster insights from data even with small teams, and move your business at the speed of data. Improve your competitive advantage. DataChat AI is a conversational, natural language, data analytics platform -
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NeuroIntelligence
ALYUDA
NeuroIntelligence is a neural networks software application designed to assist neural network, data mining, pattern recognition, and predictive modeling experts in solving real-world problems. NeuroIntelligence features only proven neural network modeling algorithms and neural net techniques; software is fast and easy-to-use. Visualized architecture search, neural network training and testing. Neural network architecture search, fitness bars, network training graphs comparison. Training graphs, dataset error, network error, weights and errors distribution, neural network input importance. Testing, actual vs. output graph, scatter plot, response graph, ROC curve, confusion matrix. The interface of NeuroIntelligence is optimized to solve data mining, forecasting, classification and pattern recognition problems. You can create a better solution much faster using the tool's easy-to-use GUI and unique time-saving capabilities.Starting Price: $497 per user -
45
SmokePing
SmokePing
SmokePing is a deluxe latency measurement tool. It can measure, store and display latency, latency distribution, and packet loss. SmokePing uses RRDtool to maintain a long-term data store and to draw pretty graphs, giving up-to-the-minute information on the state of each network connection. Click on any graph in detail mode and use the mouse to mark your area of interest in the navigator graph. Show information from multiple targets in a graph. With one central Smokeping Master node, you can run a series of Slave nodes, taking their configuration from the master. This allows you to ping a single target from multiple locations. The standard deviation is now used in several places to give a number for the variation in round trip times as depicted by the smoke. Wide variety of probes, ranging from simple ping to web requests and custom protocols. Master/slave deployment model to run measurements from multiple sources in parallel.Starting Price: Free -
46
OpenText Unstructured Data Analytics
OpenText
OpenText™ Unstructured Data Analytics products employ AI and machine learning to help organizations uncover and leverage key insights stored deep within their unstructured data, including text, audio, video, and images. Organizations can connect all their data to understand the context and information locked inside high-growth unstructured content—at scale. Discover insights hidden within all types of media with unified text, speech, and video analytics that support more than 1,500 data formats. Use natural language processing, optical character recognition (OCR), and other AI-powered models to understand and track the meaning within unstructured data. Employ the latest innovations in machine learning and deep neural networks to understand written and spoken language in data, revealing greater insights. -
47
KeyLines
Cambridge Intelligence
Build game-changing graph visualization products that turn connected data into insight. Harness JavaScript’s power and flexibility to quickly and easily build graph visualization applications that can be deployed anywhere, to anyone. KeyLines is a completely flexible way to build your graph visualization application. Build interactive graph visualization tools to reveal threats and hidden insight. The KeyLines JavaScript graph visualization toolkit lets you build applications specifically for your users, your data, and the questions you need to answer. It fits with any browser, device, server, or database and comes with clear tutorials, demos, and API documentation. Combined with our developer support, you’ll be uncovering network insight in no time. KeyLines makes it easy to build high-performance JavaScript graph visualization tools that work anywhere. They harness HTML5 and WebGL graphics rendering and thoughtfully crafted code to give users fast and insightful visualization. -
48
The Graph
The Graph
APIs for a vibrant decentralized future. The Graph is an indexing protocol for querying networks like Ethereum and IPFS. Anyone can build and publish open APIs, called subgraphs, making data easily accessible. Subgraphs can be composed into a global graph of all the world's public information. This data can be transformed, organized, and shared across applications for anyone to query with just a few keystrokes. Before The Graph, teams had to develop and operate proprietary indexing servers. This required significant engineering and hardware resources and broke the important security properties required for decentralization. -
49
Quantexa
Quantexa
Uncover hidden risk and reveal new, unexpected opportunities with graph analytics across the customer lifecycle. Standard MDM solutions are not built for high volumes of distributed, disparate data, that is generated by various applications and external sources. Traditional MDM probabilistic matching doesn’t work well with siloed data sources. It misses connections, losing context, leads to decision-making inaccuracy, and leaves business value on the table. An ineffective MDM solution affects everything from customer experience to operational performance. Without on-demand visibility of holistic payment patterns, trends and risk, your team can’t make the right decisions quickly, compliance costs escalate, and you can’t increase coverage fast enough. Your data isn’t connected – so customers suffer fragmented experiences across channels, business lines and geographies. Attempts at personalized engagement fall short as these are based on partial, often outdated data. -
50
Centrifuge Analytics
Culmen Internal LLC
Centrifuge Analytics™ is a big data discovery technology that provides the power and flexibility to connect, visualize and collaborate without complex data integration, costly services or a data science degree. It combines sophisticated link-analysis, interactive visualizations and discovery features to dramatically simplify data pattern and connection recognition. - First and foremost, a fully integrated solution that empowers analysts to work with no IT support - Sophisticated link-analysis features such as pattern Identification, intelligent bundling and various unique visual interactive features - 100% Browser footprint ensures no client-side data retention that simplifies security and client administration Patent-pending server-side rendering engine enables highly scalable network graphs Agile data integration – No need to stage, warehouse or apply a fixed ontology Model-based analytics – Setup once and reuse – build upon the experience of more seasoned analystsStarting Price: Call
