Top 31 Graph Databases
Top 31 Graph Databases : A graph database is based on graph theory, uses nodes, properties, and edges and provides index-free adjacency. These database uses graph structures with nodes, edges, and properties to represent and store data. Every element contains a direct pointer to its adjacent elements and no index lookups are necessary in a graph database. Neo4j, AllegroGraph, Oracle Spatial and Graph, Teradata Aster, ArangoDB, Graphbase, ThingSpan, Bitsy, HyperGraphDB, DEX/Sparksee, Titan, VelocityGraph, InfoGrid, Oracle NoSQL Database, OrientDB, Blazegraph, Weaver, Stardog, Sqrrl Enterprise, GraphDB, MapGraph, IBM System G Native Store, VertexDB, Cayley, Graph Engine, FlockDB, grapholytic, Dgraph, Apache Giraph, Graph Story and Horton are some of the top graph databases in no particular order.
Top Graph Databases
Neo4j, AllegroGraph, Oracle Spatial and Graph, Teradata Aster, ArangoDB, Graphbase, ThingSpan, Bitsy, HyperGraphDB, DEX/Sparksee, Titan, VelocityGraph, InfoGrid, Oracle NoSQL Database, OrientDB, Blazegraph, Weaver, Stardog, Sqrrl Enterprise, GraphDB, MapGraph, IBM System G Native Store, VertexDB, Cayley, Graph Engine, FlockDB, grapholytic, Dgraph, Apache Giraph, Graph Story and Horton.
Neo4j is a native graph database, designed to store and process graphs from bottom to top. This is an embedded, disk-based, fully transactional Java persistence engine that stores data structured in graphs rather than in tables.Neo4j speeds write throughput significantly across the board, as much as 100 times in certain cases to benefit highly concurrent applications while leveraging available hardware much more efficiently. This is achieved through faster buffering of updates, and a new unified transaction log that now serves both the graph and its indexes.Neo4j is an open-source graph database, implemented in Java.Neo4j delivers the lightning-fast read and write performance you need, while still protecting your data integrity. It is the only enterprise-strength graph database that combines native graph storage, scalable architecture optimized for speed, and ACID compliance to ensure predictability of relationship-based queries.
Dataiku DSS is the collaborative data science platform that enables teams to explore, prototype, build, and deliver their own data products more efficiently. Dataiku DSS provides an interactive visual interface where they can point, click, and build or use languages like SQL to data wrangle, model, easily re-run workflows, visualize results, and get up-to-date insights on demand. Dataiku DSS provides tools to draft data preparation and modelisation in seconds, that wish to leverage their favorite ML libraries (scikitlearn, R, MLlib, H2O, and so on), and that rely on automating their work in a completely customizable interface. Data Ops.
AllegroGraph is a modern, high-performance, persistent graph database. AllegroGraph uses efficient memory utilization in combination with disk-based storage, enabling it to scale to billions of quads while maintaining superior performance. AllegroGraph supports SPARQL, RDFS++, and Prolog reasoning from numerous client applications. AllegroGraph is designed to store RDF triples, a standard format for Linked Data. A custom browser, Gruff, is available for viewing the graph.
3.Oracle Spatial and Graph
Oracle Spatial and Graph supports a full range of geospatial data and analytics for land management and GIS, mobile location services, sales territory management, transportation, LiDAR analysis and location-enabled Business Intelligence. The graph features include RDF graphs for applications ranging from semantic data integration to social network analysis to linked open data and network graphs used in transportation, utilities, energy and telcos and drive-time analysis for sales and marketing applications.
4. Teradata Aster
Teradata Aster is a high performance, multi-purpose, highly scalable and extensible MPP database incorporating patented engines supporting native SQL, MapReduce and Graph data storage and manipulation. An extensive set of analytical function libraries and data visualization capabilities are also provided. The Aster Management Console makes it easy to conﬁgure, manage and monitor data, applications and infrastructure. The graphical interface includes summary dashboards, graphical views of query and process execution.
Graphbase is a customizable, distributed, small-footprint graph store with a rich tool set. GraphBase makes massive, highly-structured data stores possible because it was built from scratch to manage large graphs. GraphBase features include tiny memory and storage footprint, distributable – out of the box, built-in support for traversal heuristics and graph-based transactions.
Objectivity’s ThingSpan is a purpose-built, massively scalable graph analytics platform that leverages the open source stack by natively integrating with Apache Spark and the Hadoop Distributed File System (HDFS). It provides ultra-fast navigation and pathfinding queries against huge distributed graphs.
Bitsy is a small, fast, embeddable, durable in-memory graph database that implements the Blueprints API. Features include support for most Blueprints features including key indices and threaded transactions, ACID guarantees on transactions, designed for multi-threaded OLTP applications, implements optimistic concurrency control, data stored in readable text files and serialization using the Jackson JSON processor.
HyperGraphDB is an open source data storage mechanism based on directed hypergraphs. This can be used as an embedded object-oriented database for Java projects of all sizes or a graph database or a (non-SQL) relational database. Features include powerful data modeling and knowledge representation, graph-oriented storage, N-ary, higher order relationships (edges) between graph nodes, graph traversals and relational-style queries, customizable indexing and extensible, dynamic DB schema through custom typing.
DEX/Sparksee is a high performance and scalable graph database management system . The main characteristics is its query performance for the retrieval & exploration of large networks. Sparksee 5 mobile is the first graph database for mobile devices. Sparksee makes space and performance compatible with a small footprint and a fast analysis of large networks. SparkseeIt is natively available for .Net, C++, Python, Objective-C and Java, and covers the whole spectrum of Operating Systems.
Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Features include elastic and linear scalability for a growing data and user base, data distribution and replication for performance and fault tolerance, multi-datacenter high availability and hot backups and support for ACID and eventual consistency.
VelocityGraph is an open source C# .NET hybrid NoSQL Graph Database and Object Database that can be Embedded/Distributed. Features include scalable smart caching enables millions of database to be used without running out of memory. High Performance objects are created the same way transient objects are and are made persistent efficiently when requested, persistence does not change the object, just adds an object identifier.
InfoGrid is a Web Graph Database with a many additional software components that make the development of REST-ful web applications on a graph foundation easy. InfoGrid is open source, and is being developed in Java as a set of projects. InfoGrid provides valuable higher-level services than JEE Application Servers do themselves. Applications have a choice in the persistence layer, they can write to relational databases, just like in a RDBMS-centric architecture, but can also write to grid technology, or other NoSQL Stores. InfoGrid provides a common abstraction layer.
14. Oracle NoSQL Database
RDF Graph for Oracle NoSQL Database is a feature of Enterprise Edition providing W3C RDF graph capabilities in NoSQL Database.The Oracle NoSQL Database is a distributed key-value database. It is designed to provide highly reliable, scalable and available data storage across a configurable set of systems that function as storage nodes. Data is stored as key-value pairs, which are written to particular storage node(s), based on the hashed value of the primary key
OrientDB is a 2nd Generation Distributed Graph Database with the flexibility of Documents in one product with an Open Source commercial friendly license. OrientDB is fast and can store 220,000 records per second on common hardware.OrientDB supports schema-less, schema-full and schema-mixed modes and has a strong security profiling system based on user and roles and supports SQL amongst the query languages.
Blazegraph is specifically designed to support big graphs offering both Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop, blueprints, vertex-centric) APIs. It features robust, scalable, fault-tolerant, enterprise-class storage and query and high-availability with online backup, failover and self-healing.
Weaver is a distributed graph store that provides horizontal scalability, high-performance, and strong consistency. Weaver enables users to execute transactional graph updates and queries through a simple python API
Stardog is a semantic graph database, implemented in Java. It provides support for RDF and all OWL 2 profiles providing extensive reasoning capabilities and uses SPARQL as a query language
Sqrrl Enterprise enables organizations to ingest, secure, connect, and analyze massive amounts of structured, semi-structured, and unstructured data. Sqrrl Enterprise stack is a graph-oriented database, layered on top of Apache Hadoop.
GraphDB is a leading RDF Triplestore and graph database, that can perform semantic inferencing at scale allowing users to create new semantic facts from existing facts. GraphDB handles massive loads, queries and inferencing in real time.
MapGraph is Massively Parallel Graph processing on GPUs. The MapGraph API makes it easy to develop high performance graph analytics on GPUs.
22.IBM System G Native Store
IBM System G Native Store provides an efficient graph data store solution that can handle various graphs, property graphs, and RDF-like graphs, in terms of storage, analytics, and visualization.
IBM System G Native Store
VertexDB is a high performance graph database server that supports automatic garbage collection.Vertex is built on libevent and tokyocabinet. It uses HTTP as it’s communication protocol and JSON as it’s response data format. It’s BSD licensed and was written by Steve Dekorte and Rich Collins.
Cayley is an open-source graph inspired by the graph database behind Freebase and Google’s Knowledge Graph.Features include RESTful API, built-in query editor and visualizer, multiple query languages, plays well with multiple backend stores, modular design; easy to extend with new languages and backends and good test coverage.
Graph Engine (GE) is a distributed, in-memory, large graph processing engine, underpinned by a strongly-typed RAM store and a general computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set.
FlockDB is a distributed graph database for storing adjancency lists, with goals of supporting a high rate of add/update/remove operations, potientially complex set arithmetic queries, paging through query result sets containing millions of entries, ability to “archive” and later restore archived edges, horizontal scaling including replication and online data migration.
grapholytic by MIOsoft is the leading approach to get the best results out of the combination of Graph DB and highly scalable object database architecture. It provides automatic based distribution of graphs to cluster nodes using advanced machine learning algorithms. No Limits for scalability. Binding Data to CPU power: enabling parallel processing and advanced performance for analytical processing and combining In-Memory Computation and Low Cost storage for enterprise computation scenarios.
Dgraph is a Scalable, Distributed, Low Latency, High Throughput Graph Database. Dgraph’s goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON.
Apache Giraph is an iterative graph processing system built for high scalability.It is currently used at Facebook to analyze the social graph formed by users and their connections Giraph adds several features beyond the basic Pregel model, including master computation, sharded aggregators, edge-oriented input, out-of-core computation, and more.
Graph Story offers fast, secure and affordable access to graph databases-as-a-service and makes them even easier to use through our customized API.
Horton is a research project in the eXtreme Computing Group to enable querying large distributed graphs. It consists of a graph library built on top on Orleans that targets hosting large graphs in a data center. The library provides a querying interface to search the graph for matching paths.
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