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Top 27 Graph Databases
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Top 27 Graph Databases

Top 27 Graph Databases
4.9 (97.24%) 58 ratings

Many companies in the contemporary business environment deal with Big Data and need to utilize the right tools to manage large volumes of data. Companies are constantly facing extreme competition and the business world is constantly changing in terms of how businesses handle data. For this reason, businesses must find a way to leverage their data by using the best database technologies. They need database systems that can represent and visualize data in a simple and clear manner. Graphs are extremely powerful tools because they help people in the business world and other settings to understand datasets by representing data in a simplified form. With the right graph database, businesses can visualize their data in the form of graphs and manage it to improve their overall performance. Many organizations have embraced graph databases because they have realized the importance of this database technology.

Top Graph Databases : ArangoDB, Neoj, OrientDB, AllegroGraph, Ontotext GraphDB, Graph Story, Titan, Stardog, GraphBase, Dgraph, Oracle Spatial and Graph, HyperGraphDB, Blazegraph, Aster, Sparksee, VelocityGraph, Sqrrl Enterprise, IBM System G Native Store, Graph Engine, ThingSpan, Bitsy, Oracle NoSQL Database, Apache Giraph, FlockDB, InfoGrid, grapholytic, Weaver are some of the Top Graph Databases.

What are 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.

Graph databases are types of NoSQL databases that are based on graph theory or the graph data model. These databases comprise of nodes that represent entities and edges that represent relationships or connections between nodes. Each node has a unique identifier, outgoing and/or incoming edges, and properties or key-value pairs. Every edge has a unique identifier, properties, a starting node, and an ending node. Nodes and edges are sometimes tagged with labels that represent roles. Graph databases are useful in domains where entities and relationships are equally important. They assemble the simple concepts of nodes and relationships between nodes into connected structures allowing users to build models and map their problems. Graph database users can build simpler and easy-to-understand models that are difficult to build with other NoSQL databases and conventional relational databases. The expressive structure of a graph allows users to model all any scenario. There are many types of graph databases with different features. The best product will depend on your company’s needs and preferences.

What are Graph Databases

What are Graph Databases

  • Database Engine/Storage – Graph storage is one of the most important features of all graph databases. This feature allows database users to store information in the form of graphs. The database engine provides processing and indexing capabilities for quick storage, querying, indexing, and retrieval. Graphs databases with advanced indexing capabilities allow users to quickly retrieve graphical information from large databases.
  • Querying – This is an essential feature in all database management systems. Graph databases usually use the associated graph model and the simplest querying technique is known as the index-free adjacency. Query capabilities allow users to look for nodes, scan neighbouring nodes, retrieve edges, and retrieve attribute values. Users can also perform more complex queries.
  • Scalability/Partitioning/Sharding – Although it is difficult to scale graph data across multiple servers, it is possible to scale for large datasets, read performance, and write performance. The availability of this feature and scaling capabilities depend on the product you are using.
  • ACID Transactions – All databases systems have transaction processing capabilities. Graph databases include the tools needed to create, read, modify, and delete information. They also include features such as real-time analytics and reporting. Graph databases also implement ACID (Atomicity, Consistency, Isolation, and Durability) capabilities to ensure persistent, consistent, and complete transactions.

Some of the benefits include:

  • Managing large volumes of data without affecting performance.
  • Storing highly associative data.
  • The flexible model can accommodate change.
  • Agility – They align with the current practices and the changing business needs

Top Graph Databases

ArangoDB, Neoj, OrientDB, AllegroGraph, Ontotext GraphDB, Graph Story, Titan, Stardog, GraphBase, Dgraph, Oracle Spatial and Graph, HyperGraphDB, Blazegraph, Aster, Sparksee, VelocityGraph, Sqrrl Enterprise, IBM System G Native Store, Graph Engine, ThingSpan, Bitsy, Oracle NoSQL Database, Apache Giraph, FlockDB, InfoGrid, grapholytic, Weaver
Top Graph Databases
PAT Index™
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

1

ArangoDB

ArangoDB helps to arrange the data in a very creative and flexible way. The data can be stored as key or value pairs, graphs or documents and all of this can be accessed by just one query language. For safer option more than declarative models can be used in the query. The reason why users can combine different models and their features in one query is because ArangoDB uses the same core and same query language for all the data models. If a new product is being developed then every now and then new ideas are generated and the model…

Bottom Line

ArangoDB provides you with the opportunity of staying updated and keeping your product updated as well. It is not just a product of a single individual rather different teams make it possible for ArangoDB to be the success it really is.

7.6
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ArangoDB

2

Neoj

Neoj is an application which employs the application of graphs to give a detailed insight into a chunk of data. There are many connections inside a big data and neoj helps you to find the intertwining links between them with the help of its visually interactive graphs. A graph database helps you explore a huge piece of information in an astute manner through Neoj. The old conventional methods of fitting data into predefined tables are long gone. These methods have been dethroned by Neoj which promises an intuitive data model which can shape shift itself in minutes as the business…

Bottom Line

The Neoj graph database is superior to other non-native graph solutions for a number of reasons. Neoj4uses natives graph storage which gives the freedom to manage and store your data in a highly disciplined manner.

7.6
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Neoj

3

OrientDB

OrientDB features a 2nd generation distributed graph database that is unique, multi model graph database that offers flexibility for documents all in one product. It includes replication and sharding that can be used in most complex use cases and with an open source that is compatible with Apache 2 license. OrientDB works fast and capable of storing 220,000 records per second on most common hardware and supports schema less, full and mixed modes including SQL as one of the query language used. OrientDB provides safety in all confidential data that is present with the use of authentication, password and data-at-rest…

Bottom Line

OrientDB works fast and capable of storing 220,000 records per second on most common hardware and supports schema less, full and mixed modes including SQL as one of the query language used. OrientDB provides safety in all confidential data that is present with the use of authentication, password and data-at-rest encryption.

7.6
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OrientDB

4

AllegroGraph

AllegroGraph uses well-organized memory operations which are basically combined with a lot of disk storage so that maximum efficiency can be achieved. It supports SPARQL, RDFS++ and Prolog reasoning for various client requirements. The most highlighting new feature of AllegroGraph database is the 3D and multidimensional geospatial functionality. The data will not look flat on the screen rather it will have many facets which will provide with the opportunity of explaining the phenomenon in a better way. It is enabled with full and fast recoverability and there’s hardly ever a chance of losing the data. There is also a better…

Bottom Line

AllegroGraph basically provides services including vision building, rapid prototyping and proof-of-concept development, complete enterprise technology solution stack, best practices to maximize value from semantic technologies and new organizational skills required custom training.

7.6
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AllegroGraph

5

Ontotext GraphDB

Ontotext GraphDB is a semantic graph database that helps organizations manage, store and organize contents into a smart data. This NoSQL database handles huge amount of queries in real time. Using smart data management works on products and services information in a faster speed. By flawlessly exposing, mixing and sharing data in different platforms, smart data management is achieved as there would be detailed information when it comes to mapped relationships. OntotextGraphDB makes it easier to classify, reuse and combine information since data are stored in atomic facts. Updating and adding new data are easier to manage as well in…

Bottom Line

Ontotext GraphDB makes it easier to classify, reuse and combine information since data are stored in atomic facts. Updating and adding new data are easier to manage as well in this form of approach.In graph database, managing relationships are the key to a better system.

7.6
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Ontotext GraphDB

6

Graph Story

Graph Story can help get answers in real-time, scale cost-effectively, and without long-term contracts. Graph Story can help users be successful in building graph-powered application. Users can Get access to a proven and scalable option to manage complex, highly-connected data. Graph Story has technical experts and advanced tools to monitor and help optimize databases for optimal performance. Users talk to real human beings who built the platform. None of Graph Story plans artificially limit the amount of data users can store or request. No arbitrary caps on the number of nodes or relationships. It runs daily, weekly, and monthly hot…

Bottom Line

Graph Story can deploy where your servers already live: AWS, Azure, or Google Compute Engine, in any region.All of the plans include auth and access controls, 128 SSL for encryption in-transit and regular patch management.

7.6
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Graph Story

7

Titan

Titan is a graph database provider for better business data storage and querying graphs that may contain billions of nodes and edges. It can support multiple users that can access the graph database information real time and make updates and changes at the same time.Titan allows linear an elastic scalability for accommodating bigger amount of data as well as number of users that can execute updates on the graphs. Other features would be distribution and replication of data for better performance with multi-datacenter that provides high availability to unsure backups. It also comes with other storage backends such as Apache…

Bottom Line

Titan allows linear an elastic scalability for accommodating bigger amount of data as well as number of users that can execute updates on the graphs.

7.6
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7.2
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Titan

8

Stardog

Stardog provides more insight, faster and easier. It unifies enterprise data that is based on semantic graphs, schema alignment, data modeling, and deep reasoning. With smart graph database technology, doing query, searches, inference and data virtualization has never been easy and effective.The latest version of Stardog supports RDF graph data model, SPARQL query language, property graph model as well as Gremlin graph traversal language. Stardog’s High Availability clusters ensure that any failure will not affect the applications that depend on a single machine. Using clustered version can immediately resolve failures by automatically creating multiple copies of the service to make…

Bottom Line

Stardog’s High Availability clusters ensure that any failure will not affect the applications that depend on a single machine. Using clustered version can immediately resolve failures by automatically creating multiple copies of the service to make sure everything keeps running still.

7.6
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Stardog

9

GraphBase

GraphBase works like magic when it comes to handling complex data which needs to be converted into arranged form. GraphBase has always been used for handling large unprocessed data because it is the best when it comes to utility, performance and scalability. This graphical database can absolutely convert any data into the most sophisticated graphs ever seen. It has graph focused tools which arrange the data into an external graph and deliver it and then after all the manipulation and processing convert that graph into Java POJOs with a single line of code. With GraphBase perfect graph suitable for a…

Bottom Line

The graphical database can absolutely convert any data into the most sophisticated graphs ever seen. It has graph focused tools which arrange the data into an external graph and deliver it and then after all the manipulation and processing convert that graph into Java POJOs with a single line of code.

7.6
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GraphBase

10

Dgraph

Dgraph is an open source, scalable, distributed, highly available and fast graph database, designed from ground up to be run in production. Dgraph started with the idea that every startup should be able to have the same level of technology as run by big giants. Dgraph was designed from ground-up to allow data sharing, horizontal scalability, consistent replication, and a fast and distributed architecture. By building a truly robust piece of technology, Dgraph can have users run only one database, which allows arbitrarily complex queries while providing rock solid performance. The recent release of Dgraph is packed with new features…

Bottom Line

Dgraph can run complex distributed queries involving filters, string matching, pagination, sorting and geolocations blazingly fast.

7.6
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8.8
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Dgraph

11

Oracle Spatial and Graph

Oracle Spatial and Graph is one of the leading graphical databases that are available in the industry at the moment. It supports a wide range of geospatial data and can easily analyze any kind of land management and GIS without much difficulty. It also provides mobile location services, transportation and location-enabled business intelligence. Other services included in the Oracle Spatial and Graph are LiDAR analysis and sales territory management. Coming on to the features, the Oracle Locator which is a cost free feature of Oracle Database Standard and Enterprise Editions provides the user with fast processing, location query and analysis…

Bottom Line

Oracle Spatial and Graph uses Oracle Database 12c and its newest, most effective feature is the Oracle Database In-Memory which provides the user with the access to analytics and workload OLTP which delivers extremely efficient results as well as supports real-time analytics, business intelligence and reports.

7.6
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Oracle Spatial and Graph

12

HyperGraphDB

HyperGraphDB is an open source data storage mechanism based on the powerful directed hypergraphs. It provides with all the data modelling knowledge and has a lot of memory for large information. It is equipped with N-ary and out of box Java OO database. It offers with customizable indexing and storage management which is essential when working with graphical representation because an unprocessed and complex data constantly needs to be edited and modified. Another powerful feature is the extensible, dynamic database schema through custom typing which gives an altogether different look to the graphs and is fully transactional and multi-threaded so…

Bottom Line

HyperGraphDB finds its usage in server-side Java application, desktop Java application, Bioinformatics, Semantic web and network research.

7.6
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HyperGraphDB

13

Blazegraph

Blazegraph is a powerful graph database that offers flexibility in all linked data. Its scalable and high performance database supports the Blueprints and RDF/SPARQL APIs. Blazegraph can work on billions of edges on single machine and has high availability and scale out architecture. Blazegraph deployment mode offers three different features that can match a particular need of the user. The Single Server and Embedded deployment mode supports RDF/SPARQL and Apache TinkerPop APIs. It can support up to 50 billion edges using fast disk I/O with large CPU cores and generous amount of RAM. Blazegraph’s High Availability deployment mode uses shared-nothing…

Bottom Line

Blazegraph can work on billions of edges on single machine and has high availability and scale out architecture. Blazegraph deployment mode offers three different features that can match a particular need of the user. The Single Server and Embedded deployment mode supports RDF/SPARQL and Apache TinkerPop APIs.

7.6
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10
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Blazegraph

14

Aster

Aster is a revolutionary technology which promises to do big data analysis in lighting fast speeds with minimum resource outlays. This highly charged suite for analysis is the best choice for visually stunning and swift representations for SQL, map reduce as well as in detail graphical representations. Its massive parallel design helps to boost performance by carrying out loads, queries, backups, installs etc. in parallel for rapid insight discoveries. Another feature of this award winning analytical suite is that you can couple up multiple analytic engines of your own choice ( SQL-MR, SQL-GR, R and SQL) based on your own…

Bottom Line

Dynamic mix workload is another important feature of the Aster database which lets you maintain scalable performance in a heavy workload and a crowd of concurrent users. By using an analytic engine such as SQL during query runtime, the data from the hadoop can be used in the aster database where a large array of aster functions can be used to carry out complex data analysis and that too in bulk.

7.6
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Aster

15

Sparksee

Sparksee by Sparsity Technologies is the newest, most revolutionized product which is high-performance graphical database. It is known for making space and performance compatible with just a small effort and large outcome. It is available for .Net, C++, Python, Objective-C and Java. It is the first application that is available on both Android and iOS. Sparksee specializes in compressing large data into smaller representations which are easily to view. In every representation, values are viewed only once so that there isn’t any unnecessary repetition of numbers or figures. It provides direct access to operating systems which helps to avoid excess…

Bottom Line

Sparksee specializes in compressing large data into smaller representations which are easily to view. In every representation, values are viewed only once so that there isn’t any unnecessary repetition of numbers or figures.

7.6
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Sparksee

16

VelocityGraph

VelocityGraph is a graph database that offers the fastest and scalable database that a particular enterprise can take advantage in order to manage their business information well and effectively. It works on multiple computer platforms such as Windows 10 PC and Phone, Xbox, Xamarin iOS, Android and Linux.VelocityGraph can help save money and time while getting a data structure for most of your applications. With the huge amount of data a particular business may have, the memory that you are using may not be enough over the period of time. Using VelocityGraph saves the amount of memory needed without sacrificing…

Bottom Line

VelocityGraph provides an easy way on backing up a company’s database by putting them all in one local directory. Exporting and importing to and from JSON is also made possible.

7.6
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VelocityGraph

17

Sqrrl Enterprise

Sqrrl Enterprise is a security analytics company that helps organizations to target, hunt and disrupt cyber threats that will affect their business. In this day and age wherein technology is not only used for advancements but also for crimes, most organizations are prone to cyber threats and Sqrrl Enterprise is a tool that can be used to help stop it from happening.The program uses machine learning and hunts effectively the threats to avoid losses and damage to the organization. Sqrrl Enterprise reduces the attacker dwell time by detecting its behavior faster and by using fewer resources effectively. This gives the…

Bottom Line

Sqrrl Enterprise uses link analysis, UEBA or User and Entity Behavior Analytics as well as multi petabyte scalability capabilities into an incorporated solution. It facilitates proactive threat detection by analyzing different datasets available at a given time.

7.6
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Sqrrl Enterprise

18

IBM System G Native Store

IBM System G Native Store is a provider of graph database that handles different types of graphs such as property graphs and RDF like graphs while working on storage, analytics and visualization of the whole system. It offers both Scale Up features that use memory and storage of single machines while the Scale Out can distribute to multiple machines.IBM System G Native Store does not only offers unrelenting graph storage but also provides sequential, concurrent and distribute graph runtimes, C++ graph programming APIs, CLI command set, socket client, socket client GUI and visualization toolkits. IBM System G Native Store is…

Bottom Line

IBM System G Native Store is designed for efficient graph computing since the structure of data is optimized in multiple layers which included disk storage, graph specific file caching, optimized scheduler for concurrent access to the graph and others

7.6
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IBM System G Native Store

19

Graph Engine

Graph Engine is a distributed, in memory made with large graph processing engine with powerful RAM storage. This distributed RAM provides high performance key-value store over a group of machines. This makes users easily access the data in the system, do updates, necessary changes that needs to be done in order to have efficient relationships or connections in the graph database. Graph Engine’s is capable of exploring data in a speedy manner and distributed parallel computing due to its large graph processing platform. Graph Engine supports low-latency online query as well as high-thought output offline analytics regardless a billion-node sized…

Bottom Line

Graph Engine’s is capable of exploring data in a speedy manner and distributed parallel computing due to its large graph processing platform. Graph Engine supports low-latency online query as well as high-thought output offline analytics regardless a billion-node sized graphs.

7.6
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Graph Engine

20

ThingSpan

ThingSpan can help to find the way out of any graphical trouble that can come across. It is a purpose-built, scalable graph analytics platform that integrates with Apache Spark and HDFS (Hadoof Distributed File System). If the graph is very large and is distributed over a very complex data then ThingSpan can help to navigate the path and follow queries to find the right way. It supports parallel pattern finding and predictive analytics in combination with Spark components such as MLlib, Graph X and Spark SQL. With the help of ThingSpan a single logical view of all the data representation…

Bottom Line

ThingSpan can help to navigate the path and follow queries to find the right way. It supports parallel pattern finding and predictive analytics in combination with Spark components such as MLlib, Graph X and Spark SQL. With the help of ThingSpan a single logical view of all the data representation can be achieved.

7.6
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ThingSpan

21

Bitsy

Bitsy is a tiny yet fast, embeddable, high storage DB that implements the Blueprints API. It supports the basic features such as key indices and threaded transactions and efficiently implements positive concurrency controls. It stores the data serial wise using the Jackson JSON Processor. The data can be recovered and chances of losing it due to power failures are null. Online backup is also provided through JMX interface. The main features of Bitsy are very interesting and of course helpful. It follows optimistic concurrency which uses the best practices to retry transactions. Furthermore with the help of Bitsy, algorithms can…

Bottom Line

The main features of Bitsy are very interesting and of course helpful. It follows optimistic concurrency which uses the best practices to retry transactions.

7.6
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Bitsy

22

Oracle NoSQL Database

Oracle NoSQL Database provides a reliable and flexible data management of configurable set of nodes. This particular scalable and NoSQL database can be highly trusted when it comes to businesses managing all their data to ensure effectivity.Using graph database uses nodes and edges to represent an entity that establishes relationship and connections. Oracle NoSQL Database, a sharded system, allocates data uniformly across other shards in the groups. Storage nodes are then replicated to establish high availability to maintain consistency.Oracle NoSQL Database is integrated with different Oracle and open source applications to work on development and operation of big data applications…

Bottom Line

Oracle NoSQL Database is integrated with different Oracle and open source applications to work on development and operation of big data applications that most organizations have nowadays.

7.6
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5.5
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Oracle NoSQL Database

23

Apache Giraph

Apache Giraph is an iterative graph processing system built for high scalability. For example, it is currently used at Facebook to analyze the social graph formed by users and their connections. Giraph originated as the open-source counterpart to Pregel, the graph processing architecture developed at Google and described in a 2010 paper. Both systems are inspired by the Bulk Synchronous Parallel model of distributed computation introduced by Leslie Valiant. Giraph adds several features beyond the basic Pregel model, including master computation, sharded aggregators, edge-oriented input, out-of-core computation, and more. With a steady development cycle and a growing community of users…

Bottom Line

Giraph adds several features beyond the basic Pregel model, including master computation, sharded aggregators, edge-oriented input, out-of-core computation, and more. With a steady development cycle and a growing community of users worldwide,

7.6
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Apache Giraph

24

FlockDB

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. FlockDB is much simpler than other graph databases such as neo4j because it tries to solve fewer problems. It scales horizontally and is designed for on-line, low-latency, high throughput environments such as web-sites. Twitter uses FlockDB to store social graphs (who follows whom, who blocks whom) and secondary indices. As…

Bottom Line

FlockDB is much simpler than other graph databases such as neo4j because it tries to solve fewer problems. It scales horizontally and is designed for on-line, low-latency, high throughput environments such as web-sites.

7.6
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4.9
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FlockDB

25

InfoGrid

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. As powerful as InfoGrid is, it derives much of its power from just a handful of core ideas. Users can develop perfectly fine InfoGrid applications with applying just the first two ideas. But the more of these code ideas users apply, the more value users get out of InfoGrid. All information in InfoGrid is represented as objects, called MeshObjects. Each…

Bottom Line

InfoGrid is open source, and is being developed in Java as a set of projects.Provides an abstract common interface to storage technologies such as SQL databases and distributed NoSQL hashtables.

7.6
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InfoGrid

26

grapholytic

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 is the only database with 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. Combining In-Memory Computation and Low Cost storage for enterprise computation scenarios. Users do not want to write lines and lines of SQL code to find the nearest way between two places. Users do not want to execute dozens…

Bottom Line

The only database with automatic based distribution of graphs to cluster nodes using advanced machine learning algorithms.

7.6
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grapholytic

27

Weaver

Weaver Alpha is a scalable, fast, consistent graph store. 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. For example, users can create a user (node) and a link (edge) of a specified type in a single transaction. Users can also query a user's friends-of-friends in another transaction. Weaver dynamically migrates portions of the graph across shards to maintain graph locality and minimize communication. Weaver also enables users to cache results of graph computation at the nodes. Weaver has a…

Bottom Line

Weaver enables users to execute transactional graph updates and queries through a simple python API.

7.6
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Weaver

3 Reviews
  • Reginald
    November 14, 2014 at 10:53 am

    ADDITIONAL INFORMATION
    It’s a good starting point, but maybe you’d like to refine this list… I am a Microsoft guy, but I don’t find any reason to rank first a product like Horton which is still in MS Research Labs, having no production or customer references. Moreover, another mature player is missing here: OrientDB, which instead has a reasonable and convincing customers’ list…

  • January 21, 2015 at 12:07 pm

    ADDITIONAL INFORMATION
    Check out Graph Story. We offer fast, secure and affordable access to graph databases-as-a-service and make them even easier to use through our customized API.

  • João Polo
    November 22, 2017 at 1:59 pm

    ADDITIONAL INFORMATION
    Hi… The HiperGraphDB was with a wrong title “ArangoDB” in the list

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