GraphBase is a second generation Graph Database Management System (DBMS). Built for 21st Century data problems, GraphBase is a game-changer when it comes to handling large, complex data structures.
Until now, the Relational Database Management System (or RDBMS) was the application of choice for managing structured data. Modern large enterprise and web-scale applications with complex structures however, are a challenge for the RDBMS - in modelling utility, performance and scalability.
GraphBase makes massive, highly-structured data stores possible because it was built from scratch to manage large graphs. GraphBase is not tacked on top of an RDBMS, OODBMS or other early technology. Compare these features...
GraphBase power comes from its performance, its simplicity, its versatility and its unique tools.
Getting the most from today's data is not just about handling scale. It's about data integration and interoperability. It's about data migration, data-sharing and portability. It's about database schemas the size of a wall. It's about complex data-based environmental, economic, medical and biological models. These are complex problems - Complex Data is a bigger problem than Big Data.
That's why the idea of a Graph Database is so enticing. Put your data anywhere in your database, connect it to anything, create the most complex of data models and change them at any time without having to migrate your data. It's the Holy Grail of data management and it's why tens of thousands of Property Graph and RDF database implimentations are downloaded every month.
But only a handful of these downloads ever produce anything useful. Why? The power to model data problems is not matched by an equivalent power to query them and to build useful applications using them. What looks initially like a panacea for data complexity quickly becomes a headache.
GraphBase is different. It dramatically simplifies working with graph-structured data because it's the only database that lets you think about graphs - by using graphs. And it comes with query functionality designed for graphs.
Forget using half-baked SQL copies to query your data, GraphBase queries recognise the fact that most of what you might normally put in an SQL statement has already been declared within your super-graph. A simple query construct lets you create "bounds" for your query by specifying interactions between simultaneous graph traversals. It's like shining multiple beams of light into your graph and bringing back the overlaps.
It's a surprisingly powerful query paradigm, and when you need even more expressiveness to slice and dice your data you can package a Java "handler" with your query. Java is a language more powerful than any provided with a database - and it's a language you probably already know.
What's more, you can throw out those bloated object-database mapping frameworks - GraphBase lets you turn a graph into objects with a single line of code.
GraphBase comes with visual tools that further simplify working with graphs. Tools that let you visualise your graphs and queries - and that let you use drag and drop to create them.
A graph is a powerful way to represent data. But by the time you've broken your data problem up into all of its "connected" pieces, it can be difficult to keep an understanding of those pieces in your head.
An RDBMS gives you rows, columns and tables. A Document store gives you... documents. With first-generation Graph Databases you get to make hugely-complex spaghetti-like structures - but you're forced to think about and work with your data at the individual vertex level.
GraphBase dramatically simplifies the management of graph-structured data with its "graph-focused" tools paradigm. In GraphBase, the graph is the unit-of-work - not the vertex.
It's a simple, elegant and productive way to manage graph data.
GraphBase is the only Database Management System engineered for AI support.
What is Artificial Intelligence or AI? We create Artificial Intelligence when we give a machine the capacity to turn data, observations and communication into knowledge - and then use that knowledge to perform useful tasks. Like a human does.
Deep Learning is getting all the press lately, but there's much more to AI than Deep Neural Networks and other forms of Machine Learning. Central to any AI effort is the need to represent, manage and use knowledge.
GraphBase manages and stores knowledge in the form of facts. These are concepts, values and the relationships between them. Included are semantic structures to support natural language processing and sophisticated mapping of words to concepts.
But unlike any other DBMS, GraphBase also stores the “how to” - what in humans we call “procedural memory”. Procedural Java “agents” can reside in-graph and are aware of their context, and GraphBase can also encapsulate, feed, run and provide insight into pre-trained “black box” Deep Neural Networks (DNNs).
There is no consensus as to what the ideal graph structure is for storing data. It depends on the nature of the data and the purposes for which it's used. Triplestore, Property Graph, HyperGraph... they all have their strengths and their problems.
Your ideal structure may contain features of all of these graph types, and more besides. With GraphBase Enterprise Edition you can configure light-weight primitives to give you the structure you need. Even our simplified Agility Edition gives greater data-modelling power than any other DBMS and any other Graph Database solution.
Enterprise Edition also lets you configure how your graph is indexed - including support for subsumption. Take a look at the Community Semantic Framework to get a sense for how this works.
GraphBase lets you store objects directly within vertices. Enterprise configurations allow these objects to become first-class citizens within GraphBase, and "Agent" mechanisms allow their logic to be distributed amongst GraphBase server Nodes.
You can also embed simple high-performance data structures within graph vertices to handle high volume real-time and "big data" problems. This is a strategy used to dramatic effect by our i6 Real-Time Intelligence product.
Versatile Transaction Control and Security
Agility Edition enforces full transaction (ACID) semantics. These, however, can create significant performance issues - particularly across a distributed data store. That's why most new NoSQL database products don't support them.
The GraphBase Enterprise Security Framework allows you to specify which parts of your GraphBase graph need locks, rollback and other transactional support - and which parts don't. Get ACID where it matters, Eventual Consistency where it doesn't - and the best possible performance at all times.
The Security Framework also gives you fine-grained control over who can see and modify which parts of your GraphBase graph.
Architecture for this Decade
Existing DBMS products were engineered in a time when processing, memory, storage were expensive and more-limited in their capability. GraphBase. on the other hand, has been built for modern multiprocessor servers and is designed to take maximum advantage of big RAM and high-speed storage.
A single low-cost 1RU GraphBase server can handle billions of queries and updates per day against a graph of one billion vertices and 100 billion arcs. That's FaceBook on a single pizza box.
The secret to this performance is sophisticated thread management, and compact structures that allow as much of the graph as possible to remain in memory. GraphBase also carries a host of unique innovations. Arc heuristics, for example, enable graph traversals and query speed 10 to 100 times faster than other Graph Database implimentations.
Designed for Cloud
Anyone who's worked with graph structures, knows that partitioning or "sharding" graph data is a difficult problem. But sometimes it's not possible to keep your entire graph on one server. At other times it makes sense to distribute your graph so that processing can also be distributed.
GraphBase is designed to be distributed in true "Cloud" fashion. Each server "Node" is autonomous, but aware of it's obligations to it's peers. Communication between nodes is asynchronous, and sophisticated cacheing and queueing strategies allow a group of GraphBase Nodes to accommodate the latency and bandwith issues of a geographically-distributed cloud.
A true Graph Database keeps its arcs close - a strategy refered-to as index-free adjacency. Unlike some competing products, GraphBase arcs are encapsulated within each vertex and go wherever that vertex goes. It's an architecture that greatly simplifies data distribution.
The Only Graph DBMS for Big Data
Graphs are great for simplifying and managing complex data structures, but they're the wrong tool for handling the high-volume kludge of classic "big data" problems.
GraphBase lets you embed simple, compressed, highly-efficent, vertex-focused data stores. Think "all the phonecalls or transactions for a person". It's strategy so effective that it permits a level of real-time big data analysis that's difficult - and expensive - to achieve with any other technology.
GraphBase Enterprise Edition is the ultimate tool for solving large and complex data problems. Use it for your biggest data challenges...
GraphBase Enterprise Edition gives you features that you just won't find in other NoSQL and Graph Databases. Features like...
Enterprise Edition gives you under-the-hood access to GraphBase. With it you can tune...
So that you can make the most of this access, we give you ten hours of high-level consultation with each GraphBase Enterprise Edition annual subscription.
Our Enterprise Beta Program includes 100 hours of professional services per license in support of your installation. This program will be strictly limited, so please register below if you'd like to discuss being part of it. Be sure to use your company or institution e-mail address.