AllegroGraph System Properties

• AllegroGraph is 100 percent ACID, supporting Transactions: Commit, Rollback, and Checkpointing.

• Triple Level Security with Security Filters

• Gruff - Graph Visualization, Generate SPARQL and Prolog queries visually.

• AllegroGraph server can be scripted using the JavaScript API

• Full and Fast Recoverability

• 100% Read Concurrency, Near Full Write Concurrency

• Online Backups, Point-in-Time Recovery, Replication, Warm Standby

• Dynamic and Automatic Indexing – All committed triples are always indexed (7 indices)

• Advanced Text Indexing – Text indexing per predicate

• SOLR and MongoDB Integration

• SPIN support (SPARQL Inferencing Notation). The SPIN API allows you to define a function in terms of a SPARQL query and then call that function in other SPARQL queries. These SPIN functions can appear in FILTERs and can also be used to compute values in assignment and select expressions.

• All Clients based on REST Protocol – Java Sesame, Java Jena, Python, C#, Clojure, Perl, Ruby, Scala, and Lisp clients

• Completely multi-processing based (SMP) – Automatic Resource Management for all processors and disks, and optimized memory use. See the performance tuning guide here, and server configuration guide here

• Column-based compression of indices – reduced paging, better performance

• Cloud-Hosted AllegroGraph - Amazon EC2

• JavaScript-based interface (JIG) for general graph traversal

​​AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and languages like JavaScript. AllegroGraph uses sorted quintuple indices that will index every primary and non-primary field. So users never have to worry about whether a certain field is indexed or not. There are 6 default indices that are in general sufficient for set based query index to execute almost any adhoc query.

One of the most powerful features of AllegroGraph is that it is possible to mix Geospatial, Temporal, Social Network Analytics, and Reasoning, all in the same query (SPARQL or Prolog). An example:

“Find whether the most important friend of Sonya (using the SNA centrality statistic) made a payment within a 100 miles of Rotterdam, NY (using geospatial) within the last 10 years (temporal).” 

This would be impossible in any other graph database, RDF store, document store or Hadoop like solution in such a concise way.

• AllegroGraph - Combines Geospatial, Temporal, and SNA into a single “Golden” query.

• W3C standards based query language and data format via SPARQL and RDF.

• ​GRUFF - Data explorer, Graph Visualization, Graphical Query Generation

• AllegroGraph has a built-in Rule Based System on top of an ISO compliant Prolog.  Users can write rules and stored procedures in Prolog and make them available to other rules and/or users.

• ​Triple Level Security
  

• True Durability in AllegroGraph - Many RDF and Graph DBMS systems to NOT write transaction logs for every transaciton, so in essence these databases are NOT durable.   Experiment - Perform multiple commits per second and run monitor "vmstat 1" to look at blocks in and out (column - io bi/bo).​

Bloor Research Positions Franz’s AllegroGraph as a ‘Champion’ and Highest Ranked in Graph Database Market
28 March 2017

AllegroGraph v6.2 - Now Available
21 February 2017

#AllegroGraph News - February 2017
1 February 2017

#AllegroGraph News - October 2016
4 October 2016

The Power of Cognitive Probability Graphs
20 June 2016