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Transcript of Titan:db
"Titan is designed to support the processing of graphs so large that they require storage and computational capacities beyond what a single machine can provide"
please ask questions after the practical example
(HBase, Cassandra, ElasticSearch,...)
(Rexster, Gremlin, Blueprints,...)
easy to install
Graph derivation (
cousin-graph from father and brother edges
Titan focuses on effective
. Therefore persistence layer utilizes
local server mode
remote server mode
remote server with rexster
Also other 3rd party adapters
Supports indexing on persisted data
Titan can store up to 2^60 edges and half as many vertices
Graph or vertex-centric indices cannot be removed, only disabled.
Batch loading in Titan is currently slower than batch loading modes provided by single machine databases
Single machine (same JVM)
Graph statistics (
counting vertices, number of friends, ...
originates from project
breaks down graph to
adjacency list items
then processes units
Titan-Hadoop only supports
property values (whereas the Blueprints API supports objects)
A vertex and it's incident edges must fit into the memory. Therefore
can cause overflow
Index string properties (
-based indices (within a circle)
Numeric range (age between 18-25)
Provides standardized API for graphs.
: server that encapsulated Titan and provides REST access graphs
subset of Titan API
: API for graph traversals
: graph visualization and web-based gremlin shell
download from https://github.com/thinkaurelius/titan/wiki/Downloads
This starts Cassandra, Titan and Rexster in separate processes (all contained in the downloaded archive)
launch doghouse and play :)
Property graph (same as Neo4j)
Adjacency list (list of node-neighbors)
By default random partitioning
leads to ineffective traversals
can be replaced with own explicit partitioning
Virtual partitions (on the same machine)
the number of partitions cannot be changed without reloading the graph
Edge cut, Vertex cut