Enterprises in many industries have struggled with numerous graph-related challenges as they work to unlock real value from connected data. These challenges include an inability to support large data volumes, slow query performance, and lack of flexibility with existing business intelligence (BI) tools.
To address these concerns, graph analytics leader TigerGraph has released a new benchmark report which demonstrates the technology is capable of running BI queries fast, returning results in a few minutes or less even across a data set of significant size.
In this benchmark, TigerGraph’s powerful graph analytics software was put to the test using the respected Linked Data Benchmark Council (LDBC) Social Network Benchmark (SNB) Scale Factor 30k data set, which features 36TB of raw data with 73 billion vertices and 534 billion edges. This was the first time a graph database has been tested at this scale.
This new study clearly demonstrates that a graph database has the ability to handle a big graph workload in a real production environment, where tens of terabytes of connected data with hourly or daily incremental updates is the norm.
The full report can be downloaded here.
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