Elastic Brings Real-Time Graph Analytics to the Elastic Stack
(Thomson Reuters ONE) -
A New Way to Explore Relationships That Live in Your Data Using Relevance as a
Guide
MOUNTAIN VIEW, CA and AMSTERDAM, THE NETHERLANDS--(Marketwired - Mar 30, 2016) -
Elastic today unveiled Graph, a new extension for Elasticsearch and Kibana that
allows anyone to uncover, understand, and explore the relationships that live in
their data. By combining the speed and relevance-ranking of search with graph
exploration, Graph opens up a whole host of new use-cases with the Elastic
Stack.
"We built Graph to help you ask new types of questions about the data you store
in Elasticsearch," said Steve Kearns, Sr. Director of Product Management at
Elastic. "By looking at the relationships in your data through the lens of
relevance, it becomes easy to answer questions that previously would involve
multiple systems, batch jobs or machine learning."
Graph Enables New Use Cases for the Elastic Stack
When you store data in Elasticsearch -- products, users, documents, logs -- this
data often contains references or properties that represent connections between
objects, entities, people, or machines. The best way to explore these
connections is to see them, which Graph provides via a Kibana plugin. Like
everything at Elastic, this UI is built on a simple, but powerful API that
leverages Elastic's deep experience in relevance ranking to surface the most
meaningful connections that live in your data. This unique approach to graph
exploration opens a wide range of new use-cases for the Elastic Stack, without
requiring new index formats, by allowing users to query their existing data in
new ways.
Graph makes it easy to answer complex questions and address use-cases such as
behavioral analysis, fraud, cybersecurity, drug discovery, personalized
medicine, and to build personalized recommendations based on continuous real-
time data. Graph automatically identifies the most important connections,
separating the signal from the noise by employing relevance ranking specific to
each query. Because it is built on Elasticsearch, Graph benefits from high
scalability and near-real-time data availability, enabling answers that evolve
as your data changes.
Graph Brings Relevance to Relationship Exploration
When data is added to Elasticsearch, the indexing process tracks and counts the
values in each field of the document, updates global frequencies, and prepares
the data for a wide range of queries. These statistics are used to perform
relevance ranking for search and efficiently summarize the data in Elasticsearch
aggregations. With Graph, the Elastic Stack uses these statistics in new ways --
first to identify relationships within and across sets of documents, and then to
prioritize the most relevant relationships for the given query.
In contrast, traditional graph techniques are based on a simple count of the
frequency of a given relationship. This approach has the drawback that elements
with the most connections -- the Shawshank Redemption in movie recommendation
data or Starbucks in credit card purchase data -- are returned as the most
important. With Graph in Elasticsearch, relevance is calculated by correlating
the significance of each relationship in comparison to global averages, bringing
back the important results, and avoiding frequent connections.
"Graph is an excellent example of the limitless possibilities within our
products and how we strive to make it as easy as possible for our users to
leverage the power of the Elastic Stack," said Shay Banon, Co-Founder and CTO of
Elastic. "I am proud to see our company continue to innovate, and I can't wait
to see the new ways in which our customers will adopt Graph to solve really
challenging problems and use cases."
Learn More
* Graph Product Page
* Watch the Graph webinar
About Elastic
Elastic is the world's leading software provider for making structured and
unstructured data usable in real-time for use cases like search, logging, and
analytics. Founded in 2012 by the people behind the Elasticsearch, Kibana,
Logstash, and Beats open source projects, the Elastic Stack, X-Pack and Elastic
Cloud have had more than 50 million cumulative downloads to date. Elastic is
backed by Benchmark Capital, Index Ventures, and NEA with headquarters in
Amsterdam and Mountain View, California, and offices and employees around the
world. To learn more, visit www.elastic.co.
Media Contacts
Michael Lindenberger
Reidy Communications for Elastic
Michael(at)reidycommunications.com
(415) 531-1449
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other applicable laws; and
(ii) they are solely responsible for the content, accuracy and
originality of the information contained therein.
Source: Elastic via GlobeNewswire
[HUG#1998093]
Unternehmensinformation / Kurzprofil:
Datum: 30.03.2016 - 15:00 Uhr
Sprache: Deutsch
News-ID 460694
Anzahl Zeichen: 5515
contact information:
Town:
Mountain View
Kategorie:
Business News
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