Expanding Elastic: Learn how anyone can leverage heterogeneous compute to extend and accelerate Elasticsearch The document discusses how Ryft provides solutions to leverage powerful FPGA- and x86-based heterogeneous compute resources to gain immediate insight from data in Elasticsearch without indexing or data preparation latency. Ryft can accelerate workflows, speed search and analysis across unstructured data with no transformation needed, and increase the power of edit distance searches for fuzzy matching beyond a distance of 2. Ryft offers flexible deployment on-premise, in the cloud, or in hybrid environments to extend the capabilities of Elasticsearch.

1. Expanding Elastic:
Learn how anyone can leverage heterogeneous compute
to extend and accelerate Elasticsearch
Pat McGarry, Vice President of Engineering
Al Leyva, Director of Product Management for Analytics Integration
Ryft
March 7, 2017
@Ryft

2. Analytics at the Speed of Your Business
 Challenges:
 Exponential data growth
 Traditional text searching is
hindered with complex
indexing and transformation
requirements
 Answers are delayed as
legacy architectures require
hours or days to find insights
Solutions:
 Deploy heterogeneous
compute on-premise, hybrid
or in the cloud
 Abstract away the
complexities of powerful
FPGA-based compute
technology
 Real-time insights with no
indexing or data preparation
latency
Fast data growth is creating the largest business threats & opportunities since the
Internet

3. Accelerate and Extend Elasticsearch with Ryft
Leverage powerful FPGA- and x86-based heterogeneous compute resources to
gain immediate insight without indexing
Reduce need for data indexing and transformation, accelerate searches and extend
Elasticsearch capabilities to:
 Accelerate workflows with the ability to deploy pre-index and post-index
searches
 Speed search and analysis across unstructured data and JSON, XML, LOGs,
CSV, TSV and other files with no transformation
 Increase the power of edit distance with user selectable changes to large (>2)
distance requests for Fuzzy Hamming or Levenshtein searches.
 Enhance wildcard searches to include leading wildcard characters

4. Flexible Deployment On-Premise, in the Cloud or in
Hybrid Environments
Kibana Layer
Elasticsearch Layer
Lucene Layer
ES to Lucene
Ryft ONE / AWS F1 Instance
ES Plugin mechanism routes requests
(fuzziness & metric)
The Elastic Stack implements a distributed,
JSON-based search and analytics engine:
ES to Ryft
Primitive
Elasticsearch on Ryft can be deployed in your
environment, on-premise, hybrid or in the
cloud:
Deploy via the new Amazon
F1 platform.
Deploy on-premise or in
hybrid environments with the
Ryft ONE accelerator.

5. Speed search and analysis across unstructured data
and JSON, XML, LOGs, CSV, TSV files with no ETL
• Using
Elasticsearch
command
• Un-indexed
human genome
data
• Match query
with Levenshtein
search
• Edit distance of
4

6. Increase edit distance values beyond 2 using Fuzzy
Hamming or Levenshtein searches powered by Ryft
• Using
Elasticsearch
command
• Match phrase
query with
Levenshtein
search
• With edit
distance of 6
• No re-indexing
necessary
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7. Enhance wildcard searches to include leading
wildcard characters powered by Ryft
• Using
Elasticsearch
command
• Using XML
pcap file
• Looking for IP
addresses
xx.0.90.xx
• No ETL or
indexes
necessary

8. Thank you!
Contact us at info@ryft.com or www.ryft.com for a demo.