Learn how Lucene runs more than just search indexes, how to build a proper search engine, and how to decide between SolR , Elasticsearch, Amazon CloudSearch or Azure Search.

1. www.anant.us | solutions@anant.us | 202.905.2818
1010 Wisconsin Ave, NW | Suite 250 | Washington, DC 20007
Research & Development –
Comparing Lucene / SolR / Elastic &
Cloud Search Providers
Building Search Engines

2. What do we do?
Streamline, Organize & Unify
Business Information

3. Agenda
• Challenge - Why does this matter?
• Info Retrieval - Retrieval / Routing
• Lucene - More than meets the eye ...
• Search Engine - 30k Foot View
• On Premise - Lucene / SolR / Elastic
• Cloud Providers - Amazon / Azure

4. Challenge – Why does this matter?
Knowledge
Project
Information
Client Service
Information
Corporate
Guides
Collaborative
Documents
Assets
& Files
Corporate
Resources
Appleseed Framework (Portal, Base, Search)
G Drive
Delta
DropBox
G Drive
Delta
Nutshell
Dropbox
Freshbooks
G Drive
G Sites (KB)
G Drive
Workflowy
Evernote
G Drive
DropBox
OwnCloud
Pocket
Leaves
AIC (WP)
Anant (WP)

5. Document Retrieval
• Google Search
• Amazon Search
• LinkedIn Search
• CMS Search *
• Portal Search *
• CRM Search *
• Search *
Document Routing
• Google Alerts
• Amazon Recommendations
• Netflix Recommendations
• LinkedIn Recommendations
Information Retrieval

6. Lucene – Inverted Index

7. Lucene – More than meets the eye
Who
Next?
Think of it like a “NoSQL” Database that has great indexing..
everywhere.

8. Search Engine – 30 Thousand Foot View
The search index is only as good as your processed data.
If you put everything you find in your index, you are going to
spend a lot of time telling people how to search.

9. On Premise – Lucene / ES / SolR
Lucene
• Library
• File System
• Format
• Fast
• Embeddable*
• Indexing Anywhere
• Need to really know
Lucene
• No Interface
• No server
• Lots of house
keeping
SolR
• Server
• Admin / REST
Interface
• Configurable
• Scalable
• Great at Text*
• Truly Open
• 10+ Years
• Good ecosystem
• Too customizable
• Schemas*
• Zookeeper Needed
ElasticSearch
• Server
• Configurable
• Scalable
• Good ecosystem
• Built in Clustering
• Grouping / Filtering
• Great for Logs
• Started as a Cloud
Tool
• No great OTS
Interface
• Only REST Interface

10. Cloud Search – Amazon / Azure
Amazon
• SolRCloud*
• AWS* Ecosystem
• 5 QParsers
• Dynamic Fields
• 100% Completely
Managed
• Been Around for a
While
• Data / Read Writes
• No nested Objects
Azure
• ElasticSearch*
• Azure* Ecosystem
• 2 QParsers
• 100% Completely
Managed
• Good SDK
• Few Years Old
• Data / Read Writes
• No nested Objects
• Not so Dynamic Fields

11. Questions & Contact
www.anant.us | solutions@anant.us | 202.905.2818
1010 Wisconsin Ave, NW | Suite 250 | Washington, DC 20007
@anantcorp
facebook.com/anantCorp
linkedin.com/company/anant
rahul@anant.us
linkedin.com/in/xingh
Rahul Singh
CEO & Founder
Questions & Contact
• Modern Enterprise
• Mastering Services in the Service of Others
• Hybrid Agile Project Management
• Building Search Engines
• CICD / DevOps
• Connecting Internet Software

12. www.anant.us | solutions@anant.us | 202.905.2818
1010 Wisconsin Ave, NW | Suite 250 | Washington, DC 20007
Streamlined Data
Integration / Data Pipelines
Organized Knowledge
Search / Data Warehouses
Unified Interfaces
Portals / Dashboards / Mobile