Elasticsearch and the Database Market
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The number of databases and database technologies has grown considerably. Databases are also becoming more and more application specific. Neither end of the spectrum is easy to manage. That's how database-as-a-service (DBaaS) can help. You can limit the number of technologies and still be flexible.
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Elasticsearch and the Database Market
- 1. www.objectrocket.com ELASTICSEARCH AND THE DATABASE MARKET Finding A Needle in the Database Haystack Steve Croce ObjectRocket for Elasticsearch Product Manager
- 2. www.objectrocket.com ObjectRocket What we do… • Hosted MongoDB, Redis, Elasticsearch and Hadoop How we do it… • ObjectRocket performance DBaaS platform • 24x7x365 engineer and DBA support on all plans Where we do it… • Rackspace Datacenters • AWS via Direct Connect • Microsoft Azure Our Mission: Disrupt the market with a completely new product class. One where customers can forget about the back- end data source and focus on building compelling products. Ultimately, we aim to improve by an order of magnitude the way customers store, retrieve, and manage data.
- 3. www.objectrocket.com Explosion of Database Technologies Source: DB-Engines and Wikipedia
- 4. www.objectrocket.com Achieving Balance Old Model Few databases for all the things Focused expertise Hard to scale New Model Unique databases for unique use cases Polyglot persistence Scale as you wish
- 5. www.objectrocket.com Elasticsearch A distributed, real-time, search engine / document store Easily scales to multiple servers and TBs of data. Data is searchable as it is added. Less strict schema or SQL-like rigidity. Very JSON friendly Best full text search capabilities of any technology in this space. Elasticsearch is a trademark of Elasticsearch BV
- 7. www.objectrocket.com • Ease of Use • Community • Compatibility / JSON • Broad Use Cases Elasticsearch is a trademark of Elasticsearch BV Elasticsearch: Why
- 8. www.objectrocket.com SEARCH LOG ANALYSIS VISUALIZATION Expansion of Use Cases MONITORING ANALYTICS Logstash Kibana Packetbeat Metricbeat Alerting Aggregations Filebeat Curator Timelion
- 9. www.objectrocket.com Implementation Methods Elasticsearch as the data store Elasticsearch as a complementary technology Elasticsearch as an additive technology I already have logs in ES… why not add: • Metrics • Monitoring • Analytics • Searchable Catalog • Document Store • Logging System • Add visualization to SQL, MongoDB, etc. • Add indexing/search to Hadoop • Add processing/storage to Kafka
- 10. www.objectrocket.com ELASTICSEARCH APPEARS TO BE DISRUPTING A FEW MARKETS OTHERS AREN’T THERE YET AND MAY NOT GET THERE Innovator’s Dilemma. Disruptive vs. Sustaining Technologies: Accessed 10/24/17. http://web.mit.edu/6.933/www/Fall2000/teradyne/clay.html Mainstream Adoption vs. Remaining Niche PRODUCTPERFORMANCE TIME Performance demanded at the high end of the market Performance demanded at the low end of the market or in a new emerging segment
- 11. www.objectrocket.com ● New datastore technologies = new challenges: Which to adopt and when? ● Finding balance is key ● Elasticsearch has grown from niche database technology ● Elasticsearch is set to disrupt markets ● Picking winners is difficult. DBaaS lowers the investment to investigate. Summary
- 12. www.objectrocket.com Consultations Available sales@objectrocket.com objectrocket.com/customers/ View Customer Stories Trial & Migrations always free objectrocket.com
Editor's Notes
- The discussion here will focus on a few key points: #1. The number of databases and database technologies has grown considerably #2. In the old model, you didn’t have the challenges of big data and there were fewer reasonable options out there for databases #3. Fast forward to today and the explosion of web technologies and big data has created a vast market of databases #4. Databases are also becoming more and more application specific #5. Neither end of the spectrum is easy to manage #6. The Punchline: You probably need to get closer to New School, so that’s why you need help (DBaaS), but also how can you limit the number of technologies and still become flexible
- Key points: #1. Elasticsearch is growing like crazy and passing other NoSQL technologies. Why? #2. See the reasons on the slide #3. Elasticsearch overtook Solr (IMHO) due to the closer alignment with the Python boom #3. It’s becoming a disruptive “utility” database In Top 10 Databases by DB-Engines Used by customers across industries: Facebook, Uber, Tinder, Yelp, ebay, Dell, Cisco, The Home Depot, etc.
- Key points: #1. Elasticsearch excelled (and still does) at a very niche area (search) #2. The key to the growth is this expansion outward over time #3. It started with Logstash and Kibana #4. They’re now doubling down and seriously improving the Analytics and Monitoring capabilties #5. Talk about it sweeps up the shortcomings of some other databases and plays as an add-on vs. a replacement (search for Hadoop, visualization for Mongo, etc.)
- Key talking points: #1. Talk about how disruptive what Elasticsearch is doing is #2. This is a low barrier to entry, easy to pick up technology that can grow with you #3. On the other hand some technologies that had similar popularity a few years back haven’t progressed