The Fifth Elephant 2014

A conference on big data and analytics

In 2014, infrastructure components such as Hadoop, Berkeley Data Stack and other commercial tools have stabilized and are thriving. The challenges have moved higher up the stack from data collection and storage to data analysis and its presentation to users. The focus for this year’s conference on analytics – the infrastructure that powers analytics and how analytics is done.

Talks will cover various forms of analytics including real-time and opportunity analytics, and technologies and models used for analyzing data.

Proposals will be reviewed using 5 criteria:
Domain diversity – proposals will be selected from different domains – medical, insurance, banking, online transactions, retail. If there is more than one proposal from a domain, the one which meets the editorial criteria will be chosen.
Novelty – what has been done beyond the obvious.
Insights – what insights does the proposal share with the audience that they did not know earlier.
Practical versus theoretical – we are looking for applied knowledge. If the proposal covers material that can be looked up online, it will not be considered.
Conceptual versus tools-centric – tell us why, not how. Tell the audience what was the philosophy underlying your use of an application, not how an application was used.
Presentation skills – proposer’s presentation skills will be reviewed carefully and assistance provided to ensure that the material is communicated in the most precise and effective manner to the audience.



For queries about proposals / submissions, write to


  1. Data Collection and Transport – for e.g, Opendatatoolkit, Scribe, Kafka, RabbitMQ, etc.

  2. Data Storage, Caching and Management – Distributed storage (such as Gluster, HDFS) or hardware-specific (such as SSD or memory) or databases (Postgresql, MySQL, Infobright) or caching/storage (Memcache, Cassandra, Redis, etc).

  3. Data Processing, Querying and Analysis – Oozie, Azkaban, scikit-learn, Mahout, Impala, Hive, Tez, etc.

  4. Real-time analytics

  5. Opportunity analytics

  6. Big data and security

  7. Big data and internet of things

  8. Data Usage and BI (Business Intelligence) in different sectors.

Please note: the technology stacks mentioned above indicate latest technologies that will be of interest to the community. Talks should not be on the technologies per se, but how these have been used and implemented in various sectors, enterprises and contexts.

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Vivek Shrivastava


Why we built the most adopted Polyglot Object Mapper for NoSQL?

Submitted Apr 25, 2014

The talk would narrate the story of building the most adopted Polyglot Object Mapper for NoSQL, Kundera ( Kundera is a High Level Client / Object Mapper with a JPA interface for working with RDBMS and NoSQL Datastores. It can be considered as a Hibernate equivalent for NoSQL Datastore.


NoSQL Datastores are tough. But JPA interface of dealing with Datastores is easy, well known and has been popular with developers since long. So we combined both the two things and created Kundera.

Kundera is innovative in many ways:
• Kundera supports polyglot persistence i.e. an application can use multiple and any combination of datastores. All the hard work related to mapping, persisting, reading, indexing and transacting object model across multiple datastores is handled by Kundera,
• Kundera supports 8 NoSQL datatsores and any RDBMS.
• Kundera provides very easy and well known interfaces like JPA and REST to interact with all the datastores. Hence it hides all the complexities of NoSQL stores and reduces the learning curve enormously.
• Kundera also facilitates easy migration of your existing hibernate/JPA powered applications to NoSQL.
• Kundera is extremely extensible and one can easily add support for new datastores with very minimal effort.

Impact of this product:
• It has made the task of a NoSQL developer extremely easy.
• It has simplified working with 8 leading NoSQL datastores; Cassandra, MongoDB, HBase, Neo4j, Redis, Oracle NoSQL, CouchBase and ElasticSearch.
• It has enabled 10 very big scale applications to use NoSQL and move to production.
• It has enabled number of people in open source community to build exciting solutions (like NoSQL Datastore Migrator, NoSQL Data Viewer) on top of Kundera.

While coming up with such a product that talks to so many different types of datastore, there have been challenges. And the learnings. The talk would cover these challenges and learnings.

Speaker bio

Vivek Shrivastava, Technical Architect & NoSQL Evangelist, Impetus Technologies

Vivek Shrivastava has over 14 years of experience on product development, designing and engineering enterprise grade solutions for Finance, Travel, Retail and Interactive Television domains. His expertise includes NoSQL Data-stores, Cloud Computing and BigData. Vivek has spearheaded the design & architecture of several large & cloud scale solutions for data lifecycle management at petabyte scale. Vivek also leads the development at Open source project Kundera which is a JPA 2.0 compliant Object-NoSQL Mapping Library and is a major advocate of Polyglot Persistence.


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All about data science and machine learning