Hadoop and Salesforce Integration: the Ultimate Successful Database Merger
Monday, April 18, 2016 at 8:56AM 
The emergence and continued success of Hadoop has revolutionized the management of big data. This open source MapReduce technology has enabled easy access and reliable answering of advanced data questions. It has taken the data management to a completely new level. The recent news of partnership between salesforce and key Hadoop components including Cloudera and Hortonworks has made the concept even easier and more reliable. With the new set up in place, nothing but perfection and lots of ease is expected in handling large data entries. It will be easier facilitating the management of bulky files and databases.
What remains as a great challenge is the integration of such components for everyday users. It will only be profitable if database managers can efficiently take advantage of the integration. For instance, how does one transfer salesforce data into Hadoop? Not everyone who needs this knowledge has reliable access to it. It might appear quite a simple task for a database guru and yet a completely daunting one for someone who is setting foot in this challenging yet eventful arena.
Transferring Salesforce Data to Hadoop
Essentially, getting salesforce data into Hadoop cluster comes with a completely new set of challenges. It opens a new world of database integration awaiting exploration. It is a relentless opportunity of combining salesforce data and other essentials like log data and domain specific data necessary for ideal business operations. Depending on the salesforce data you are handling, transferring essential information from Salesforce to Hadoop Clusters does not have to be a daunting task.
By using innovative tools such as Salesforce2Hadoop, it becomes easier facilitating the transfers of such entries. This tool normally comes in the form of command line. With the tool, it is possible to carry out a complete import. Alternatively, one can use the tool to increase the importation of data from Salesforce platform to local file systems. What makes the tool an incredible option in transferring data from salesforce to Hadoop is the fact that it supports other common salesforce data types like Opportunity and Account. Additionally, it offers support for custom type data types. This makes it an incredible tool for transferring data from Salesforce to Hadoop Cluster.
What are the key features of the data transfer tools?
Salesforce2hadoop, the new platform for facilitating large data transfers between the two giant systems exhibit unique specifications. These include;
- Scala Programming Language
Unlike Hadoop, which is chiefly based on Java language, this new, and exciting data transfer platform embraces another programming language known as Scalar. It makes the interaction with Hadoop relatively easier. This easily accessible language also makes the user interface friendly and more accessible to average users.
- Based on KiteSDK Library
KiteSDK is an information packed library that was an establishment of Cloudera technical team. The knowledge from this incredible collection is used in the setup of salesforce2hadoop; an incredible data transfer tool. With this advanced knowledge, it becomes relatively easier creating data sets with particular shema. It also becomes possible to read and even write records to these datasets without having to use the challenging APIs.
- Features Apache Avro
It is also worth noting that the incredible platform also features the use of Apache Avro to enable writing to HDFS. This comes with a significant advantage of being able to evolve the schema without the necessity of re-importing all the data.
The Data Transfer Process
The process of transferring information using the salesforce2hadoop tool is even more challenging but not without its own share of interest. Every single import involves updating of Avro Schema. In the process, the contents of the Enterprise WSDL of your organisation will be duly reflected.
Most notably, the data extraction process uses WSC. This Java library component creates an interaction with Salesforce using SOAP. Notably so, the WSC involved is an advanced level abstraction in addition to the regular SOAP interface.
Other Integration Applications
Besides the transfer of data from Salesforce to Hadoop, there are other applications involving the two systems. These wide range applications come in handy for those in need of efficient and reliable data management services.
- Integration of Salesforce and Hadoop has given birth to Collaborative filtering tool, which is an essential component of Salesforce. Salesforce uses this tool to recommend files and users worth following. This trending innovation has made it possible for the Salesforce giants to better their platform and make it more interactive. Without the emergence of Hadoop and creative integration of the two components, such innovative ideas could not have materialised into profitable and helpful tools.
- The other notable fruit of merging Hadoop and Salesforce is Product metrics. Technically, this is useful for product managers. It facilitates their endeavours of understanding the usage of various products. It is a critical tool necessary for definition of features, standard metric sets and log instrumentation. These are key Salesforce aspects that could not have been in place were it not for the profitable merger of Hadoop and Salesforce.
- Most incredibly, taking advantage of Hadoop technology has enabled Salesforce to embrace critical products in their systems. Through the integration, Salesforce was able to adopt a variety of products like Chatter File, User Recommendation and even search relevancy. This has not only eased operations at salesforce but also steered data management and technological development in this giant system.
Conclusion
There is no doubt that Hadoop has taken data management to the next level of success. It is the new face of efficient management of large files and bulky systems that were otherwise considered difficult. The integration of Hadoop and Salesforce has made the process of managing large data files even easier and more reliable. It might not be too early to say that the integration has brought home some of the most successful projects. The merger has brought home newer applications that are handy in solving everyday data problems. It’s only those who embrace this new technology and take advantage of the merger walk away smiling.
Reader Comments (2)
Needs correction - Should be Scala and not Scalar
Scalar Programming Language.
Its "Scala Programming Language". You need to correct this. Otherwise, It is very informative post. Keep posting!!