In the world of Big Data, it seems that everybody is talking about data being everywhere and needing tools to be able to manage and analyze all of this data. One problem we see is that users are having trouble getting to the data they need. Sure, most data sources have their own tools for reporting and analysis, but what happens when data is in different locations? How do I pull data from different sources into a common tool? Here is an interesting scenario:
I run a hotel in Whistler, Canada. In the summer, if the weather is good, I notice we get a lot of drive up traffic from Vancouver of people wanting to stay the weekend. How can I incorporate weather information with my staff scheduling system?
The answer to the above scenario is that the solution is based on the APIs. Every system that has data needs some form of API (application programming interface) to enable users and analytical applications to pull data from the data source. Of course, the problem is that every API could be different and how could an analytical application talk to every API? Our friends at Star Trek came up with the "Universal Translator" to allow different people to talk to each other. Together with our friends at Microsoft, we came up with ODBC (Open Database Connectivity) to solve the similar problem with different APIs and different applications. If every data source is enabled with an ODBC driver and if every analytical application is able to talk to an ODBC data source, then bingo, we have the data equivalent of a "Universal Translator". Of course, this worked well in the traditional world of databases like Oracle, IBM, and Microsoft. In today's world of Big Data, the same thing can still work. We just need to have all these proprietary interfaces somehow enabled with an ODBC driver and suddenly everything lights up.
At Simba, our SimbaEngine ODBC SDK has been just the tool that our partners need to build their ODBC drivers. Some examples are:
1. A medical management SaaS company used SimbaEngine ODBC SDK to build ODBC drivers so their customers could pull EHR data into Excel.
2. A GRC SaaS company used SimbaEngine ODBC SDK to build ODBC drivers so their customers could use BusinessObjects to report on their data.
3. Simba build an ODBC driver to talk to Hadoop/Hive so companies like MapR and DataStax could allow users of their Hadoop distributions to connect any ODBC compliant application to the data stored in the Hadoop cluster.