In the beginning: OLTP (Online Transaction Processing)
OLTP emerged several decades ago to make possible the development of interactive experiences for customers. Prior to the OLTP, a customer would perform an activity and only at some point, relatively far off in the future, would the back-end system be updated to reflect the activity. If the activity caused a problem, that problem would not be known for several hours or days.
Up until now, OLTP systems have been the go-to choice for handling transactional use cases. These cases typically involve a high volume of database transactions, demanding extremely fast response times and concurrent data processing. Examples include e-commerce and online banking.
The usual approach involves the creation of relational databases, which are designed to manage structured data using predefined schemas, in rows / columns and tables. SQL (Structured Query Language) is the language of choice for querying and managing data within this domain.
OLAP (Online Analytical Processing) Emerges to Complement OLTP
OLAP emerged after OLTP, as enterprises recognized the need for flexible access to the data stored in their OLTP systems for analytical purposes. Given the criticality of the OLTP systems, it was not safe to allow database users to run resource-intensive queries that could potentially jeopardize the system’s availability and reliability.
Analytical use cases then found their home in OLAP systems, which handle complex queries at relatively slower response times, more suitable for data analysis rather than real-time business applications.
The NoSQL Work Around
NoSQL databases emerged in the 2010s as the cost of storage dramatically decreased. Gone were the days of needing to create a complex, difficult-to-manage data model in order to avoid data duplication.
As storage costs rapidly decreased, the amount of data that applications needed to store and query increased. With the data coming in various forms and sizes, defining the schema in advance became nearly impossible. Thus, NoSQL databases started to allow developers to store huge amounts of unstructured data, offering them lots of flexibility.
Conclusion
The database market is the largest category in enterprise software — $60B and growing – meaning that there is room for many winners in the space, which Fabrica Ventures will hopefully be able to source.