The History of Blob Storage

In early 2000 ‘s I had my introduction to Business Intelligence and all things data while working for an SAP partner in Glasgow. At the time I was glad to see the back of the Training company I’d been stuck in for the past three years and who had sent me to the training equivalent of Siberia which, in this case, was Livingston; a town with a train station miles outside of the town and a hell of a place to get to if you couldn’t drive. How I ended up there is another story but I now found myself in a new business and spending time with my head stuck in a training manual for Oracle PL/SQL This is where I came across the Binary Large Object or BLOB. In time I became an accredited Oracle SQL and PL/SQL trainer and was obliged to reel off the various datatypes , including BLOBs,  but I have to confess I didn’t give them much thought as they seemed a strange and exotic datatype that would surely be forgotten like the Palm Pilot or the Pager. Cut to quite a few years later and I’m playing about with Amazon Web Services and up pops Amazon S3 on my radar and its BLOB storage. Not only that but its suddenly a big thing; the De-facto storage for AWS which everyone is using.  The organisation I worked for were partnering with a lot of  Cloud application providers and they had BLOB setup as their default storage as if it were the most natural and obvious thing in the world. Looking at it now, BLOB is the perfect Datatype for a world where you need to be able to store digital information; not just banking records or customer mailing lists. Somewhere the Palm Pilot and Varchar2 are sitting, reminiscing on the old days while the new kid takes over. So, inthat spirit, lets take a whistle stop tour of the History of the Blob Storage. 

Blobs were originally just big amorphous chunks of data invented by Jim Starkey at DEC. He described them as “the thing that ate Cincinnati, Cleveland, or whatever” from “the 1958 Steve McQueen movie”.  Later, Terry McKiever, a marketing person for Apollo felt that it needed to be an acronym and invented the backronymn Basic Large Object. Then Informix invented an alternative backronym, Binary Large Object; a term that has now stuck.

The data type and definition were introduced to describe data not originally defined in traditional computer database systems; because it was too large to store practically at the time when the field of database systems were first being defined in the 1970s and 1980s. The data type became practical when disk space became cheap.

These days BLOBS are used to store a range of data. In particular Blob Storage is designed for:

• Serving images or documents directly to a browser.
• Storing files for distributed access.
• Streaming video and audio.
• Writing to log files.
• Storing data for backup and restore, disaster recovery, and archiving.
• Storing data for analysis by an on-premises or Azure-hosted service.

The story of BLOB storage follows closely the evolution of database systems and the need to efficiently handle and manage large and diverse data types. Over time, it developed in the following way:

1. Early Database Systems (Pre-1990s): In the early days of database systems, the focus was primarily on structured data, such as text and numbers. Storing binary data like images or documents was not a primary concern, and these data types were often stored as separate files on the filesystem, with references to those files stored in the database.
2. Emergence of BLOB Data Type (1990s): As the demand for more comprehensive and integrated data storage solutions grew, database vendors started introducing BLOB data types in their systems. This allowed for the storage of binary data directly within the database, offering better data integrity, security, and manageability compared to external file references.
3. Development of BLOB Storage Solutions (2000s): With the increasing popularity of multimedia content on the internet, the need for efficient BLOB storage solutions became more apparent. Database management systems (DBMS) like Oracle, Microsoft SQL Server, and MySQL introduced specialized BLOB storage mechanisms and optimisations to handle the unique challenges posed by storing and retrieving large binary data.
4. Cloud Storage and Object Storage (2010s): With the rise of cloud computing and the need for scalable and distributed storage solutions, object storage systems gained prominence. Cloud providers like Amazon Web Services (AWS) introduced services like Amazon S3 (Simple Storage Service), which offered reliable and scalable BLOB storage capabilities. These object storage systems became popular choices for businesses and developers to store and manage large volumes of binary data.
5. Advancements in BLOB Management (2010s-2020s): As data volumes continued to grow, database management systems and object storage services evolved to provide better performance, scalability, and accessibility for BLOB data. Technologies like sharding, replication, and distributed storage architectures further improved the efficiency of BLOB storage solutions.
6. Integration with Big Data and Analytics (2010s-2020s): BLOB storage became an integral part of big data and analytics platforms. Data lakes and data warehouses started accommodating large binary datasets alongside structured data, enabling organisations to perform advanced analytics on a wide range of data types.
7. Hybrid and Multi-Cloud Storage Solutions (2020s): The trend toward hybrid and multi-cloud environments has further influenced the development of BLOB storage solutions. Organisations are seeking ways to seamlessly manage and migrate BLOB data across different cloud providers and on-premises infrastructure.

Throughout its history, BLOB storage has evolved to address the challenges of storing and managing large binary data within the context of database and storage technologies. The demand for efficient, scalable, and accessible BLOB storage solutions continues to drive innovation in the field of data management and storage.

There you have it and thats it for this blog post. Watch out for others in our ‘History’ series.

Brian Rutherford

Ops Director

IO Analytics