Thomas Edison spent 10,000 hours testing to build one of the great inventions of all time, the electric lightbulb.
As a kid, I dreamed of becoming Thomas Edison, not Thomas Coffing, but I have spent what seems like 1,000,000 hours attempting to get all databases to integrate seamlessly.
It took Thomas Edison two years to build the lightbulb, but it took me five years to get Teradata and Oracle to integrate and another 15 years to migrate and join data across all systems.
After programming in assembler and COBOL for ten years, I became a teacher of Teradata systems. I traveled the world teaching the largest companies all aspects of Teradata. I wrote 50 books on Teradata, and people began to call me Tera-Tom.
I then began teaching and writing another 35 books on all other database platforms, but that is when I noticed something nobody else had seen. There are only two types of database platforms:
1) Systems such as Teradata, Oracle, Synapse, DB2, and SQL Server type systems with enormous indexing take a ton of DBA and tuning to work efficiently. 2) Load-and-go systems that capture min/max metadata for each data block require no major tuning, like Redshift, Yellowbrick, and Snowflake.
I realized that all database companies think their product is the only database a customer needs, but it's not about the database. It's about the end-user accessing data across all databases.
So, I said to myself, who in the world has spent ten years in the trenches as a programmer, written 85 books on all databases, taught over 1,000 classes to the largest clients, and knows the needs of the IT staff, developers, ETL teams, DBAs, and data warehouse managers better than me? Nobody.
That is when I knew I could build software that nobody would see coming until it was too late. I realized that one day no database could hold a company's data and that every company would need to access multiple databases. In time, companies would need to access data across dozens of systems, and eventually, companies would need to access data across hundreds of systems. And even further out, companies would eventually not even care what system the data resided because they would need to access data wherever it resides.
So, I hired a team of genius developers, and we built Nexus for everyone who accesses data. Nexus queries all systems and lets users slice and dice the answer sets, pivots, calculates analytics, shares the answer sets, and has the option to build the SQL for the user automatically. Nexus allows the ETL team to migrate thousands of tables to and from two data sources. Business users can integrate and build data into their sandboxes without the required technical knowledge.
And the most difficult part is to allow everyone to join data across any number of systems as easily as if all the data were on a single enterprise data warehouse or data lake. Who wants to be Thomas Edison when they could be Thomas Coffing, better known as Tera-Tom? Edison was a slacker😊.
Each company has a unique timing for its growth and evolution. So when your time intersects with my vision, and you need to migrate across platforms and join data anywhere, please call me.
Yours when you need to shine the light on all data,
Thomas "Edison" Coffing
Below is a video of Nexus in action that is all you will need to see to realize why 20 years of dedication to corporate perfection pays dividends.
The picture below shows Nexus using an advanced Snowflake SET Operator technique to provide five different reports on sales data in a single report.
Tom Coffing has also led a team of developers for almost 20 years to create the Nexus, which queries, migrates, and joins data across all systems. Amazingly, Nexus migrates between all the databases below with the click of the mouse.
• MySQL
• Excel
• Microsoft Access
• Snowflake
• Redshift
• Synapse
• BigQuery
• Teradata
• Oracle
• SQL Server
• DB2
• Hadoop
• MapR
• Greenplum
• Postgres
• Vertica
• Netezza
• SAP HANA
• Yellowbrick
• SQLite
The picture below shows Nexus in dark mode migrating Oracle data to Snowflake. Some customers are migrating thousands of tables to Snowflake in a single job.
It is never too early to dream about the future of data.
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