Skip to main content

Is Oracle's Larry Ellison Wrong on Object Stores?

It's All About the DATA

Here's Larry Ellison's critique of Workday. "Workday does not use a database, they use an object store. So, they can't really do reporting. They use flash. So, they can't run on iPhones or iPads. Besides that, they're great!"


 Here's the overview Workday application architecture (from Workday).
Workday uses object model and stores the objects MySQL table as a blob instead of normalizing and storing the data in multiple tables, tuples, and columns. Object store makes object-relational mapping, object disassembly/assembly unnecessary. Because you store objects, you lose some benefits of RDBMS: query processing -- select, join, project, schema, optimizer to rewrite complex query, and help the query to perform better.  Complex query processing is essential for canned or ad hoc reporting.  Each task will be have to be written as a program that retrieves all the objects, explode them into runtime objects, and then do the analysis.  It's slow. It's expensive.
Larry Ellison may have been right back in 2012.  BLOB or TEXT were the options to store objects in most RDBMS. DB2 and others had XML store with XQuery never really took off in any serious enterprise application. Back in 2012, MongoDB, provided object store with its flexible JSON data model, basic query processing, was focusing on developers, rather than enterprise.  Any reporting or complex query processing was not possible.
Workday would have to support very limited reporting on their object store or provide ways to extract the data into a normalized form to enable reporting on them. Additional setup, maintenance, work and cost.
Document oriented databases like MongoDB, Couchbase, DynamoDB, DocumentDB have all provided a way to store in JSON.  JSON stores hierarchical data as nested basic types, objects, and arrays.  So, we can store hierarchical objects in JSON, limiting the object to store mapping work. Here’s an example of customer object in JSON.
Now that we have object and its persistence defined, you can develop application on this object store.  Couchbase SDKs and MongoDB SDKs help you develop applications. So far, so good.
The criticism from Larry Ellison back in 2012 was that while you can develop applications, trying to reports on the data these applications created is impossible.
While document databases started out with with the NoSQL approach of basic GET, SET APIs, they’ve seen the need for complex query and provided them to various degrees. Mongo’s query API and Couchbase N1QL is inspired by SQL.  Some more than others :-)
MongoDB provides SQL inspired basic version of SELECT, INSERT, UPDATE, DELETE, UPSERT.  For reporting, MongoDB’s find() provides basic select-join-project operation,  You can even get the plan using the explain() on find().  Aggregation and joins are provided via the aggregate() method.  The aggregation method provides all of the basic filtering, grouping, aggregation, sorting functionality.  Pipelining of the aggregation helps you with multi-level filtering/ordering/grouping.  The aggregate comparison page shows you how the simple SQL statements can be written in MongoDB form.
On the other hand, Couchbase N1QL stays close to SQL, extending it to access & manipulate JSON. In Couchbase N1QL, you can issue queries like this on JSON data.  Select, join, project, nest, unnest, subqueries, aggregation, pagination, sorting are all available just like SQL. You can also generate reports using Couchbase N1QL.  Look at the example below. 
So simple and so SQL. 
Checkout more examples at querycouchbase.com.  Couchbase N1QL also has ODBC, JDBC drivers from Simba to enable BI tools, Excel to directly access and create complex reporting and visualization. Checkout the talk and the blog on using this on your data.
Is Larry Ellison wrong for saying: “you can’t do reporting on object store” in 2012?  Fortunately, you’re not in 2012 anymore.

Comments

Post a Comment

Popular posts from this blog

Swami Vivekananda: The Monk That Nobody Sent to Chicago

  There’s a saying in Chicago: “We don’t want nobody that nobody sent.” This was the cold reception Swami Vivekananda faced when he arrived in the windy city in July 1893, determined to attend the World Parliament of Religions that September. He belonged to no organization, carried no letter of recommendation, his countrymen were nobody, and represented an alien religion to the Western world. As the days passed, his hope of attending the parliament dwindled. With money running out and the odds stacked against him, he left the Windy City and went to Boston, praying for a glimmer of opportunity.  Swamiji came to America to share India’s most profound gift: the wisdom of the Hindu sages, preserved through centuries of oral tradition and embodied by its monks. This was 1893, not 1993—India was under the British grip, its resources drained, and its spirit subdued. Swamiji’s mission was not just a cultural exchange; it was a bold step toward envisioning a future where India could re...

Why Should Databases Go Natural?

From search to CRM, applications are adopting natural language and intuitive interactions. Should databases follow? This article provides a strategic perspective. Amid the many technological evolutions in software and hardware (CISC/RISC, Internet, Cloud, and AI), one technology has endured:  Relational Database Systems   (RDBMS), aka SQL databases. For over 50 years, RDBMS has survived and thrived, overcoming many challenges. It has evolved and adopted beneficial features from emerging technologies like object-relational databases and now competes robustly with   NoSQL databases .  Today, RDBMS dominates the market, with four of the top five databases and seven of the top ten being relational. RDBMS has smartly borrowed ideas, like JSON support, from NoSQL, while NoSQL has also borrowed from RDBMS. NoSQL no longer rejects SQL. From a user perspective, all modern databases have SQL-inspired query language and a set of APIs. All applications manage the respective data...

iQ Interactive: Cool Things for Developers on Couchbase Capella iQ

  The landscape of software development is ever-evolving with the advent of new technologies. As we venture into 2023, natural language processing ( NLP ) is rapidly emerging as a pivotal aspect of programming. Unlike previous generations of tools that primarily aimed at enhancing coding productivity and code quality, the new generation of Artificial Intelligence ( GenAI ) tools, like iQ, is set to revolutionize every facet of a developer's workflow. This encompasses a wide range of activities: Reading, writing, and rewriting specifications Designing, prototyping, and coding Reviewing, refactoring, and verifying software Going through the iterative cycle of deploying, debugging, and improving the software Create a draft schema and sample data for any use case Natural language queries. Generate sample queries on a given dataset Fix the syntax error for a query Don't stop here. Let your imagination fly. Although the insights garnered from iQ are preliminary and should be treated ...