NoSQL and SQL Introspective
Oracle NoSQL Database 11g Release 2 (
Oracle White Paper
October 2013
Oracle White Paper— NoSQL and SQL Introspective: Oracle NoSQL Database 11g Release 2
Introduction ....................................................................................... 2
NoSQL – purpose-built data management ......................................... 2
NoSQL Application Example – simple data, simple queries ........... 2
Customer Profile Management ...................................................... 2
RDBMS vs NoSQL – The right tool for the right job ........................... 4
Simple Data, Simple Queries ......................................................... 5
Simple Joins .................................................................................. 6
Complex Queries ........................................................................... 7
What is NoSQL?................................................................................ 8
NoSQL systems............................................................................. 9
Oracle NoSQL Database – Value Proposition ............................. 10
Other NoSQL databases ............................................................. 11
NoSQL Database and RBBMS Database .................................... 12
Where do NoSQL Database projects get started? ....................... 12
Conclusion ........................................................................................ 1
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NoSQL – purpose-built data management
NoSQL systems are purpose-built solutions, designed to address specific technical
requirements. NoSQL systems originated to provide high throughput, fault-tolerant
horizontally scalable simple data storage and retrieval with a bare minimum of
additional functionality. Specifically, NoSQL systems were created in order to
Horizontally distributed data management of simple structured and unstructured
data across a large cluster of commodity storage systems,
Highly fault-tolerant data management and ability to continue operating even after
multiple hardware and system failures,
Very high throughput for simple read/write operations, with limited or no
transaction semantics,
Schema-less or flexible schema definitions allowing highly variable data and record
Application and application developer-centric special purpose data models and
On the other hand, RDBMS systems, like Oracle Database, are designed to provide
general purpose data management capabilities and standard APIs for a very wide
variety of requirements. Hence, they incorporate a lot of features and functionality.
Not all applications require the full set of RDBMS functionality. If the application
doesn’t require all of the functionality in a typical RDBMS, why would the customer
pay for the hundreds of features that they don’t need? For example, web-centric
customer service, loyalty card programs and customer profile management
applications primarily require fast, scalable key-based access to data. In such
scenarios, a cost-effective, purpose-built NoSQL database is an attractive alternative
to a relational system. Enterprises, ISVs and SIs are actively identifying applications
and data management processes which can be implemented and managed more
effectively using special-purpose NoSQL systems.
NoSQL Application Example – simple data, simple queries
Customer Profile Management
Let’s look at a specific example of an application that matches the capabilities of a
NoSQL system – customer profile management. In the past, customer profiles were
typically financial transaction-oriented data structures/repositories. Today, a
customer profile includes a much richer data set that includes information from a
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wide variety of customer interaction points that include both structured and
unstructured data. Capturing and managing this new class of data is crucial to the
enterprise, in order to more effectively obtain a 360 degree view of a customer and
to optimize customer interactions. This information enables a broad category of
Line-of-Business applications from Marketing, Advertising, Customer Service, Risk
Analysis, Fraud Detection, Personalized content, Promotional Campaigns, Loyalty
Programs, Inventory Management, etc. These Line-of-Business applications leverage
the richer user-profile data in order to provide
More personalized customer experiences via targeted product offerings, special
promotions, loyalty rewards, more informed/context sensitive interactions, etc.,
b. Better operational insight into how their customers interact with them, how they
perceive the company and its products and services, with a longer and more
complete historical perspective,
c. Better competitive insight into how customers perceive their competition,
d. Better operational decision making, based on a more detailed understanding of their
Modern customer profile management applications benefit directly from the
capabilities of NoSQL systems because they provide
A horizontally scalable, distributed data management system to manage the large
volume of data that is part of a rich customer profile and that can grow with little to
no maintenance as the customer base grows,
b. A highly fault tolerant system, ensuring that the customer profile data is always
available to the applications that need to access and update it,
c. A flexible or no-schema data store, which facilitates a wide variety of data record
formats to be stored in a given customer profile and for those record formats to
change over time,
d. Specialized, high throughput application-specific read and write access to the
portions of the customer profile that are important for that particular application1.
It is important to note that these applications often require support for transactions and
concurrency. Not all NoSQL databases provide this functionality. Oracle NoSQL Database does. For
more information see section on Oracle NoSQL Database on page 9.
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A great example of this is our recent work with well known Entertainment company
on their Next Generation Experience (NGE) application. This company wants to
create a centralized repository for each of its customer’s experience across all of its
entertainment properties (theme parks, restaurants, cruises, merchandizing outlets,
etc.) over a span of decades. The value of this solution is that a customer’s visits as a
child, then as a parent, then as a grandparent are all available in the system, regardless
of which (other) system the interaction originated from. They want the customer
profile repository to contain both structured and unstructured data, with a schemaflexible format so that it can evolve over time. Each customer’s profile will include
URL-style pointers to records of activities at the various properties, as well as
photos, privileges, loyalty program links, associated groups, other related customers,
customer feedback, etc. For this company the concept of “a customer profile”
includes many different sources and types of data, over an extended period of time,
resulting in a very large and varied set of data – centralized and served from one data
management infrastructure. This customer profile will be used to drive existing and
future applications that provide the customer with a personalized, enhanced
experience, utilizing both real-time and Business Intelligence Advanced Analytics
access to the customer profile. Originally this centralized repository was designed to
be managed in a relational database. However, last year they decided to re-design the
NGE repository to use a NoSQL database. They made this decision because
the NGE customer profile repository primarily required simple queries, simple data,
flexible schemas and horizontally distributed storage, which was more efficiently
addressed using a special purpose NoSQL database,
b. of specific application developer technical synergies with NoSQL technology. In
particular, their applications didn’t manage data using SQL nor did it represent the
data as SQL tables. From the application point of view, records were just JSON
objects consisting of simple, but variable data elements and pointers to other
records. Their natural application-developer-centric technical inclination was to
eschew using SQL and focus on a simpler, more special purpose database and API
that was closer to their application’s view of the data.
They are now also looking at a NoSQL Database. This is great example of a
common use case for a NoSQL Database.
RDBMS vs NoSQL – The right tool for the right job
Sophisticated RDBMS systems, for example the Oracle Database, encompass a very
rich set of features and functionality, primarily focused on general purpose OLTP
and Data Warehousing use by many different types of applications. NoSQL systems,
on the other hand, encompass a very limited set of features and functionality while
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providing horizontal scalability, availability and data modeling flexibility for specific
applications that manage simple data and simple queries.
NoSQL systems typically include a set of software packages running across dozens,
hundreds or even thousands of smaller systems. Efficient horizontal scalability, high
availability and concurrent data processing are provided out of the box, but the
integration effort to weave the software components into an integrated solution is
left up to the customer. Many of the advanced features that are common with
mature RDBMS systems are not present in NoSQL systems. This requires NoSQL
technology users to integrate their NoSQL data with the RDBMS systems in order to
make use of the advanced features that they need. NoSQL systems can do lots of
specific-purpose, simple operations extremely quickly, but are not designed with the
features to perform complex, general purpose operations in a integrated way.
Let’s look at an example of how this plays out in terms of understanding what types
of application characteristics are best suited for NoSQL and which ones are not.
Simple Data, Simple Queries
Let’s take the example of customer profile management discussed earlier. The
functionality that is required is very simple – the application needs to read and write
a few records based on the primary key -- customer ID. These records combine
structured and unstructured data, stored in a way (often de-normalized) that allows
the application to only operate on the subset of data that it needs for that specific
type of transaction. Customer profile management applications typically have to
perform an extremely high number of these simple operations of lookup based on a
customer ID with minimal latency. The latency component is critical because these
applications often implement the “last mile” interface with the customer. Customers
and other downstream systems interact directly with the content managed in the
NoSQL Database, and real-world studies have shown that any increase in latency can
be linked directly to reduced revenue and loss of business.2
Amazon.com conducted an extensive study that demonstrated a direct relationship between
increased latency and loss of revenue. For every 100ms (that’s 1/10 th of a second) of increased latency
on their web site, they observed a decrease of 1% in revenue. In other words, an almost imperceptible
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These “last mile” applications, based on rich customer profile management, are a
perfect fit for NoSQL databases. An RDBMS can provide the same level of
functionality and throughput, but they may not fit the technical requirements as
closely or as efficiently as a special purpose NoSQL database . This example can be
extended to sensor data (machine profiles, rather than customer profiles), loyalty
card programs, financial data, product data, etc. The bottom line is that for these
kind of operations (simple queries over simple data), NoSQL databases can be more
efficient than RDBMS systems.
Simple Joins
Let’s imagine a slightly more complex requirement, where the customer profile
application needs to perform multiple lookups in a small set of related tables (joins).
For example, a customer profile is likely to include a list of products (stored as
product IDs) that the customer has “liked” or “disliked” in the past.
In this case, it’s relatively easy to express the SQL JOIN queries in an RDBMS
(joining the Customer Profile table with Product table) and have the query optimizer
do the right thing to optimize and execute the joins. In a NoSQL database, it’s up to
the application (and the application developer) to implement the appropriate primary
and foreign key lookups in the most efficient order as separate operations in order to
satisfy the query. In a NoSQL database, the application logic would have to contain
code to perform a lookup of the Product table for each product ID in the customer
profile. Both the RDBMS and the NoSQL database could be used support this kind
of application requirement – the RDBMS is easier to implement, while the NoSQL
database may perform the simple queries more efficiently but some of the
functionality would have to be implemented within the application logic (the
application developer has to implement the joins using client-side code to perform
the appropriate lookups). So, why wouldn’t a developer choose the “easier” option
of using an RDBMS for this kind of application? Primarily for three reasons:
increase in latency translated directly into lost business because customers stopped browsing or using
the site.
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Simple joins are basically just incremental key lookups, sometimes described as
client-side joins. These simple joins are easily implemented in application code
b. When scalability and performance are the key requirement, simple special-purpose
data stores like a NoSQL Database offer an option that is better performing at a
lower cost of operation,
c. Over the past decade application development has changed. Even within established
RDBMS shops and especially in new/innovative technology companies, the
development of web-scale applications and new customer-oriented services has
moved towards Java-based application development. Developers are much more
accustomed to building data management and access to specialized, high
performance, high scalability databases such as Key-Value based NoSQL databases
in order to leverage the advantages that these products provide, even if it requires
some additional application development effort. It’s a “religious” discussion!
Complex Queries
Finally, let’s imagine that the application requires more than simple queries or simple
joins. The application may need to perform complex, multi-table joins3, to perform
complex analytics; it may require fixed schemas in order to enforce referential
integrity or other business rules; it may require heightened data security, data lifecycle
management or other advanced features that are commonly found in an RDBMS. In
this case, the clear choice is to use an RDBMS-based solution. A NoSQL technology
based solution would require significant functionality that would have to be
An example of a complex multi-table join: In an effort to reduce inventory overhead, a retail
manager wants to identify low margin items that are not selling well in the northwest region. They
might ask “Give me the Supplier name, Item Number and Item Description from the Supplier and
Inventory tables where the Price/Cost is less than 10% and the QuantityOnHand is greater than 20
and the total sales for the last 6 months in the NW region is less than $1000 from the Sales and
Inventory tables.” This is relatively easy to express in SQL and let the SQL optimizer and query
planner figure out how to get the data. But in a NoSQL application it would require writing multiple
queries and application code to collect and process the results of those queries in order to produce the
same result.
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implemented in the application. In fact, this is the primary argument in favor of
staying with an RDBMS, rather than switching to a NoSQL database. If the
application needs the rich functionality of the an RDBMS, don’t try moving to a
platform that doesn’t have (nor will it ever have) that functionality.
The above characterization of use cases reflects what we’re seeing in our customer
base – complex application functionality continues to be implemented using the
Oracle Database. However, in application scenarios where simple functionality,
horizontal scalability and schema flexibility are the primary requirements, these
applications are being implemented in NoSQL databases. The fact is that a full
customer solution typically includes both types of operations, and therefore both
types of databases. Customers are actively engaged in identifying the right database
management tool for the right job.
They are undertaking the necessary steps to adopt and integrate NoSQL databases as
part of an overall solution, where that tool makes sense. When talking with
customers it’s critical to recognize the technical challenges that are being addressed,
that one size does not fit all and how/when to use
What is NoSQL?
NoSQL (commonly interpreted as “not only SQL”) is a broad class of database
management systems developed over the last decade that is primarily identified as
not adhering to the widely used relational database management system model.
Although it is inherently difficult to define a technology based on what it isn’t, and
although NoSQL systems vary significantly in implementation, features and
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behavior, there are common design principles and technology requirements that
NoSQL databases share in common.
NoSQL systems
NoSQL systems provide horizontal scaling across a very large numbers of servers
(tens, hundreds or even thousands of servers) by using a technique that has been
deployed for many years in conventional RDBMS databases, called sharding.
Sharding requires that a separate database run on each server and that the data be
physically partitioned so that each database has its own subset of the data stored on
its own local disks. NoSQL systems maximize throughput by limiting how the
sharded data is managed and accessed. NoSQL systems typically do not provide
support for operations that require accessing multiple shards of data – this includes
joins, distributed transactions and coordinated/synchronized schema changes –
because of the I/O overhead and coordination required. NoSQL systems typically
implement limited transaction capability, either by relaxing transaction consistency
(by using “eventual consistency”), providing shard-local ACID consistency only or
by disallowing transactions altogether.
The primary use case for NoSQL systems is horizontally distributed, sharded data
sets with a flexible schema, and simple read/write operations. More complex, general
purpose functionality is not considered to be the primary goal of NoSQL databases.
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Oracle NoSQL Database – Value Proposition
The NoSQL Database is a highly scalable, high performance, high availability
distributed Key-Value database for near-real-time access to data. Like other NoSQL
databases, it is focused on providing horizontally scalable, simple data management
functionality. It differentiates itself from other NoSQL databases because:
Oracle NoSQL Database is based on mature, field-proven, production quality
software. Oracle NoSQL Database utilizes Berkeley DB Java Edition as the basis
for its storage and replication technology. Berkeley DB Java Edition has been
powering mission-critical applications in the field for almost a decade, including
companies like Amazon.com, LinkedIn, Yammer, Sand Vine and Macys.com. Many
of the other NoSQL databases are either creating their own storage and replication
layers from scratch (and finding out how difficult that is). Others are adopting
existing open source storage and replication technology (which may not be well
suited to their specific requirements).
Oracle NoSQL Database is the only NoSQL database developed and supported by a
major database vendor.
Oracle NoSQL Database is integrated with other related products like Oracle
Database, Oracle Business Intelligence, Event processing, Oracle Spatial, RDF &
Graph, Oracle Coherence and Hadoop/MapReduce . Other NoSQL databases
require that the customer figure out how to implement integration with their other
IT assets. Most Big Data projects require multiple, complementary data
management technologies and Oracle is the only vendor that has a comprehensive
offering of integrated technologies.
Oracle NoSQL Database has unique features like configurable ACID transactions,
and Dynamic Storage Node rebalancing, that many of the other NoSQL systems
lack. ACID transactions make application development much simpler and Dynamic
Storage Node rebalancing ensures robust, consistent and scalable database
deployment. Additionally, the Oracle NoSQL Database is not only proven to deliver
high throughput, but also guarantees predictable throughput and latency through
automatic, highly tuned database cache eviction policies and Java garbage collection
parameters. Other NoSQL databases often have unexpected limitations when it
comes to performance management and predictability, specifically related to file
system cleanup, compaction and Java garbage collection. A report from Amazon
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based on actual studies showed that 100ms (that’s 1/10 of a second!) of added
latency in accessing a page from the browser caused a 1% decrease in revenue!
Oracle NoSQL Database is much easier to deploy and simpler to manage4.
Oracle NoSQL Database has been extensively benchmarked using the industry
standard YCSB benchmark5, that has conclusively demonstrated a) scalability to
hundreds of storage nodes, b) across 10s of TB of data, c) 1.25 million operations per
Oracle NoSQL Database is Oracle’s flagship NoSQL database product. Sales can
confidently recommend the Oracle NoSQL Database, alongside the Oracle
Database, in order to address the needs of cost effective extreme data scalability and
Other NoSQL databases
There are over a hundred different NoSQL databases currently being offered on the
market. Customers who become early adopters of open source NoSQL databases
often invest in programming staffs that participate in the development and
maintenance of these products. There are currently no standards in the NoSQL
technology space, so each NoSQL product is different in terms of features, behavior
and implementation. It is not within the scope of this paper to do a full competitive
analysis of all of the alternative NoSQL databases that are available. For product
specific competitive comparisons, see the competition section of the Oracle NoSQL
Database OTN site.
Oracle NoSQL DB Quickstart Guide; http://docs.oracle.com/cd/NOSQL/html/quickstart.html
The YCSB benchmark is the de-facto standard benchmark used for NoSQL databases. More
information can be found here: http://research.yahoo.com/Web_Information_Management/YCSB
6 Oracle NoSQL Database benchmark links:
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The value proposition of Oracle NoSQL database is discussed in the previous
section. Oracle NoSQL Database as the best integrated, highest quality NoSQL
database from the best of breed purveyor of enterprise-class supported,
industrial grade database software.
NoSQL Database and RBBMS Database
The NoSQL Databases and the RDBMS Database complement each other. Each
solves a different type of requirement.
The NoSQL Database is designed to cost-effectively manage large volumes of
simple, structured and unstructured data. However, it is often the case that important
subsets of that data need to be loaded into the RDBMS Database in order to access
more advanced capabilities like complex queries, data security, data lifecycle
management and Advanced Analytics. Typically the same ETL-class tools that
support loading Hadoop data into RBDMS systems are also used for loading
NoSQL data into an RDBMS. The Oracle NoSQL Database supports the Oracle Big
Data Connectors (ODI and OLH), as well as direct access to its data via Oracle
Database External Tables, allowing customers to combine relational and NoSQL
data in the same query.
Just as Oracle NoSQL Database data may be moved into Oracle Database for
analytical functions, data stored in the Oracle Database may be moved into Oracle
NoSQL Database in order to enable high volume, high velocity web-based
applications. A typical example of this is moving certain aspects of customer profile
data and inventory information into the NoSQL Database in order to drive a webbased consumer retail application (e.g. loyalty card programs).
As discussed earlier, customers may choose to replace their RDBMS Database with
Oracle NoSQL Database, but for only the subset of data and functionality that are
best suited for the NoSQL technology approach. Most customers will use a
combination of an RDBMS and Oracle NoSQL Database to address their overall
data management requirements.
Where do NoSQL Database projects get started?
Although a NoSQL database project may start in almost any technical group, our
experience indicates that there are a few common ways that NoSQL projects get
NoSQL technology is typically evaluated in the context of Big Data data management
infrastructure and can get started in almost any technical group within a customer’s
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organization. It is often the case that these projects and opportunities are being
driven by application developers. When discussing application areas for a NoSQL
Database or when introducing the technology to customers, it is crucial to include
Application Architects and Developers in the technology discussion. It is often
within these groups that NoSQL technology evaluation and research is occurring.
Customers are constantly looking for opportunities to do more (increase business
value, deliver new services, derive new insights) with less (using commodity
hardware, open source software). The potential value and capabilities of Big Data
hold a lot of promise and customers are actively exploring ways to leverage Big Data
and/or NoSQL technologies. This technical exploration often leads to different
kinds of Big Data or NoSQL initiatives within the company. These initiatives fall
under some broad categories:
New initiatives (experiments) to leverage Big Data: For example, some
customers are leveraging social media data from Facebook and Twitter for example,
to provide a more comprehensive view of their customers. They are combining
these Big Data insights with their NoSQL customer profile applications.
New applications using existing data: Projects to take existing data and reuse it
in new ways. For example, an entertainment company might leverage customer
visits and interactions (e.g. hotel bookings, restaurant and car reservations, retail
activities, etc.) from existing systems and repurpose that data into a NoSQL
repository to provide a personalized experience for visitors.
Cost effective data management choices: Use NoSQL technologies to provide
efficient special purpose data management for existing applications that do not
require the full capabilities of an RDBMS. For example, a large electricity utility
company is planning to manage several terabytes of metering data in a special
purpose NoSQL repository because the application requirements, data structures
and queries are very simple.
Private cloud services: Several large customers have initiatives to build an inhouse data services platform that includes RDBMS, NoSQL, MapReduce and other
related technologies. By combining the three technologies together into a service
platform, customers can harness the rich feature set of an RDBMS, plus the
distributed, scalable, simple storage and processing of NoSQL (for interactive data
usage) and Hadoop/MapReduce (for batch usage).
NoSQL database technology is here to stay. It addresses specific technical requirements that are not as
efficiently or cost effectively addressed with other data management technologies, including RDBMS
systems. The RDBMS and Oracle NoSQL Database are complementary in the sense that they work together
to address the overall data management needs of our customers, each providing the technical capabilities
required by today’s complex and evolving applications. Customers can rely on the quality, integration and
support of the Oracle Database and Oracle NoSQL Database, and deploy their applications with
confidence, maximizing their technology investment and minimizing their risk; as opposed to opting for
other NoSQL database products with unknown scalability, quality and integration challenges.
NoSQL and SQL Introspective
October 2013
Author: Anuj Sahni, Dave Segleau
Contributing Authors: Oracle NoSQL Database
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