Welcome!

Java IoT Authors: Liz McMillan, Elizabeth White, Yeshim Deniz, Zakia Bouachraoui, Pat Romanski

Related Topics: Microservices Expo, Java IoT

Microservices Expo: Article

Architecture Evaluation Framework for ORM Technologies

Enterprise architects must use this framework to decide on the appropriate ORM technology to use

Object Relational Technologies form the backbone of most of the enterprise Java applications. Choosing the appropriate technology however is one of the most important decisions for an enterprise architect. More often than not, such a decision is either a hit or miss. Mistakes done in selecting the appropriate technology results in performance bottlenecks, lack of scalability, unreliable transaction handling etc.

More than the problem with the specific ORM technology, it's the suitability of that technology to the underlying business needs and non-functional requirements. This article aims to establish an objective architecture evaluation framework for evaluating which ORM technology best fits your project needs. Based on the requirements, one or the other technology may be appropriate.

Flexibility
For an ORM framework to be flexible, the following considerations are important

  1. Do multiple options exist to access and manipulate data
    Should the project need multiple ways to access data. This would include object based way of querying data, using native SQL, using ORM specific natural query language. The architect must decide the importance of each of these methods and evaluate this parameter.
  2. Does the ORM tool supports extending the various default data types, with user defined data types
    Project needs change and so there are requirements to add custom data types. The ORM tool must support this feature, should you envisage the changing needs of your project.
  3. Ability to invoke interceptors on the data before it is saved, accessed or deleted
    Enterprise projects often need to add additional business validations or business logic over a period of time. Many of these changes need to be cross-functional. The ORM tool must have mechanism to intercept requests and inject such validations. This is an important factor if you foresee changes happening after the production deployment.
  4. Programmatic and Declarative Configurations
    The ORM framework must provide multiple ways for it to be configured. This is important again from the perspective of how flexible the tool needs to be.

Ease of Development

  1. Ability to create domain model from the database tables
    This is an important consideration if you already have database tables and you need to create domain model out of it through automatic code generation. The ORM framework must provide the appropriate utility for doing that.
  2. Ability to generate database tables from the domain model
    This is an important factor when the domain model has already been created as part of MDD and database needs to be created. This would ensure that there are minimal errors during generation of database schema
  3. Ability to specify natural query language for retrieval
    Typically ORM tools provide a criteria API to fire object oriented queries. However based on development experience, it is understood that this is not the best way of visualizing large and complex queries. If this is a criteria important for your project, you must ensure the availability of natural query language with the ORM tool. Support for native SQL is also important under this consideration

Reliability

  1. Support for JTA transactions
    An enterprise ORM framework must support JTA transactions. This support should be both declarative as well as programmatic. This is the most important consideration for evaluating the reliability of the platform as incorrect transaction handling would be catastrophic
  2. Support for Batch Processing
    Looping through individual transactions for batch processing is a perfect way to crash your system. The ORM tool must support JDBC Batch updates for batch processing.
  3. Support for Caching
    Caching is important both from scalability as well as reliability perspective. Support for integrating third party cache should be an important consideration for all enterprise projects. The cache support must be distributable across the cluster as well

Scalability and Performance

  1. Ability to use container or third party connection pools
    Connection pools should provide ability to scale up to increased load
  2. Ability to support legacy code
    If you need support for legacy code, the ORM tool must support native invocation of stored procedures
  3. Ability to optimize queries for performance
    It is very difficult to optimize a two page query written using criteria API. Infact for many complex scenarios for an enterprise application, there is a need to fire native SQL queries. These queries are also easy to optimize especially by the DBAs. If performance is a critical requirement, this factor must be considered
  4. Ability to cache queries and query results
    This is an important criterion for scalability

Maintainability

  1. Ability to modify domain model or DB model with minimal changes to underlying code
    This is an important factor if you foresee such changes
  2. Ability to log the framework internals
    During development as well as during production failures, there is an urgent need to debug to identify the issue. Many a times the issue may lie with the ORM framework itself. This is an important consideration for any enterprise application.
  3. Integration with JMX for runtime statistics
    If instrumenting the application during production under consideration, this is a must have feature for your ORM tool.

Essential Features

  1. Ability to support multiple relationships
    These would include one-to-many, many-to-many and many-to-one relationships
  2. Ability to support lazy loading
    This is important when you need to eagerly load a chain of nested objects. This feature is useful when underlying data store is not huge.
  3. Ability to support sorting and pagination
    These features are a must for search based applications
  4. Declarative security
    Authorizing different users to execute different queries can easily be achieved using this framework.
  5. Support for Dynamic SQL
    For any non-trivial application dynamic SQL is a must

Conclusion
An enterprise architect can use the above criteria to evaluate the most suitable ORM framework for his application. Each of the criteria should be judged with respect to the application requirements. A scoring model which gives weightage to respective parameters and computes the final scores for each of the applicable ORM tools is the right procedure to use the above architectural framework.

More Stories By Mahesh K Punjabi

Mahesh K Punjabi is a senior technology architect with Infosys Technologies Ltd. He has extensive experience designing enterprise applications using Java and multitude of RIA technologies including Flex and GWT. His other passions include photography and speaking with Toastmasters' clubs.

IoT & Smart Cities Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...