One of a software architect’s main issues is managing a database. This article’s goals are to highlight a few of these patterns and educate readers on Jakarta Data, a new specification proposal meant to simplify Java development. It is essential to take into account the persistence integrations in addition to selecting from a variety of available solutions.
MicroStream’s commitment to creative storage, on the other hand, is what distinguishes it from other databases of a similar type. Older databases hold their data on the physical storage, and disk access latency can often result in poor performance. MicroStream, in contrast, keeps all of its data in memory, which makes access very easy and fast. Moreover, MicroStream’s unique architecture allows it to achieve outstanding reduction rates, meaning that it has an extremely low memory profile. More memory equals free space for your data. MicroStream is designed to be easy and user-friendly, which always results in client satisfaction. Its meaningful design and low reliance dramatically minimize the impact is simple. It is simple to integrate MicroStream into your system because it requires a few extra resources.
What is MicroStream for Jakarta EE?
MicroStream is a high-performance, in-memory NoSQL database platform for quick data processing and storage. One of MicroStream’s most popular features is its extremely quick data access speeds, which are made possible by its unique architecture, which reduces overhead and does away with the requirement for external storage. Because MicroStream offers an easy-to-use programming architecture, you can include it in your current workflows and applications. Applications like real-time analytics engines, gaming platforms, and financial trading systems that need fast analysis and processing of data can benefit from MicroStream’s ease of storing and retrieving huge amounts of data in real-time.
MicroStream can leverage the new Jakarta Data and NoSQL specifications, which offer specific and quick solutions for handling data and modules in modern applications.
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MicroStream Eliminates Mismatch Impedance
The difficulty in mapping out the data between object-oriented programming languages and relational databases is what is usually meant by the term object-relational impedance mismatch. Object-oriented programming languages like Java or Python show data via objects and classes; on the other hand, relational databases store data in tables, rows, and columns. This misinformation of harmony in how data is represented could pose challenges for developing database systems that work seamlessly with object-oriented languages.
Overall, by eliminating the object-relational impedance mismatch and providing a simple, easy, efficient, and performant way to store and access data whenever needed by the client, MicroStream can help developers focus on building great applications rather than worrying about database architecture and design.
MicroStream’s ability to minimize conversions to and from objects could ensure improved performance. Together, let’s construct a MicroProfile application as the next stage in your path.
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Difference between JPA & Jakarta Persistence
Java Persistence API (JPA) and Jakarta Persistence Layer (JPL) are both well known frameworks for managing specific relational data in Java applications. While JPA has been around for a much longer time than Jakarta, JPL was introduced as part of the Jakarta EE specifications after Java EE was transferred to the Eclipse Foundation. In this blog post, we will compare the Java Persistence API and Jakarta Persistence Layer, providing code implementation examples for both circumstances.
What is Jakarta EE Used For?
Jakarta EE includes several specifications that serve different purposes, like generating web pages, reading and writing from a database in a transactional way, and managing distributed queues.
It is used for specifications like:
1. Web specifications
- Jakarta RESTful Web Services provides support in creating web services according to the Representational State Transfer (REST) architectural pattern;
- Jakarta JSON Processing is a set of specifications to manage information encoded in JSON format;
- Jakarta JSON Binding provides specifications to convert JSON information into or from Java classes;
- Jakarta XML Binding allows the user to map XML into Java objects;
- Jakarta XML Web Services can be used to create SOAP web services.
2. Enterprise specifications
- Jakarta Activation (JAF) specifies an architecture to reach component Beans by providing data structure typing and bindings of such types.
- Jakarta Contexts and Dependency Injection (CDI) is a specification to provide a dependency injection storage;
- Jakarta Enterprise Beans (EJB) specification defines a complex set of low APIs that an object container (the EJB container) will support in order to provide transactions (using JTA), remote procedure calls (using RMI or RMI-IIOP), concurrency control, dependency injection and access control for business subjects. This package contains the Jakarta Enterprise Beans classes and interfaces that define the contracts between the enterprise bean and its clients and between the enterprise bean and the EJB container.
3. Other specifications
- Jakarta Batch provides a sufficient means for batch processing in applications to run long-running background tasks that possibly involve a large volume of data and which may need to be subsequently executed.
- Jakarta Connectors is a Java-based tool for connecting application servers and enterprise information systems (EIS) as part of enterprise application integration (EAI). This is a primary-level API aimed at vendors that the average application developer typically does not come in touch with.
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Why is Java EE Called Jakarta?
The name java itself comes after Java Coffee, a type of coffee grown in Java Island.
James Gosling originally named it Oak, and the green before finally named it Java. It still carries the logo of the hot coffee cup.
Jakarta EE was initially known as Java EE or Java Enterprise Edition. In 2017, Oracle decided to Submit Java EE to the Eclipse Foundation. However since Eclipse and Oracle can not agree on the use of the “Java” trademark, it was renamed to “Jakarta”, a term that is familiarly close to Java.
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Conclusion
Jakarta NoSQL and Jakarta Data are crucial specifications that provide a standard set of APIs and tools for enhancing data in Java-based applications. Jakarta NoSQL enables developers to interact with various NoSQL databases using a familiar interface, while Jakarta Data provides APIs for working with data in various formats.
The MicroStream, Jakarta NoSQL, and Jakarta Data combination offer special tools and specifications for the management of data in upcoming Java-based applications. These technologies help streamline the development process and enable developers to focus on building various applications that meet the needs of their clients.