Tag: Data computing middleware

To achieve the business logic focused on database in Java, three key elements are required: the objectification of the database table, the ability to calculate the structured data, and the ability to process the flow. Hibernate is an old and well-established technology, and has long since provided the three elements, and achieved a large number of data business logics in many projects. SPL is a new data computing language. Likewise, SPL has the said elements, which can also be used to achieve data business logic. This article will compare them in many aspects so as to find out the one

Many open-source technologies can implement the business logic focused on database in Java. Among them, JOOQ is more powerful than Hibernate in computing power, and more powerful than MyBatis in migratability, thereby getting increasing attention. Likewise, esProc SPL, as a new data computing language, is also outstanding in terms of computing power and migratability. This article will compare them in many aspects so as to find out the one that is more efficient in developing data business logic. JOOQ commercial edition mainly supports commercial database and stored procedure, which will not be discussed in this article. Language features Programming style

Many free open-source data processing engines can be embedded in Java application, among which, SQLite has been used for a long time, and used by many users, and esProc SPL, as a rising star, is also strong in functionality. This article will compare them in many aspects. Basic features Language style SQLite uses the traditional SQL code (the two are equivalent in this article). SQL is popular in this industry, so there is no need to give a more introduction to it. SPL is a modern data computing language, whose style belongs to the simplified object-oriented language. SPL has the

The open-source data processing languages based on JVM mainly include Kotlin, Scala and SPL. This article will compare them in many aspects to find out the one with the highest development efficiency. The applicable scenarios of this article are limited to common data processing and business logic in practice, placing emphasis on the structured data, not focusing on big data and high performance, nor involving special scenarios such as message flow and scientific computing. Basic features Applicability Kotlin was originally designed to develop more efficient Java, and is applicable to any application scenario involved in Java. In addition to common

It is common to process data files of open formats like txt, csv, json, xml and xls in Java applications. Hardcoding in Java is extremely complicated, so we often turn to certain ready-for-use open-source packages. But each package has their weaknesses. Parsing library. This type of class libraries enables to read an external file in Java as the latter’s internal object through a simpler coding process than hardcoded data retrieval. Common products include OpenCSV for parsing txt and csv files, SJ.json, Gson and JsonPath for parsing json files, XOM, Xerces-J, Jdom, Dom4J intended to parse xml files, and POI, which

Though a lot of embedded data engines for Java are available, the competent and effective ones are rare. Redis has poor computing ability and can only handle simple query scenarios. Spark has complex and heavy framework and is inconvenient to deploy and maintain. Embedded databases like H2\HSQLDB\Derby have lightweight frameworks but they lack sufficient computing abilities – they even do not support the basic window functions. SQLite achieves the best balance between a good framework and satisfactory computing ability. It is now a widely-used Java embedded data engine. SQLite suits regular basic computing scenarios SQLite has lightweight framework. The library

During contemporary application development, SQL is generally used to achieve simple data loading and saving while most part of the computing procedure and business logic is implemented in the application. This is because: In view of this, it is important to implement post-SQL computations in the application. Generally, SQL returns structured data. So, a good post-SQL computation technology should have a convenient structured data object for further computing and processing data returned by SQL, offer enough library functions and have computing ability at least as good as SQL, and ideally, support loop and branching statements to achieve procedural control. Additionally,