honey
Bee is an AI, easy and high efficiency ORM framework,support JDBC,Cassandra,Mongodb,Sharding,Android,HarmonyOS. Honey is the implementation of the Bee.
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Bee is an ORM framework that provides easy and high-efficiency database operations, allowing developers to focus on business logic development. It supports various databases and features like automatic filtering, partial field queries, pagination, and JSON format results. Bee also offers advanced functionalities like sharding, transactions, complex queries, and MongoDB ORM. The tool is designed for rapid application development in Java, offering faster development for Java Web and Spring Cloud microservices. The Enterprise Edition provides additional features like financial computing support, automatic value insertion, desensitization, dictionary value conversion, multi-tenancy, and more.
README:
Easy for Stronger.
Bee is an ORM framework.
Bee is an easy and high efficiency ORM framework.
Coding Complexity is O(1),it means that Bee will do the Dao for you.
You don't need to write the Dao by yourself anymore.Help you to focus more on the development of business logic.
Good Feature: AI, Timesaving/Tasteful, Easy, Automatic (AiTeaSoft Style)
Newest version is:Bee V2.4.0 LTS
Sharding target: It is mainly transparent to business development and coding, with only a little sharding config.
Bee see:
https://github.com/automvc/bee
bee-ext:
https://github.com/automvc/bee-ext
Easy to use:
- 1.Simple interface, convenient to use. The Suid interface provides four object-oriented methods corresponding to the SQL language's select, update, insert, and delete operations.
- 2.By using Bee, you no longer need to write separate DAO code. You can directly call Bee's API to perform operations on the database.
- 3.Convention-over-configuration: Javabean can no annotation, no xml.
- 4.Intelligent automatic filtering of null and empty string properties in entities eliminates the need for writing code to check for non-null values.
- 5.Easily implement partial field queries and native statement pagination.
- 6.Supports returning query results in JSON format; supports chaining.
- 7.Supports Sharding, both database and table Sharding; database-only Sharding; table-only Sharding; and read-write separation. This functionality is transparent to existing code and does not require additional coding.
- 8.Easily extendable with multiple database support (MySQL, MariaDB, Oracle, H2, SQLite, PostgreSQL, SQL Server, Access, Kingbase, Dameng, etc.), and theoretically supports any database supported by JDBC. Additionally, supports Android and Harmony.
- 9.Additional database pagination support for: MsAccess, Cubrid, HSQL, Derby, Firebird, etc.
- 10.Multiple databases can be used simultaneously (e.g., MySQL, Oracle, SQL Server).
Automatic, powerful:
- 11.Dynamic/arbitrary combination of query conditions without the need to prepare DAO interfaces in advance. New query requirements can be handled without modifying or adding interfaces.
- 12.Supports transactions, using the same connection for multiple ORM operations, FOR UPDATE, batch processing, executing native SQL statements, and stored procedures.
- 13.Supports object-oriented complex queries, multi-table queries (no N+1 problem), and supports one-to-one, one-to-many, many-to-one, and many-to-many relationships. The result structure can differ based on whether the sub-table uses List;multi-table association update, insert, and delete(2.1.8).
- 14.MongoDB ORM and support for MongoDB Sharding.
- 15.Supports register, interceptor, multi-tenancy, and custom TypeHandlers for handling ResultSet results in queries. SetParaTypeConvert converts PreparedStatement parameter types.
- 16.Custom dynamic SQL tags, such as @in, @toIsNULL1, @toIsNULL2, , . Allows dynamic SQL, converting lists into statements like in (1,2,3) without requiring foreach loops. Batch insertion also does not require foreach.
- 17.Complex query can be automatically parsed by the frontend and backend.
- 18.L1 cache, simple in concept and powerful in function; L1 cache can also be fine tuned like the JVM; Support updatable long-term cache list and update configuration table without restart. Inherently resistant to cache penetration. L2 cache extension support; Redis L2 cache support.
- 19.No third-party plugin dependencies; can be used with zero configuration.
- 20.High performance: close to the speed of JDBC; small file size: Bee V1.17 is only 502k, V2.1 is only 827k.
Assist function: - 21.Additional features: 21. Provides a naturally simple solution for generating distributed primary keys: generates globally unique, monotonically increasing (within a worker ID) numeric IDs in a distributed environment.
- 22.Supports automatic generation of Javabean corresponding to tables(support Swagger), creating tables based on Javabean, and automatically generating backend Javaweb code based on templates. Can print executable SQL statements without placeholders for easy debugging. Supports generating SQL scripts in JSON format.
- 23.Supports reading Excel files and importing data into the database; simple operations. Supports generating database tables from Excel configurations.
- 24.Stream tool class StreamUtil;DateUtil date conversion, judge date format, calculate age.
- 25.Rich annotation support: PrimaryKey, Column, Datetime, Createtime, Updatetime; JustFetch, ReplaceInto (MySQL), Dict, DictI18n,GridFs, etc.
- 26.Use entity name _F (automatically generated) to reference entity field names, e.g., Users_F.name or in SuidRichExt interface using the format Users::getName.
- Chaing SQL programming supports placeholder precompilation to prevent injection attacks
- Do not cache if no table name is specified
- Add a default date sharding implementation for Calculate, and add a custom sharding implementation example
- Support ElasticSearch(7.x) ORM query
- PreparedSql support set table name for enhance relative cache
- MongoDB gen Javabean support gen comment
7.the Sharding template method class uses finally to handle context recycling
8.MapSql(MapSuid)supports using Condition to implement more complex where conditions, with updateSet set values
MapSql add methods: public void where(Condition condition);
public void updateSet(Condition condition);
9.add ConditionExt to support the use of entity::getName to reference property
ConditionExt support Condition no need hard code the field name
10.add ChainSqlFactory
11.add select Result Assembler
12.MoreTable add methods:selectWithFun,count
13.MoreTable add method List<String[]> selectString(T entity, Condition condition)
14.enhance MoreTable update
15.support property style sharding config
16.MoreTable support selectJson
17.GenBean support java.time.LocalDateTime
18.fixed bug: GenConfig baseDir default value support Linux env
19.Suid support java.time.LocalDateTime type
20.TO_DATE for Oracle filter the record in SQL where part
21.Fixed bug: MoreTable single insertion, automatic value setting before doBeforePasreEntity
InsertAndReturnId in sharding mode need setInitIdByAuto > doBeforePasreEntity
InsertAndReturnId: The pkName passed in should be converted to column name
22.enhance:
When inserting multiple tables, if there are no child tables, insert is used for inserting the main table
File generation, add backup of existing files function
TranHandler throws the received exception to the upper level
23.support pgsql json/jsonb, but in where part, need write the pgsql special sql
24.Improve the sharding function
V2.2(2024.1.1·LTS)
- Javabean entity supports inheritance (configure bee.osql.openEntityCanExtend=true).
- Enhanced the association between batch insert and transaction.
2.2 Before version 2.2, calling batch insertion would commit on each batch, but in version 2.2, it is changed to only call once within a transaction. The content of the batch insertion method is no longer committed, but is controlled by the transaction. - Fixed bugs:
- When Condition uses Op.in and the parameter is null, an exception is thrown.
- Context-related bug in sharding batch insert.
- Resolved context issues when only sharding databases.
- When sharding, the context of the main thread needs to be cleared.
- Bug with InheritableThreadLocal and parallelStream() being incompatible.In 2.2, when not in sharding mode, parallelStream() can be used, but it is not recommended to use parallelStream() when sharding.
- Move major commonly used interfaces such as Suid, SuidRich, MoreTable, PreparedSql, MapSuid, etc. to the org.teasoft.bee.osql.api package.
- Better support for MVC programming and Spring RestFul programming.
- Support configuration of multiple data sources in bee.properties (no need for XML or Java code configuration).
- GenBean supports Lombok annotations: @Setter, @Getter, @Data.
- Built-in json tool fastjson support, with the option to use a custom JSON tool.
- Generate all Java bean files for the entire database with a single line of code: new GenBean().genAllBeanFile();
- Bulk insert for broadcast table.
- Improved sharding functionality.
- Full support for MongoDB ORM.
9.1. Support for insertion and querying of geospatial information in MongoDB (including sharded queries).
9.2. Various operations on GridFs files, with support for annotations.
9.3. Direct execution of native statements (MongodbRawSql).
9.4. Logging of native statements for object-oriented operations in MongoDB.
9.5. Support for MongoDB transactions.
9.6. Support for creating and deleting indexes in MongoDB.
9.7. MongoDB beans defined as pluggable components. - Default support for pagination in more databases: MsAccess, Cubrid, HSQL, Derby, Firebird, etc.
1.MySQL
2.Oracle
3.SQL Server
4.MariaDB
5.H2
6.SQLite
7.PostgreSQL
8.MS Access
9.Kingbase
10.DM
11.OceanBase
12.Cubrid,HSQL,Derby,Firebird
13.Other DB that support JDBC
NOSQL:
14.Mongodb
15.ElasticSearch
16.Cassandra
Mobile environment (database):
17.Android
18.Harmony
Test Evn : Local windows.
DB: MySQL (Version 5.6.24).
Test point: Batch Insert;Paging Select; Transaction(update and select).
Batch Insert(unit: ms) |
|||||
| 5k | 1w | 2w | 5w | 10w | |
| Bee | 529.00 | 458.33 | 550.00 | 1315.67 | 4056.67 |
| MyBatis | 1193 | 713 | 1292.67 | 1824.33 | Exception |
Paging Select(unit: ms) |
|||||
| 20 | 50 | 100 | 200 | 500 | |
| Bee | 17.33 | 58.67 | 52.33 | 38.33 | 57.33 |
| MyBatis | 314.33 | 446.00 | 1546.00 | 2294.33 | 6216.67 |
Transaction(update and select) (unit: ms) |
|||||
| 20 | 50 | 100 | 200 | 500 | |
| Bee | 1089.00 | 70.00 | 84.00 | 161.33 | 31509.33 |
| MyBatis | 1144 | 35 | 79.67 | 146.00 | 32155.33 |
Bee need files
orm\compare\bee\service\BeeOrdersService.java
MyBatis need files
orm\compare\mybatis\service\MybatisOrdersService.java
orm\compare\mybatis\dao\OrdersDao.java
orm\compare\mybatis\dao\OrdersMapper.java
orm\compare\mybatis\dao\impl\OrdersDaoImpl.java
common,Javabean and Service interface:
Orders.java
OrdersService.java
Performance comparison data of Bee application in app development
Operate 10000 records, and the use time comparison is as follows.
Operate 10000 records(unit: ms) |
|||
| insert | query | delete | |
| greenDao(Android) | 104666 | 600 | 47 |
| Bee(Android 8.1) | 747 | 184 | 25 |
| Bee(HarmonyOS P40 Pro simulator) | 339 | 143 | 2 |
<dependency>
<groupId>org.teasoft</groupId>
<artifactId>bee-all</artifactId>
<version>2.4.0</version>
</dependency>
<!-- Mysql config.You need change it to the real database config. -->
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.47</version>
<scope>runtime</scope>
</dependency>Gradle
implementation group: 'org.teasoft', name: 'bee-all', version: '2.4.0'
//Gradle(Short)
implementation 'org.teasoft:bee-all:2.4.0'eg:
Create one database,default name is bee.
Create the tables and init the data by run the init-data(user-orders)-mysql.sql file(it is mysql sql script).
If no the bee.properties file, you can create it by yourself.
#bee.databaseName=MySQL
bee.db.dbName=MySQL
bee.db.driverName = com.mysql.jdbc.Driver
#bee.db.url =jdbc:mysql://localhost:3306/bee?characterEncoding=UTF-8
bee.db.url =jdbc:mysql://127.0.0.1:3306/bee?characterEncoding=UTF-8&useSSL=false
bee.db.username = root
bee.db.password =
#print log
bee.osql.showSQL=true
bee.osql.showSql.showType=true
bee.osql.showSql.showExecutableSql=true
# since 2.1.7 sqlFormat=true,will format the executable sql
bee.osql.showSql.sqlFormat=false
#log4j>slf4j>log4j2>androidLog>harmonyLog>systemLogger>fileLogger>noLogging>jdkLog>commonsLog
bee.osql.loggerType=systemLogger
Orders(Javabean)
Auto Genernate Javabean
import java.math.BigDecimal;
import java.util.List;
import org.teasoft.bee.osql.BeeException;
import org.teasoft.bee.osql.Suid;
import org.teasoft.honey.osql.core.BeeFactoryHelper;
import org.teasoft.honey.osql.core.Logger;
/**
* @author Kingstar
* @since 1.0
*/
public class SuidExamEN {
public static void main(String[] args) {
try {
Suid suid = BeeFactoryHelper.getSuid();
Orders orders1 = new Orders();//need gen the Javabean
orders1.setId(100001L);
orders1.setName("Bee(ORM Framework)");
List<Orders> list1 = suid.select(orders1); // 1. select
for (int i = 0; i < list1.size(); i++) {
Logger.info(list1.get(i).toString());
}
orders1.setName("Bee(ORM Framework)");
int updateNum = suid.update(orders1); //2. update
Logger.info("update record:" + updateNum);
Orders orders2 = new Orders();
orders2.setUserid("bee");
orders2.setName("Bee(ORM Framework)");
orders2.setTotal(new BigDecimal("91.99"));
orders2.setRemark(""); // empty String test
int insertNum = suid.insert(orders2); // 3. insert
Logger.info("insert record:" + insertNum);
int deleteNum = suid.delete(orders2); // 4. delete
Logger.info("delete record:" + deleteNum);
} catch (BeeException e) {
Logger.error("In SuidExamEN (BeeException):" + e.getMessage());
//e.printStackTrace();
} catch (Exception e) {
Logger.error("In SuidExamEN (Exception):" + e.getMessage());
//e.printStackTrace();
}
}
}
// notice: this is just a simple sample. Bee suport transaction,paging,complicate select,slect json,and so on. bee.db.isAndroid=true
bee.db.androidDbName=account.db
bee.db.androidDbVersion=1
bee.osql.loggerType=androidLog
#turn on query result field type conversion, and more types will be supported
bee.osql.openFieldTypeHandler=true
#If you are allowed to delete and update the whole table, you need to remove the comments
#bee.osql.notDeleteWholeRecords=false
#bee.osql.notUpdateWholeRecords=falsepublic class YourAppCreateAndUpgrade implements CreateAndUpgrade{
@Override
public void onCreate() {
// You can create tables in an object-oriented way
Ddl.createTable(new Orders(), false);
Ddl.createTable(new TestUser(), false);
}
@Override
public void onUpgrade(int oldVersion, int newVersion) {
if(newVersion==2) {
Ddl.createTable(new LeafAlloc(), true);
Log.i("onUpgrade", "你在没有卸载的情况下，在线更新到版本:"+newVersion);
}
}
}
Configure android:name to BeeApplication in AndroidManifest.xml file.
package com.aiteasoft.util;
import org.teasoft.bee.android.CreateAndUpgradeRegistry;
import org.teasoft.beex.android.ApplicationRegistry;
public class BeeApplication extends Application {
private static Context context;
@Override
public void onCreate() {
ApplicationRegistry.register(this);//注册上下文
CreateAndUpgradeRegistry.register(YourAppCreateAndUpgrade.class);
}
}
// 并在AndroidManifest.xml,配置android:name为BeeApplication
<application
android:icon="@drawable/appicon"
android:label="@string/app_name"
android:name="com.aiteasoft.util.BeeApplication"
>Suid suid=BF.getSuid();
List<Orders> list = suid.select(new Orders()); Performance comparison data of Bee application in app development
Operate 10000 records, and the use time comparison is as follows.
Operate 10000 records(unit: ms) |
|||
| insert | query | delete | |
| greenDao(Android) | 104666 | 600 | 47 |
| Bee(Android 8.1) | 747 | 184 | 25 |
| Bee(HarmonyOS P40 Pro simulator) | 339 | 143 | 2 |
V2.1
Let Java more quicker programming than php and Rails.
Faster development of new combinations for Java Web：
Bee+Spring+SpringMVC
Faster development of new combinations for Spring Cloud microservices：
Bee + Spring Boot
Rapid Application Code Generation Platform--AiTea Soft made in China!
...
API-V1.17(Newest) SourceCode contain bee-1.17 CN & EN API,bee-1.17 CN SourceCode
The use of Enterprise Edition, professional technical support and solution consultation are provided by the following companies:
Shenzhen Caifeng software
(Enterprises willing to join in, please contact us!)
Author's email: [email protected]
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db-ally
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db2rest
DB2Rest is a modern low-code REST DATA API platform that simplifies the development of intelligent applications. It seamlessly integrates existing and new databases with language models (LMs/LLMs) and vector stores, enabling the rapid delivery of context-aware, reasoning applications without vendor lock-in.
kitops
KitOps is a packaging and versioning system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using. KitOps simplifies the handoffs between data scientists, application developers, and SREs working with LLMs and other AI/ML models. KitOps' ModelKits are a standards-based package for models, their dependencies, configurations, and codebases. ModelKits are portable, reproducible, and work with the tools you already use.
kweaver
KWeaver is an open-source cognitive intelligence development framework that provides data scientists, application developers, and domain experts with the ability for rapid development, comprehensive openness, and high-performance knowledge network generation and cognitive intelligence large model framework. It offers features such as automated and visual knowledge graph construction, visualization and analysis of knowledge graph data, knowledge graph integration, knowledge graph resource management, large model prompt engineering and debugging, and visual configuration for large model access.
honey
Bee is an ORM framework that provides easy and high-efficiency database operations, allowing developers to focus on business logic development. It supports various databases and features like automatic filtering, partial field queries, pagination, and JSON format results. Bee also offers advanced functionalities like sharding, transactions, complex queries, and MongoDB ORM. The tool is designed for rapid application development in Java, offering faster development for Java Web and Spring Cloud microservices. The Enterprise Edition provides additional features like financial computing support, automatic value insertion, desensitization, dictionary value conversion, multi-tenancy, and more.
moxin
Moxin is an AI LLM client written in Rust to demonstrate the functionality of the Robius framework for multi-platform application development. It is currently in early stages of development and not fully functional. The tool supports building and running on macOS and Linux systems, with packaging options available for distribution. Users can install the required WasmEdge WASM runtime and dependencies to build and run Moxin. Packaging for distribution includes generating `.deb` Debian packages, AppImage, and pacman installation packages for Linux, as well as `.app` bundles and `.dmg` disk images for macOS. The macOS app is not signed, leading to a warning on installation, which can be resolved by removing the quarantine attribute from the installed app.
choco-builder
ChocoBuilder (aka Chocolate Factory) is an open-source LLM application development framework designed to help you easily create powerful software development SDLC + LLM generation assistants. It provides modules for integration into JVM projects, usage with RAGScript, and local deployment examples. ChocoBuilder follows a Domain Driven Problem-Solving design philosophy with key concepts like ProblemClarifier, ProblemAnalyzer, SolutionDesigner, SolutionReviewer, and SolutionExecutor. It offers use cases for desktop/IDE, server, and Android applications, with examples for frontend design, semantic code search, testcase generation, and code interpretation.
tidb
TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
infinity
Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.