This article analyzes six public benchmark datasets comparing HTTP/1.1+JSON (REST) against binary protocols like gRPC+Protobuf and Dubbo, showing gRPC achieves roughly 2x throughput and half the latency, but argues the gap is often negligible in real business scenarios where database and logic dominate latency.
This article benchmarks PostgreSQL JSON and JSONB types on 1 million rows, revealing JSONB delivers 6-9x faster queries and 26% less storage despite 31% slower writes, with practical guidance on when to choose each type and how to leverage GIN indexes for optimal performance.
This article argues that SQLite, often dismissed as a toy database, can replace specialized systems like Elasticsearch, MongoDB, Kafka, ClickHouse, Redis, and even microservices due to its stability, zero-configuration deployment, built-in full-text search, JSON support, vector extensions, and local-first architecture, reducing operational complexity.
This article details the practical challenges and solutions when migrating from Spring Boot 3.x to 4.x, focusing on the Jackson 2 to 3 transition including package changes, exception handling updates, annotation exceptions, immutable ObjectMapper configuration, and coexistence strategies for legacy dependencies.
The article explains how the old pattern of GET‑ing an entire JSON string from Redis, deserializing it in Java, modifying a single field and writing it back is inefficient and error‑prone, and shows how Spring Data Redis 4.2’s RedisJsonTemplate lets you update or read individual JSON paths directly, reducing code, network traffic and race‑condition risks.
Microsoft’s WSL 2.9.9 preview adds Docker‑style commands, timestamped logs, JSON volume listings, container lifecycle fixes, and network failure visibility, signaling a shift toward native Docker‑compatible container experiences on Windows, while also introducing compatibility risks for scripts that depend on the previous JSON schema.
Go 1.25 introduces a second version of the json package with new capabilities, API fixes, and performance improvements, but also many breaking changes; this article walks through the core differences, migration pitfalls, new streaming interfaces, option controls, tag extensions, custom codecs, default behavior shifts, and performance considerations.
Go 1.27 introduces generic methods, struct‑literal key selectors, expanded function‑type inference, a complete rewrite of the JSON package with encoding/json/v2, native post‑quantum signature support, a GA goroutine‑leak detector, 30 % faster small‑object allocation, and numerous toolchain and ecosystem refinements that together reshape the language, standard library, runtime, and developer experience.
Go 1.27, released on August 20, introduces generic methods, a revamped JSON v2 library, up to 30% faster small‑object memory allocation, a universally available goroutine‑leak profile, new cryptographic packages, a built‑in UUID library, experimental SIMD types, and numerous standard‑library and toolchain enhancements.
After a five‑year experimental phase, Go’s new json/v2 package becomes the default in Go 1.27; the author traces its history, presents on‑machine benchmark comparisons showing faster struct unmarshalling but slower map handling, and reveals three undocumented issues—including format‑tag removal, altered UTF‑8 output, and map[string]any slowdown—that developers must consider when migrating.
The article explains why Spring Boot continues to use Jackson as its default JSON serializer, detailing the automatic ObjectMapper/JsonMapper creation, the HTTP message conversion process, Jackson’s balanced strengths, practical code samples, and how to switch to alternatives like Gson, JSON‑B, or Fastjson2.
Security researchers disclosed a remote code execution flaw in fastjson 1.2.66‑1.2.83 that bypasses autoType, exploits @JSONType with Spring Boot’s LaunchedURLClassLoader, and works on JDK 8, providing detailed payloads, proof‑of‑concept scripts, detection tools, and mitigation recommendations.
This article explains the major breaking changes introduced in Jackson 3—including the JDK 17 baseline, package and groupId renames, immutable JsonMapper, unchecked exceptions, default configuration shifts, performance tweaks, and module consolidation—while providing step‑by‑step migration advice and a quick‑reference table for developers upgrading from Jackson 2.
The author shares a light‑colored Codex theme with a Maple Mono font, explains why a brighter background eases eye strain, shows screenshots, and provides the exact JSON configuration and import steps for applying the theme.
A flame‑graph reveals that in high‑throughput services only about 30% of CPU time is spent on business logic while the rest is consumed by serialization, prompting a step‑by‑step evolution from flexible JSON to compact binary formats, zero‑copy techniques, and selective compression to keep costs under control at tens of millions of requests per second.
This article presents four practical solutions for the Spring Boot 3.5.0 “Could not write JSON: failed to lazily initialize a collection… no Session” error that occurs when serializing bidirectional one-to-many relationships, covering @JsonIgnore, JPQL fetch joins, enabling OpenEntityManagerInView, and using the Jackson Hibernate6 module, with code examples and results.
The article explains why front‑end/back‑end separation is needed, outlines the challenges of the MVC era, describes the SPA‑based separation model, and provides a detailed, versioned interface specification—including request/response formats, mock server workflow, and special field rules—to streamline collaborative development.
A developer created an open‑source AI Agent Skill that scrapes real‑time data from the 2026 North‑American World Cup, normalizes it into JSON, and lets anyone ask natural‑language questions about matches, teams, players, and statistics, all with a single command‑line install.
This article demonstrates four techniques for persisting flexible JSON data in Spring Boot 3.5.0—using JPA @Convert with AttributeConverter, Hibernate @JdbcTypeCode, a custom MyBatis TypeHandler, and MyBatis‑Plus annotations—complete with code snippets, test cases, and execution results.
This article compiles a curated list of 20 widely used Java libraries—covering logging, JSON processing, testing, utilities, HTTP, XML, Excel, bytecode manipulation, connection pooling, messaging, PDF, date‑time, collections, email, HTML parsing, cryptography, embedded databases, JDBC debugging, serialization, and networking—to help developers avoid reinventing the wheel and boost productivity.
FastJSON is a high‑performance PHP 8.3+ JSON extension that serves as a drop‑in replacement for ext/json, offering namespaced fastjson_* APIs, full compatibility with json_last_error, and delivering up to six‑fold speed gains in encoding, decoding, and validation while detailing installation steps, supported flags, memory trade‑offs, and benchmark results.
This article walks through the rationale, common functions, and real‑world case studies of storing and querying JSON columns in a relational database, exposing issues with null handling, batch updates, and dynamic SQL generation, and presents step‑by‑step debugging and robust solutions.
When a high‑traffic Django endpoint that returned a 7 MB JSON payload slowed dramatically, the author traced the bottleneck to a misuse of StreamingHttpResponse that iterated over the response string character‑by‑character, and fixing it with a simple list wrapper or HttpResponse yielded up to an eight‑fold speedup.
This article explains how Spring MVC’s @RequestBody annotation is a universal entry point for HTTP request bodies, supporting JSON, XML, plain text, binary streams, maps, lists, and custom media types through its HttpMessageConverter mechanism, with concrete code examples and configuration details.
The article examines how JSON, once the universal data language for backend systems, is being pushed back from the interaction layer in AI‑driven applications, outlines its five key shortcomings, and explores emerging alternatives such as natural‑language interfaces, Markdown, YAML, and function calling.
The article explains why LLMs often produce malformed JSON, categorizes three common failure types, and walks through modern solutions—including withStructuredOutput + Zod, JsonOutputParser, and OutputFixingParser—plus a decision tree to choose the right approach for production use.
This article presents ten practical MySQL advanced techniques—including EXPLAIN analysis, composite and covering indexes, index condition push‑down, prefix indexes, window functions, CTEs, JSON handling, partition tables, join optimizations, variables, online DDL, and generated columns—each illustrated with real‑world SQL examples and execution‑plan screenshots to boost efficiency in high‑volume, high‑concurrency environments.
This comprehensive guide walks you through why Jackson annotation tweaks are essential, presents a full annotation hierarchy, demonstrates over 25 core annotations with concrete code examples, covers polymorphic handling, special scenarios, global Spring Boot 3 configuration, production best practices, common pitfalls, performance tips, an end‑to‑end e‑commerce example, and testing strategies, all aimed at mastering JSON serialization in Spring Boot.
This article explains how to store and query extensible JSON columns in a MySQL‑based system, lists the most useful JSON functions, walks through several real‑world scenarios—including dynamic extension queries and weight‑management cases—identifies subtle bugs caused by null values, and presents step‑by‑step SQL and MyBatis fixes to ensure reliable batch updates.
Easy Work is a Java workflow engine that offers a simple API and modular components, enabling developers to create, execute, pause, and serialize complex workflows using code, JSON definitions, and rich conditional predicates, with detailed examples covering repeat, sequential, parallel, and conditional flows.
A performance bottleneck hidden in a fintech dashboard’s “coffee‑time” API was solved by profiling, discovering that 85% of latency came from JSON serialization, and replacing it with MessagePack, which reduced payload size by up to 74% and slashed end‑to‑end response time from 847 ms to 159 ms—a more than five‑fold improvement.
This guide enumerates ten frequent traps encountered when streaming JSON in Node.js—such as assuming one chunk per object, UTF‑8 split issues, missing newline delimiters, back‑pressure overload, and handling of large numbers—and presents reliable patterns like using NDJSON framing, StringDecoder, pipeline, and proper error handling to avoid data loss and memory spikes.
The article explains how Lombok’s @Data annotation generates getter and setter methods with a lowercase first letter for camel‑case fields, causing Jackson to serialize JSON property names in all lowercase, and offers three fixes: write methods manually, use @JsonProperty, or rename fields to avoid lower‑upper patterns.
This article demonstrates how to use MySQL's JSON data type and spatial extensions to store semi‑structured and geographic data, create indexes, write optimized queries, and combine both features to build flexible GIS solutions, with complete code examples and performance tips.
The article examines Go 1.26’s release, explains why the experimental encoding/json/v2 package remains hidden, details its architectural redesign, key new features, performance gains, critical blockers such as a memory‑regression issue, and outlines the realistic timeline for its stable inclusion in Go 1.27.
This article walks through eight often‑overlooked Go language nuances—ranging from direct integer iteration and generic type constraints to UTF‑8 string length, nil interface pitfalls, safe nil method calls, time.After resource leaks, empty‑struct semaphores, and JSON field omission—showing concrete code examples, common mistakes, and recommended practices.
This article explains how to design a consistent JSON response format for Spring Boot APIs, covering status‑code conventions, message handling, a reusable Result wrapper class, controller simplification, and a global @ResponseResult annotation with interceptor and advice for automatic response packaging.
This article presents eleven practical MySQL advanced techniques—including EXPLAIN analysis, sophisticated indexing, window functions, CTEs, JSON handling, partitioning, join optimizations, user variables, online DDL, and generated columns—to help developers dramatically improve query performance and scalability in high‑load environments.
This article introduces Easy Work, a Java workflow engine, explaining its core concepts, showing how to define work units, compose complex sequential, parallel, and conditional flows, use breakpoints to pause execution, and construct workflows via JSON with complete code examples and repository links.
This guide explains how to clean a Chinese poetry corpus—removing special characters, filtering short entries, and converting traditional characters to simplified Chinese—using Python validation functions, batch file processing, and WSL‑based OpenCC conversion, then persisting the results as JSON.
The article explains what TOML is, why developers are moving away from JSON and YAML for configuration files, shows how to read TOML in Python with the built‑in tomllib module, and discusses its adoption across Python, Rust, and DevOps ecosystems.
Analyzing GitHub trending data, the article shows TypeScript/JavaScript powers about 75% of top AI Agent projects, while Rust accounts for less than 2%, and explains that JSON friendliness, development velocity, and ecosystem fit make TS the preferred language for building flexible, full‑stack agents.
This guide introduces Easy Work, a Java workflow engine, explains its core concepts, shows how to create custom Work units, assemble repeat, sequential, parallel, and conditional flows, pause execution with breakpoints, and define workflows in JSON with complete code examples.
When a tens‑million‑row order table needs a new business column, directly running ALTER TABLE can lock the table and disrupt services, so the article explores master‑slave promotion, online DDL tools, schema‑less JSON extensions, and a clever use of an existing redundant column to achieve the change safely.
This article outlines ten frequent JSON pitfalls—from deeply nested structures and string literals to missing timezone data and lack of versioning—provides clear before‑and‑after code examples, and offers practical guidelines to write cleaner, safer, and more maintainable JSON for APIs and configuration files.
After upgrading to Spring Boot 4, the article explains why both Jackson 2 and Jackson 3 appear together, outlines the four major breaking changes—including package reorganization, the shift from ObjectMapper to JsonMapper, new default date serialization, and the removal of checked exceptions—and offers migration tips.
The article explains the hidden pitfalls of using JSON.parse(JSON.stringify(obj) for deep cloning in JavaScript—such as circular references, loss of special types, prototype chain, and collection handling—and introduces the native structuredClone API as a more reliable alternative.
Spring Boot 4 upgrades its default JSON processor to Jackson 3, introducing new package names, immutable builders, ISO‑8601 date serialization, and removal of checked exceptions, while preserving annotation compatibility for a smooth migration.
When a core order table with tens of millions of rows needs a new business field, executing a plain ALTER TABLE can lock the table and disrupt services, so the article explores master‑slave switching, online schema‑change tools, extension tables, JSON fields, and a clever reuse of an existing redundant column to achieve the change with minimal risk.
This tutorial walks through Jackson usage in Spring Boot 3, covering annotations for ignoring fields, renaming properties, custom serialization/deserialization, constructor handling, property visibility, date formatting, efficient JSON read/write, and enum handling with clear code samples and output screenshots.
This guide explains how to perform bidirectional conversion between JSON and CSV in Spring Boot using lightweight open‑source libraries such as Jackson, Apache Commons CSV or OpenCSV, as well as commercial APIs, covering serialization, deserialization, custom handling of nested objects, and provides complete code examples.
This article explains the A2UI (Agent‑to‑UI) protocol, a declarative JSON‑based UI description format that enables AI agents to generate and update interactive interfaces safely across platforms, detailing its challenges, design principles, workflow examples, and its relationship with AG‑UI and CopilotKit.
Choosing between PostgreSQL and MySQL isn’t just a feature checklist; it requires weighing business complexity, team expertise, and future uncertainty, with this guide offering core design philosophies, multi-dimensional capability comparisons, actionable decision paths, and real-world case studies to help you make a production-grade database choice.
This guide explains five ways to persist PHP arrays in a database—including serialize(), JSON encoding, normalized relational tables, comma‑separated strings, and Base64‑encoded data—detailing code examples, required field types, insertion steps, and retrieval techniques.
Discover ten powerful MySQL features—including CTEs, window functions, conditional aggregation, JSON handling, generated columns, and UPSERT tricks—illustrated with real‑world examples and performance tips, so you can write SQL that is more efficient, maintainable, and production‑ready.
When a core order table with tens of millions of rows needs a new column, naïve ALTER TABLE can lock the table and disrupt services, so this article explores safe alternatives such as master‑slave switching, online DDL tools, extension tables, JSON‑based schema‑less designs, and clever reuse of existing redundant fields, complete with practical code snippets and lessons learned.
The article explains the hidden pitfalls of using JSON.parse(JSON.stringify(obj)) for deep cloning in JavaScript, such as circular references, loss of special types, prototype chain, and collection handling, and introduces the native structuredClone API as a more reliable solution.
Discover eight powerful, lesser‑known MySQL 8.0 features—including window functions, descending indexes, generated columns, invisible indexes, hints, resource groups, LATERAL JOIN, and multi‑valued JSON indexes—that can dramatically improve query performance, simplify code, and give you an edge in interviews and production environments.
This guide explains how to use Alibaba's open‑source DataX tool to synchronize large MySQL datasets, covering the tool’s architecture, installation on Linux, job configuration with JSON, full‑load and incremental sync examples, and performance results, all without relying on mysqldump or manual storage methods.
The article explains how confusing the literal string "null" with a true null value in user registration requests can let invalid accounts slip through validation, leading to downstream errors and highlighting the need for proper input checks.
This article explains how JSON.parse and JSON.stringify work, outlines their performance, type, and security limitations, and presents practical strategies such as reviver functions, streaming parsers, binary formats, Web Workers, and incremental loading to achieve faster and safer JavaScript deserialization.
This article presents seven practical DuckDB SQL patterns—querying files directly, treating partition folders as tables, deduplicating with QUALIFY, computing rolling metrics with window functions, pivot/unpivot, handling JSON arrays, and exporting results to Parquet—plus tips and a mini case study that show how to turn a notebook into a lightweight OLAP engine without leaving the Python environment.
The article explains why technical terms like API, JSON, and log can feel alien during developer‑ops conversations, and offers three practical strategies—building a personal glossary, asking smart questions, and using browser dev tools—to become an effective technical translator and improve bug‑reporting efficiency.
QLExpress4, the latest major rewrite of Alibaba's Java rule engine, dramatically improves compilation and execution speed, adds expression tracing for AI-friendly debugging, supports native JSON syntax for complex data structures, and provides extensive testing, documentation, and integration examples, demonstrating its continued strong demand and adoption across major Alibaba services.
StarRocks 4.0 introduces FlatJSON, a columnar storage and execution engine that converts high‑frequency JSON fields into native columns, dramatically reducing I/O and CPU costs and enabling JSON queries to run with performance close to that of traditional columnar data.
This article walks through advanced Jackson techniques for JSON processing in Spring Boot 3, including path queries, multi‑value extraction, view control, dynamic property handling, object unwrapping, and raw JSON insertion, each illustrated with concise JUnit test examples and expected outputs.
This article presents ten practical MySQL techniques—from using JSON columns for flexible data to leveraging CTEs, window functions, and advanced clauses like WITH ROLLUP and INSERT IGNORE—each illustrated with real‑world scenarios and ready‑to‑run SQL code to improve query efficiency and developer productivity.
This article explains how to control enum serialization and deserialization in Spring Boot 3, covering default output, @JsonFormat, @JsonValue, custom serializers and deserializers, as well as @JsonProperty, @JsonCreator, and practical code examples.
This article explains how to fine‑tune JSON responses in Spring Boot 3 using Jackson annotations such as @JsonProperty, @JsonFormat, @JsonView, and Mix‑ins, covering field hiding, renaming, null handling, date/number formatting, view‑based serialization, and custom ObjectMapper configuration with code examples.
This article describes how the author streamlined multilingual resource handling for a ticketing and hotel project by replacing manual Excel‑based workflows with a Node.js script that generates JSON locales, enforces key naming conventions, and runs with a single command, dramatically improving efficiency.
This article explains how JSON.parse and JSON.stringify work, outlines their performance, type, and security limitations, and presents advanced techniques such as reviver functions, streaming parsers, binary formats, Web Workers, and incremental loading to achieve faster and safer JavaScript deserialization.
This article explains why JSON field mismatches cause backend failures in microservice architectures and presents three robust Spring Boot solutions—using a Map, Jackson's JsonNode, and @JsonAnySetter/@JsonAnyGetter—to flexibly and safely adapt dynamic JSON structures.
This article dives into advanced Jackson capabilities for Spring Boot 3, covering file, stream, byte array, URL, typed Map, JsonNode, ObjectNode, and streaming JsonParser techniques, each illustrated with concise code examples to help developers build robust, flexible JSON handling in backend services.
This article explains how to structure API responses in a microservice environment by using a standard JSON format, custom status code ranges, a Result wrapper class, and Spring annotations with interceptors to automatically package and handle responses and errors in a clean, maintainable way.
This article explains MySQL’s native JSON data type introduced in 5.7, covering its binary storage format, built‑in functions, generated‑column indexing, performance advantages over string storage, and detailed CRUD examples with SQL syntax and practical code snippets.
This article explains three frequent MySQL table‑design errors—choosing wrong data types and lengths, missing or redundant indexes, and improper storage structures—illustrating how they affect storage, query speed, and scalability, and offers practical guidelines to prevent them.
This article explains how a smart, three‑layer JSON alignment algorithm automatically reorders and matches elements to remove false differences caused by array order, delivering high accuracy, low false‑positive rates, and strong performance for backend data comparison tasks.
This article explains how to handle JSON objects with unknown or dynamic fields in Java using Jackson's @JsonAnySetter to collect extra properties into a Map and @JsonAnyGetter to serialize them back as regular fields, complete with practical code examples and common pitfalls.
This article demonstrates how to use Jackson's JsonNode tree model within Spring Boot 3, covering node creation, conversion from JSON strings and Java objects, tree manipulation—including adding, editing, and deleting nodes—and serialization back to JSON, with complete code examples for each operation.
This article demonstrates how to use four lesser‑known Jackson annotations—@JsonAppend, @JsonNaming, @JsonPropertyDescription, and @JsonPOJOBuilder—to extend JSON serialization, customize property naming, enrich JSON Schema documentation, and deserialize immutable objects within Spring Boot 3 applications.
This article explains the hidden pitfalls of using JSON.parse(JSON.stringify) for deep cloning in JavaScript—such as circular references, loss of special types, prototype chain erosion, and broken collections—and introduces the native structuredClone API as a more reliable solution.
This article explores Go's map type in depth, covering its underlying hash table mechanics, key requirements, concurrency considerations, and a comprehensive set of practical techniques—including existence checks, JSON conversion, sorting, slicing, multi-dimensional maps, and real-world examples for analytics and log processing.
This article explains why C++ developers should adopt third‑party libraries like RapidJSON for high‑performance JSON handling and pugixml for lightweight XML processing, covering integration steps, core APIs, and detailed code examples for parsing, generating, and traversing data structures.
JSON has become the de‑facto format for data exchange, and modern relational databases like PostgreSQL and MySQL now support native JSON types alongside NoSQL solutions such as MongoDB, offering developers flexible storage, indexing, and query capabilities while balancing schema rigidity, performance, and scalability.
The article analyzes the long‑standing issues of Go's original encoding/json package, explains the design and API of the experimental encoding/json/v2 and jsontext packages, and shows how the new implementation improves correctness, flexibility, and performance while preserving compatibility.
This article explains PHP's evolution of JSON handling, introduces the native json_validate() function in PHP 8.3, outlines its advantages and best‑practice usage, and predicts further enhancements expected in the upcoming PHP 8.5 Alpha 4 release.
Redis 8.0, released on May 1, 2025, introduces a major license shift to AGPLv3, eight new native data structures—including vector sets, JSON, and time‑series—alongside a rebuilt query engine that delivers up to 16‑fold performance gains, enhanced security, and cloud‑native capabilities.
This guide explains why MySQL cannot index JSON columns directly and demonstrates two practical work‑arounds—using generated columns in MySQL 5.7 and functional indexes in MySQL 8.0.13—to efficiently index a nested request.email field for fast queries.
This article walks through the most common Jackson annotations for Spring Boot 3, explaining their purpose, showing concise code samples, and demonstrating the resulting JSON output with screenshots, so developers can confidently handle naming, ignoring, formatting, dynamic properties, and custom serialization in their APIs.
This article provides a comprehensive guide to using Jackson for JSON processing in modern Java applications, covering typical scenarios such as object serialization, date formatting, nested structures, dynamic field filtering, tree model manipulation, a complete utility class, and best‑practice recommendations.
This article walks through a real‑world Python problem of extracting nested soccer odds from a JSON file, comparing pandas read_json, jsonpath, and regex approaches, and ultimately presenting a complete pandas‑based solution that normalizes the data, cleans it with a helper function, and exports it to CSV.
This article introduces the lightweight Jackson‑jr library for Java, demonstrates how to create JSON objects and arrays, use the Composer API, customize serialization with annotations, and presents JMH performance comparisons showing Jackson‑jr’s superior speed over Jackson‑databind and Gson in Spring Boot 3.4.2 environments.
This guide explains when to use Grafana's Stat panel, walks through creating and styling it in the browser, details orientation, text, color, and graph options, shows standard settings and value mappings, and provides a complete JSON configuration example for effective monitoring.
This article explains how the Go dyno package lets you effortlessly read, modify, and serialize deeply‑nested JSON/YAML structures by providing Get, Set, Delete, Append and conversion utilities that work with map[string]interface{}, map[interface{}]interface{} and []interface{} without using reflection.
This guide explains how to efficiently preprocess, index, and query massive JSON logs in Alibaba Cloud Log Service (SLS) using flattening, ingestion processors, data processing tasks, powerful JSON functions, unnesting, and the AI‑driven SQL Copilot to turn raw log data into actionable insights.
This tutorial walks you through installing MySQL REST Service on Oracle Linux, configuring the metadata schema, using MySQL Shell in VS Code, loading the component, managing variables, handling X‑protocol settings, creating services, and authenticating via MRS, MySQL Internal, cookie or JWT, with full command‑line examples and code snippets.
This guide explains how to efficiently process and analyze massive JSON logs in Alibaba Cloud Log Service (SLS) by flattening data before storage, configuring indexes, leveraging powerful JSON extraction functions, using unnest for array analysis, and employing the AI‑driven SQL Copilot to generate optimal queries, all with practical code examples.
This article explains why converting a YAML document containing both numeric and string keys (e.g., 1 and "1") to JSON fails in Go using yaml.v3, demonstrates the resulting errors, and shows how to resolve the issue with dyno.ConvertMapI2MapS or alternative libraries, while also comparing behavior in Python and JavaScript.
FlowLong is a domestically developed, high‑performance workflow engine that uses JSON‑based process models and a visual designer to simplify complex approval scenarios, integrates seamlessly with Spring Boot and Mybatis‑Plus, provides extensive BPMN features, and includes detailed installation, architecture, and database schema documentation.
This tutorial shows how to store, query, and manipulate JSON data in PostgreSQL using JPA and Hibernate, covering native JSON/JSONB types, the Hypersistence JsonType, entity mapping, service and REST layers, WildFly configuration, and curl‑based testing.
