surrealdb/surreal-sync
Jun 2025 – Jan 2026
7 Months active
Languages Used
BSONC++DockerfileJSONJavaScriptMarkdownRustSQL
Technical Skills
API IntegrationAsync ProgrammingBackend DevelopmentBinary Data HandlingCLI DevelopmentCargo
Yuske Kuoka
PROFILE
Yuske Kuoka
Yusuke Kuoka developed and maintained the surrealdb/surreal-sync repository, building a modular, multi-database data integration platform supporting sources like MongoDB, Neo4j, Kafka, PostgreSQL, and CSV/JSONL files. He engineered robust data pipelines and synchronization mechanisms using Rust, leveraging asynchronous programming and containerized CI/CD workflows. His work included schema-aware type systems, distributed load testing tools, and version-agnostic SurrealDB integration, all designed for reliability and maintainability. By extracting sub-crates, refactoring core modules, and automating dependency management, Yusuke improved code quality and test coverage. These efforts enabled scalable, secure data migration and synchronization across diverse environments, reducing operational risk and accelerating onboarding.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
257Total
Bugs
21
Commits
257
Features
85
Lines of code
187,967
Activity Months7
Your Network
13 peopleSame Organization
@surrealdb.com10
Emmanuel KellerMember
FarhanMember
Martin SchaerMember
Micha de VriesMember
Raphael DarleyMember
Rowan BakerMember
Rushmore MushambiMember
Sergii GlushchenkoMember
Stu SchwartzMember
Shared Repositories
3
Work History
January 2026
99 Commits • 24 Features
Jan 1, 20262026-01 Monthly Summary – surreal-sync (surrealdb/surreal-sync) Key features delivered: - SurrealDB Schema Modernization and Surreal Sub-crate: Migrated from legacy schema to surrealdb-types, extracted a dedicated surreal sub-crate for SurrealDB writing, and reorganized surreal-sync CLI commands for consistency and composability. - DB Crate Extraction and Modularization: Extracted MongoDB and Neo4j crates from the main crate, created a dedicated checkpoint crate, and moved Kafka source into sub-crates; tidied up Postgres/MySQL sources and related DB code to reduce coupling and improve maintainability. - Distributed Load Testing Tools and Improvements: Added a distributed loadtesting tool; improved visibility of wait-for-completion; refined build/docs around loadtest; fixed MongoDB loadtest to pass. - SurrealDB v2/v3 compatibility and source readiness: Introduced sub-crates to support SurrealDB v2/v3, refactored several sources for version-agnostic operation, and implemented a generic checkpoint store to stay compatible across SurrealDB versions; added TimeTz universal type/value. - Loadtest framework enhancements and CI readiness: Expanded default loadtest matrix with more sources, added a GitHub Actions loadtest harness, and improved test helpers and verification to support v2/v3 testing. Major bugs fixed: - Code quality, linting, and build stability improvements across the project. - Loadtest stability, metrics reporting, and failure-log improvements to enable reliable CI results. - Cleartext logging vulnerabilities fixed (security/compliance). - Loadtest artifact naming and intermediate file cleanup to reduce noise and improve artifacts. - CI/test stability enhancements to reduce noisy failures and flakiness. Overall impact and accomplishments: - Created a modular, version-agnostic SurrealDB integration stack that supports multiple backends (MongoDB, Neo4j, Postgres, MySQL, Kafka, MongoDB, etc.) with a unified checkpoint mechanism, enabling faster feature delivery and safer upgrades to SurrealDB v2/v3. - Significantly improved test coverage, CI reliability, and performance validation via distributed loadtesting tooling and enhanced reporting. These changes reduce risk for production deployments, accelerate integration with external systems, and improve overall product reliability. - Strengthened security posture by addressing cleartext logging risks and improved code quality across the codebase, contributing to maintainability and audit readiness. Technologies/skills demonstrated: - Rust multi-crate modularization, crate extraction, and version-agnostic design. - SurrealDB integration patterns, including generic checkpoint stores and v2/v3 compatibility tooling. - Distributed load testing design, orchestration, and metrics accuracy. - CI/CD improvements, GitHub Actions-based loadtest harness, and release workflow optimizations. - Cross-database coordination (PostgreSQL WAL2JSON, Kafka, MongoDB, Neo4j) and loadtest orchestration in Kubernetes contexts.
99 Commits • 24 Features
Jan 1, 20262026-01 Monthly Summary – surreal-sync (surrealdb/surreal-sync) Key features delivered: - SurrealDB Schema Modernization and Surreal Sub-crate: Migrated from legacy schema to surrealdb-types, extracted a dedicated surreal sub-crate for SurrealDB writing, and reorganized surreal-sync CLI commands for consistency and composability. - DB Crate Extraction and Modularization: Extracted MongoDB and Neo4j crates from the main crate, created a dedicated checkpoint crate, and moved Kafka source into sub-crates; tidied up Postgres/MySQL sources and related DB code to reduce coupling and improve maintainability. - Distributed Load Testing Tools and Improvements: Added a distributed loadtesting tool; improved visibility of wait-for-completion; refined build/docs around loadtest; fixed MongoDB loadtest to pass. - SurrealDB v2/v3 compatibility and source readiness: Introduced sub-crates to support SurrealDB v2/v3, refactored several sources for version-agnostic operation, and implemented a generic checkpoint store to stay compatible across SurrealDB versions; added TimeTz universal type/value. - Loadtest framework enhancements and CI readiness: Expanded default loadtest matrix with more sources, added a GitHub Actions loadtest harness, and improved test helpers and verification to support v2/v3 testing. Major bugs fixed: - Code quality, linting, and build stability improvements across the project. - Loadtest stability, metrics reporting, and failure-log improvements to enable reliable CI results. - Cleartext logging vulnerabilities fixed (security/compliance). - Loadtest artifact naming and intermediate file cleanup to reduce noise and improve artifacts. - CI/test stability enhancements to reduce noisy failures and flakiness. Overall impact and accomplishments: - Created a modular, version-agnostic SurrealDB integration stack that supports multiple backends (MongoDB, Neo4j, Postgres, MySQL, Kafka, MongoDB, etc.) with a unified checkpoint mechanism, enabling faster feature delivery and safer upgrades to SurrealDB v2/v3. - Significantly improved test coverage, CI reliability, and performance validation via distributed loadtesting tooling and enhanced reporting. These changes reduce risk for production deployments, accelerate integration with external systems, and improve overall product reliability. - Strengthened security posture by addressing cleartext logging risks and improved code quality across the codebase, contributing to maintainability and audit readiness. Technologies/skills demonstrated: - Rust multi-crate modularization, crate extraction, and version-agnostic design. - SurrealDB integration patterns, including generic checkpoint stores and v2/v3 compatibility tooling. - Distributed load testing design, orchestration, and metrics accuracy. - CI/CD improvements, GitHub Actions-based loadtest harness, and release workflow optimizations. - Cross-database coordination (PostgreSQL WAL2JSON, Kafka, MongoDB, Neo4j) and loadtest orchestration in Kubernetes contexts.
January 2026
December 2025
45 Commits • 15 Features
Dec 1, 2025December 2025 (surreal-sync) — This month focused on enabling robust data integration at scale and improving developer productivity. Achievements span testing, incremental sync, data modeling, core type system, and CI/testing workflows, all aligned to deliver business value through reliable data synchronization, flexible schema control, and stronger type safety.
December 2025
45 Commits • 15 Features
Dec 1, 2025December 2025 (surreal-sync) — This month focused on enabling robust data integration at scale and improving developer productivity. Achievements span testing, incremental sync, data modeling, core type system, and CI/testing workflows, all aligned to deliver business value through reliable data synchronization, flexible schema control, and stronger type safety.
November 2025
6 Commits • 3 Features
Nov 1, 2025Month: 2025-11 — surreal-sync (surrealdb/surreal-sync) delivered targeted data ingestion enhancements and code quality improvements, delivering tangible business value through more flexible data import workflows and a more maintainable Rust codebase. Key features delivered: - CSV Import Enhancements: metrics collection for CSV import; multi-source CSV import (HTTP/HTTPS, local, S3); support for predefined column names when CSV has no headers with validation; source moved to sub-crate along with additional HTTP support. (Commits: 3812474e7fc26bbe34a5c1e0642cbcd7e61db11b; c4b7a7b6d0be93b459365efabbe6df0433281d03; 181e441c95845821e9cf7bbdbd7553d9a799652f) - JSONL Import Enhancements: JSONL data import via a new sub-crate, including conversion rules to SurrealDB references and support for importing from JSONL files; HTTP and S3 passthrough added. (Commits: c7a0f294d1afcc48dd28bcb027ffa8afa25914df; 7d919d7c2da25b2f56d698ce0564126156e4d6dd) - Code Quality Improvements: address Clippy lint issues across workspaces to improve Rust coding standards and maintainability. (Commit: bc89da4b171b95c8678cd051da73d31e758a9761) Major bugs fixed / quality improvements: - Systematic Clippy lint fixes across the workspaces, resulting in cleaner builds and fewer regressions during integration. Overall impact and accomplishments: - Modularity: moved CSV/JSONL sources into dedicated sub-crates to improve build times, testing, and future extensibility. - Enhanced data ingestion capabilities: multi-source CSV/JSONL support with validation enables broader data pipelines and reduces manual data wrangling. - Strengthened code health: enforced Rust best practices and maintainability, setting up a solid baseline for future features. Technologies/skills demonstrated: - Rust, Clippy linting, multi-crate modularization, cross-source data ingestion (HTTP/HTTPS, local, S3), CSV/JSONL parsing and conversion to SurrealDB references, and metrics instrumentation.
6 Commits • 3 Features
Nov 1, 2025Month: 2025-11 — surreal-sync (surrealdb/surreal-sync) delivered targeted data ingestion enhancements and code quality improvements, delivering tangible business value through more flexible data import workflows and a more maintainable Rust codebase. Key features delivered: - CSV Import Enhancements: metrics collection for CSV import; multi-source CSV import (HTTP/HTTPS, local, S3); support for predefined column names when CSV has no headers with validation; source moved to sub-crate along with additional HTTP support. (Commits: 3812474e7fc26bbe34a5c1e0642cbcd7e61db11b; c4b7a7b6d0be93b459365efabbe6df0433281d03; 181e441c95845821e9cf7bbdbd7553d9a799652f) - JSONL Import Enhancements: JSONL data import via a new sub-crate, including conversion rules to SurrealDB references and support for importing from JSONL files; HTTP and S3 passthrough added. (Commits: c7a0f294d1afcc48dd28bcb027ffa8afa25914df; 7d919d7c2da25b2f56d698ce0564126156e4d6dd) - Code Quality Improvements: address Clippy lint issues across workspaces to improve Rust coding standards and maintainability. (Commit: bc89da4b171b95c8678cd051da73d31e758a9761) Major bugs fixed / quality improvements: - Systematic Clippy lint fixes across the workspaces, resulting in cleaner builds and fewer regressions during integration. Overall impact and accomplishments: - Modularity: moved CSV/JSONL sources into dedicated sub-crates to improve build times, testing, and future extensibility. - Enhanced data ingestion capabilities: multi-source CSV/JSONL support with validation enables broader data pipelines and reduces manual data wrangling. - Strengthened code health: enforced Rust best practices and maintainability, setting up a solid baseline for future features. Technologies/skills demonstrated: - Rust, Clippy linting, multi-crate modularization, cross-source data ingestion (HTTP/HTTPS, local, S3), CSV/JSONL parsing and conversion to SurrealDB references, and metrics instrumentation.
November 2025
October 2025
54 Commits • 19 Features
Oct 1, 2025October 2025 highlights: Delivered a robust set of features enabling Kafka-based data ingestion and streamlined SurrealDB integration, complemented by foundational PostgreSQL replication groundwork and significant CI/dev experience improvements. Key features include Kafka source integration with a dedicated sub-crate, proto extensions and timestamp handling, and end-to-end tests; SurrealDB integration enhancements through module reorganization and consolidated connection code; incremental sync overhaul with additional sources and improved test stability; and PostgreSQL replication groundwork including a new sub-crate, custom types, timestamptz/timestamp parsing, and at-least-once delivery guarantees. Dev experience improvements include Ubuntu 24.04 ARM CI, Kafka service in devcontainer, clippy/backtrace enhancements, and updated test/doc tooling. These efforts collectively increase data-source onboarding velocity, reliability of durable-sync paths, and developer productivity while reducing maintenance overhead.
October 2025
54 Commits • 19 Features
Oct 1, 2025October 2025 highlights: Delivered a robust set of features enabling Kafka-based data ingestion and streamlined SurrealDB integration, complemented by foundational PostgreSQL replication groundwork and significant CI/dev experience improvements. Key features include Kafka source integration with a dedicated sub-crate, proto extensions and timestamp handling, and end-to-end tests; SurrealDB integration enhancements through module reorganization and consolidated connection code; incremental sync overhaul with additional sources and improved test stability; and PostgreSQL replication groundwork including a new sub-crate, custom types, timestamptz/timestamp parsing, and at-least-once delivery guarantees. Dev experience improvements include Ubuntu 24.04 ARM CI, Kafka service in devcontainer, clippy/backtrace enhancements, and updated test/doc tooling. These efforts collectively increase data-source onboarding velocity, reliability of durable-sync paths, and developer productivity while reducing maintenance overhead.
August 2025
2 Commits • 2 Features
Aug 1, 2025Month: 2025-08 — Surreal Sync (surrealdb/surreal-sync) delivered two major features focused on maintainability and security, with no major bugs fixed this period. The work emphasizes transparency for contributors and automation of dependency updates to reduce risk.
2 Commits • 2 Features
Aug 1, 2025Month: 2025-08 — Surreal Sync (surrealdb/surreal-sync) delivered two major features focused on maintainability and security, with no major bugs fixed this period. The work emphasizes transparency for contributors and automation of dependency updates to reduce risk.
August 2025
July 2025
16 Commits • 6 Features
Jul 1, 2025July 2025 monthly summary for surreal-sync: Delivered critical data integration and developer experience enhancements across Neo4j, MongoDB, JSONL, and CI/CD tooling. Focused on data fidelity, reliability, and streamlined release processes, enabling faster migrations and more robust deployments for customers and internal teams.
July 2025
16 Commits • 6 Features
Jul 1, 2025July 2025 monthly summary for surreal-sync: Delivered critical data integration and developer experience enhancements across Neo4j, MongoDB, JSONL, and CI/CD tooling. Focused on data fidelity, reliability, and streamlined release processes, enabling faster migrations and more robust deployments for customers and internal teams.
June 2025
35 Commits • 16 Features
Jun 1, 2025June 2025: Delivered foundational multi-database integration (MongoDB and Neo4j) for surreal-sync, improved test reliability and parallelism, advanced data-type and binary support, and aligned documentation. Built a modular Rust codebase (mongodb.rs, neo4j.rs), established devcontainer for consistent local development, and prepared for broader SurrealDB compatibility. Business value: faster integration with external sources, stronger data fidelity, and more predictable CI.
35 Commits • 16 Features
Jun 1, 2025June 2025: Delivered foundational multi-database integration (MongoDB and Neo4j) for surreal-sync, improved test reliability and parallelism, advanced data-type and binary support, and aligned documentation. Built a modular Rust codebase (mongodb.rs, neo4j.rs), established devcontainer for consistent local development, and prepared for broader SurrealDB compatibility. Business value: faster integration with external sources, stronger data fidelity, and more predictable CI.
June 2025
Activity
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Quality Metrics
Correctness93.2%
Maintainability88.2%
Architecture90.4%
Performance84.0%
AI Usage25.4%
Skills & Technologies
Programming Languages
BSONBashC++DockerfileJSONJavaScriptMakefileMarkdownProtobufPython
Technical Skills
API DevelopmentAPI IntegrationAPI designAPI developmentAWS S3AWS SDKAsync ProgrammingAsynchronous ProgrammingAutomationBSONBackend DevelopmentBinary Data HandlingBuild SystemsCI/CDCLI Argument Parsing
Repositories Contributed To
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