milvus-io/milvus - Open Source PR Review Scorecard

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

C-Rank Grade: A (Welcoming) - 67/100

External PR Merge Rate: 66%

Response Time: 16h

First Timer Success: 44%

Frequently Asked Questions

Is milvus-io/milvus welcoming to first-time open-source contributors?

milvus-io/milvus has a recorded first-timer success rate of 43.7%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in milvus-io/milvus respond to incoming external pull requests in approximately 15.8 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 66.9 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 66.9 places milvus-io/milvus in the A tier.

What is the external contributor pull request merge rate for milvus-io/milvus?

The external contributor pull request merge rate for milvus-io/milvus is 66.4%, based on public PR activity from non-core contributors.

Are there Good First Issues available in milvus-io/milvus?

milvus-io/milvus currently has 17 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

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AI Maintainer Review Guidelines

Review Persona

Strict Quality Architect

Warmth Score
6.4/10
Patience Score
7.1/10
Nitpick Rate
45%

Rigorous architecture standards (70% critical review signals). Ensure PRs strictly follow guidelines before requesting review in milvus-io/milvus.

Top PR Submission Do's

  • •Add unit tests with >80% coverage for modified code paths
  • •Run repository linter and code formatters locally before pushing
  • •Link relevant GitHub issue ID in PR description pre-flight checklist

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without referencing an existing issue
  • •Do not mix refactoring and feature logic into a single commit
  • •Do not ping maintainers repeatedly within 24 hours of opening
Response Velocity
15 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
66.4%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
43.7%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
81 core
Highly collaborative maintainer core
Diagnostic Health HUD
66.4%
Merge Gauge
43.7%
1st-Timer
Community Vibe58/100

Embed C-Rank Badge

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GetMerged C-Rank badge for milvus-io/milvus
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Active Good First Issues (5)

View on GitHub

Is there an existing issue for this? I have searched the existing issues. No directly matching open issue was identified in the catalog duplicate check. Recheck the target branch and in-flight PRs with a maintainer before claiming this task. Project Catalog ID: F01 Difficulty: easy Estimated incremental effort: 3–5 hours Make a bounded Lance dataset import runnable through the existing Parquet importer. Implementation scope Open an explicit dataset version and stream live rows/selected fields; map basic scalars and fixed-width FP32 vectors; reuse prepared upload/task-submission scaffolding and report source version/count/status. Acceptance criteria A fixture with deletions imports only live rows from the chosen version; IDs/vectors agree, dimension errors fail before submission and memory remains batch-bounded. Dependencies No numbered project prerequisite. The preparation conditions below still apply. Boundaries and preparation Existing Lance/Parquet tooling and upload scaffold r

📅 Opened Sep 24, 2026💬 4 comments
Quality: 80/100Contribute

Is there an existing issue for this? I have searched the existing issues. No directly matching open issue was identified in the catalog duplicate check. Recheck the target branch and in-flight PRs with a maintainer before claiming this task. Project Catalog ID: G02 Difficulty: easy Estimated incremental effort: 3–5 hours Connect a compatible rerank service without losing candidate/score alignment. Implementation scope Pin one supported request/response protocol; add a thin adapter or configuration reuse; demonstrate actual calls, timeout and cancellation. Acceptance criteria Returned indexes map to the correct candidates; missing, duplicate and out-of-range indexes are rejected. Dependencies No numbered project prerequisite. The preparation conditions below still apply. Boundaries and preparation Existing protocol and rerank infrastructure must be reusable. New protocol design is a separate task. The estimate assumes familiarity with the implementation language, a working build/te

📅 Opened Sep 24, 2026💬 2 comments
Quality: 80/100Contribute

Is there an existing issue for this? I have searched the existing issues. No directly matching open issue was identified in the catalog duplicate check. Recheck the target branch and in-flight PRs with a maintainer before claiming this task. Project Catalog ID: G01 Difficulty: easy Estimated incremental effort: 3–5 hours Provide a runnable text-to-embedding-to-search workflow using an existing compatible provider. Implementation scope Pin a deployed model/version; reuse existing provider and Function configuration; deliver startup settings, health checks and an end-to-end script. Acceptance criteria A real service embeds and searches text successfully; dimension mismatch and service unavailability fail clearly. Dependencies No numbered project prerequisite. The preparation conditions below still apply. Boundaries and preparation Model/service must already be ready. This is a thin integration/example, not a new provider platform. The estimate assumes familiarity with the implementa

📅 Opened Sep 24, 2026💬 3 comments
Quality: 80/100Contribute

Is there an existing issue for this? I have searched the existing issues. No directly matching open issue was identified in the catalog duplicate check. Recheck the target branch and in-flight PRs with a maintainer before claiming this task. Project Catalog ID: E02 Difficulty: easy Estimated incremental effort: 3–5 hours Make the approved plan explanation available through a usable client entry point. Implementation scope Reuse E01 and its approved response schema; connect one public API and a Milvus CLI entry point with text/JSON output, authorization and database scope. Acceptance criteria CLI and API agree for the same request. Invalid expressions and unauthorized requests preserve existing error behavior; no search is executed. Dependencies #53829 Boundaries and preparation Requires E01 and ready API/CLI extension points. No new cross-component protocol or runtime profiler within this estimate. The estimate assumes familiarity with the implementation language, a working buil

📅 Opened Sep 24, 2026💬 0 comments
Quality: 80/100Contribute

Is there an existing issue for this? I have searched the existing issues Environment - Milvus version:v3.0.0 - Deployment mode(standalone or cluster):cluster - MQ type(rocksmq, pulsar or kafka): kafka - SDK version(e.g. pymilvus v2.0.0rc2): - OS(Ubuntu or CentOS): - CPU/Memory: - GPU: - Others: Current Behavior 我的 Milvus 版本是 3.0。使用 Kafka 作为消息队列,同时还使用了第三方的对象存储服务。当我尝试将消息队列从 Kafka 切换到 Woodpecker 时,遇到了以下错误: Milvus 在通过 BulkPackWriterV2 将 Insert Log 写入对象存储时,关闭 PackedWriter 失败。对象存储在执行 CompleteMultipartUpload 操作时返回 HTTP 400,错误码为 EntityTooSmall。 错误信息表明:Multipart Upload 中存在小于对象存储最小限制(5 MB)的非最后一个分片,导致整个上传任务无法完成。 完整报错如下 [2026/08/18 03:31:52.229 +00:00] [WARN] [syncmgr/pack_writer_v2.go:178] ["failed to write inserts

📅 Opened Aug 19, 2026💬 4 comments
Quality: 50/100Contribute
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Contributor Compatibility & Review Speed Analysis for milvus-io/milvus

When evaluating whether to contribute to milvus-io/milvus, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of milvus-io/milvus acknowledge new external contributions in approximately 15 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 66.4% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to milvus-io/milvus

01

Is milvus-io/milvus welcoming to first-time open-source contributors?

milvus-io/milvus has a recorded first-timer success rate of 43.7%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~15 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 66.9 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 66.9 places milvus-io/milvus in the Welcoming tier.

04

What is the external contributor pull request merge rate for milvus-io/milvus?

The external pull request merge rate is 66.4%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in milvus-io/milvus?

Yes, milvus-io/milvus currently has 17 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for milvus-io/milvus are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.