Article Metadata
| Field | Value |
|---|---|
| Document type | Global product and technical evaluation |
| Audience | Product Manager, Engineering Manager, Backend Team, Architecture Team, DevOps Team, Security Team |
| Scope | Open-source chat server evaluation, Kubernetes scalability, high-volume messaging, voice/video strategy, and recommended PoC path |
| Date | 2026-05-21 |
| Document status | Global research version, not tied to any specific company or social platform |
TL;DR
A production-grade chat platform should not force chat, realtime delivery, voice/video, storage, push notifications, moderation, and observability into one repository.
The most practical open-source PoC is OpenIM + LiveKit.
The strongest long-term architecture is Custom Go Backend + Centrifugo + Kafka/NATS + PostgreSQL/CockroachDB + Redis + LiveKit.Note: This is a global technical evaluation, not a company-specific recommendation.
Table of Contents
- Executive Summary
- Research Process and Generated Data
- What a Global Large-Scale Chat Platform Needs
- Terminology
- Goal
- Non-Goals
- Evaluation Standards
- Global Open-Source Project Metadata Table
- Required Chat Features
- Chat Feature Comparison Table
- Architecture and Extensibility Comparison
- Kubernetes Readiness Comparison
- High-Volume Message Speed and Stability Ranking
- Voice, Video, and Live Streaming Solution Comparison
- Chat Server and Voice/Video Integration Comparison Table
- Final Global Recommendation
1. Executive Summary
This document evaluates open-source technologies for building a scalable, secure, and extensible chat platform.
The target system is a production-grade chat platform that can support:
- private one-to-one chat;
- group chat;
- channels;
- private groups;
- role-based and policy-based permissions;
- user blocking and moderation;
- high-volume realtime messaging;
- Kubernetes deployment;
- voice calls;
- video calls;
- group calls;
- long-term product customization.
The main conclusion is:
A single open-source repository should not be expected to provide private chat, groups, channels, moderation, voice/video calls, group calls, Kubernetes-native scalability, high-volume messaging, and production-grade architecture perfectly at the same time.
A safer and more maintainable architecture separates the system into specialized layers:
Chat Core
+ Realtime Delivery
+ Voice/Video Infrastructure
+ Storage
+ Push Notifications
+ Admin & Moderation Layer
+ Observability
+ Kubernetes Deployment
Recommended global path:
| Decision Area | Recommendation |
|---|---|
| Best open-source chat-core starting point | OpenIM + LiveKit |
| Best Telegram-like MVP comparison | Tinode + LiveKit |
| Best long-term architecture | Custom Go Backend + Centrifugo + LiveKit |
| Best high-stability messaging-core alternative | MongooseIM / ejabberd if Erlang/XMPP is acceptable |
| Best voice/video infrastructure | LiveKit |
| Best realtime delivery layer for a custom backend | Centrifugo |
| Enterprise collaboration fallback options | Mattermost, Rocket.Chat |
| Not recommended as a main consumer-chat foundation | Chatwoot, Dendrite, Tailchat |
2. Research Process and Generated Data
2.1 Step-by-Step Evaluation Process
| Step | Input | Processing Method | Generated Output |
|---|---|---|---|
| 1 | Generic large-scale chat requirements | Converted product needs into technical requirements | Requirement list: private chat, groups, channels, permissions, calls, K8s, scaling, security |
| 2 | Global open-source repository research | Reviewed official GitHub README pages, repository metadata, and project documentation | Candidate catalog of chat servers, realtime servers, and media servers |
| 3 | Terminology cleanup | Avoided ambiguous words such as “matrix” for generic tables because Matrix is also a protocol/project | Clear section titles using “Comparison Table” and “Scoring Table” |
| 4 | Standard definition | Converted requirements into weighted engineering standards | Evaluation weights for maintainability, speed, features, scaling, security, extensibility |
| 5 | Metadata extraction | Collected language, repository activity, license/model, and project role | Open-source project metadata table |
| 6 | Feature comparison | Compared required chat features project by project | Chat Feature Comparison Table |
| 7 | Architecture comparison | Evaluated extensibility, clean-code risk, extension mechanisms, and product fit | Architecture and Extensibility Comparison |
| 8 | Kubernetes comparison | Evaluated deployment, HA, realtime scaling, external state, observability, and operational complexity | Kubernetes Readiness Comparison |
| 9 | Speed and stability comparison | Focused on high-volume messaging, fan-out, WebSocket concurrency, and clustering | High-Volume Message Speed and Stability Ranking |
| 10 | Voice/video review | Compared LiveKit, Jitsi, mediasoup, Janus, SRS, and other media solutions | Voice, Video, and Live Streaming Comparison Table |
| 11 | Integration review | Checked which chat servers can work cleanly with external media services | Chat Server and Voice/Video Integration Comparison Table |
| 12 | Final scoring | Combined maintainability, speed, features, scaling, security, expandability, external user management, and support | Final Decision Scoring Table |
| 13 | Recommendation | Converted technical results into product/architecture guidance | Recommended PoC, long-term target architecture, risks, sprint deliverables, ADR direction |
2.2 Generated Data
| Generated Data | Purpose | Used By |
|---|---|---|
| Requirement inventory | Defines what the platform must support | Product, Backend, Architecture |
| Terminology table | Prevents misunderstanding between business and technical readers | All readers |
| Open-source project metadata | Shows language, age, contribution size, license/model, and role | Product, Architecture, Management |
| Feature support table | Shows which projects support private chat, groups, channels, permissions, calls, and moderation | Product, Backend |
| Architecture comparison | Shows which projects are easier to extend without dirty code | Backend, Architecture |
| Kubernetes readiness table | Shows deployment and scaling suitability | DevOps, Architecture |
| Speed/stability ranking | Shows which options are best for high-volume message requests | Backend, Architecture |
| Voice/video solution table | Separates media infrastructure from chat infrastructure | Backend, DevOps, Product |
| Integration comparison | Shows which chat servers can work with external media systems | Backend, Architecture |
| Risk register | Captures license, scale, customization, and operational risks | Management, Legal, Architecture |
| PoC plan | Defines practical validation steps before final selection | Backend, DevOps, Product |
| Sprint deliverables | Converts the decision into actionable implementation tasks | Engineering Management |
| ADR proposal | Provides a formal architecture decision record path | Architecture Team |
2.3 Decision Flow
Business Requirements
|
v
Technical Requirements
|
v
Open-Source Candidate Discovery
|
v
Metadata + Feature + License Review
|
v
Architecture / K8s / Security / Speed Evaluation
|
v
Voice/Video and Realtime Delivery Separation
|
v
Weighted Final Scoring
|
v
PoC Recommendation
|
v
Architecture Decision Record
3. What a Global Large-Scale Chat Platform Needs
The target system must support:
- Private one-to-one chat
- Group chat
- Channels
- Private groups
- Role and permission management
- User blocking and moderation
- Message synchronization across devices
- Scalable realtime delivery
- Voice calls
- Video calls
- Group calls
- Kubernetes deployment
- Horizontal scaling
- Monitoring and operational visibility
- Clean extensible architecture
- Low long-term maintenance risk
- Ability to customize without dirty code or deep uncontrolled forks
- External user-management integration
- Clear ownership of product-level authorization and compliance rules
4. Terminology
| Term | One-line Definition |
|---|---|
| Chat Core | The service responsible for conversations, messages, members, permissions, and message history. |
| Realtime Delivery | The layer responsible for delivering events/messages to online clients over WebSocket/SSE/gRPC/WebTransport. |
| SFU | Selective Forwarding Unit; a media server architecture used for scalable WebRTC voice/video calls. |
| Channel | A one-to-many or many-to-many conversation space, often with admin/moderator permissions. |
| Private Group | A group where membership and access are restricted by invitation or policy. |
| RBAC | Role-Based Access Control; access based on roles such as owner, admin, moderator, member. |
| ABAC | Attribute-Based Access Control; access based on attributes such as user state, group type, or policy context. |
| K8s | Kubernetes; the container orchestration platform used for deployment and scaling. |
| Horizontal Scaling | Running multiple replicas/pods of a service to increase capacity. |
| Presence | Online/offline/typing/activity state of users. |
| Fan-out | Delivering one message/event to multiple recipients or subscribers. |
| Backpressure | System behavior when incoming load is higher than processing capacity. |
| Outbox Pattern | A reliability pattern where database changes and events are coordinated to avoid message loss. |
| WebRTC | Browser/mobile technology for realtime voice, video, and data communication. |
| TURN/STUN | Network traversal services required for reliable WebRTC connectivity. |
| PoC | Proof of Concept; a focused technical validation before final platform selection. |
5. Goal
The goal is to identify a technically defensible open-source foundation for building or rebuilding a production chat platform.
The selected platform or architecture must be:
- scalable to millions of users;
- secure and permission-aware;
- extensible without dirty code;
- deployable in Kubernetes;
- suitable for long-term product development;
- able to integrate with external voice/video infrastructure;
- maintainable by a backend team using modern engineering practices;
- flexible enough to integrate with an external user-management service.
6. Non-Goals
This evaluation does not aim to:
| Non-Goal | Reason |
|---|---|
| Select a UI-only chat library | Backend/chat infrastructure is required. |
| Select a customer-support inbox | Support chat is not the same as user-to-user or community messaging. |
| Force one repository to do everything | Voice/video and chat should be separated. |
| Prioritize GitHub stars over architecture | Popularity is useful but not sufficient. |
| Ignore license risk | License must be reviewed before production use. |
| Ignore migration complexity | Chat data ownership and future migration are critical. |
| Assume one product model fits every organization | Consumer, enterprise, gaming, and support chat have different requirements. |
7. Evaluation Standards
7.1 Global Production Selection Weights
| Standard | Weight | Explanation |
|---|---|---|
| Maintainability | 15% | Code quality, documentation, upgrade path, operations clarity, and team maintainability. |
| Speed / high-volume messaging | 15% | Ability to handle high throughput, low-latency delivery, fan-out, and large request volume. |
| Feature fit | 15% | Private chat, groups, channels, private groups, moderation, permissions, and required chat features. |
| Scaling / Kubernetes / HA | 20% | Horizontal scaling, multi-pod readiness, HA, clustering, and Kubernetes suitability. |
| Security / permission model | 15% | Authentication integration, authorization, RBAC/ABAC, privacy, abuse prevention, and audit capability. |
| Expandability | 10% | Ability to add product-specific features without dirty code, uncontrolled forks, or core rewrites. |
| External user-management support | 5% | Ability to integrate with an existing user service as source of truth. |
| Support / community / enterprise confidence | 5% | Community activity, documentation, commercial support, production evidence, and ecosystem maturity. |
7.2 Score Meaning
| Score | Meaning |
|---|---|
| 90-100% | Excellent fit; strong candidate for production PoC. |
| 80-89% | Strong fit; should be considered seriously. |
| 70-79% | Possible fit; requires validation and risk analysis. |
| 60-69% | Weak or specialized fit; not first choice. |
| Below 60% | Not recommended for this use case. |
8. Global Open-Source Project Metadata Table
Reading note: This table is wide. On mobile, scroll horizontally to review all columns.
Metadata is based on public repository README pages and repository snapshots reviewed on 2026-05-21. Stars, commits, releases, and license boundaries can change over time and should be re-verified before final adoption.
| Project | Repository | Primary Language | Approx. Age | Repo Size / Contribution Signal | License / Model | Main Role |
|---|---|---|---|---|---|---|
| OpenIM | OpenIMSDK/Open-IM-Server | Go | ~5 years | ~16.4k stars, ~1.7k commits | Apache-2.0 | IM/chat core for application integration |
| Tinode | tinode/chat | Go | ~10+ years | ~13.3k stars, ~4.1k commits | GPL-3.0 backend | Telegram/WhatsApp-like chat core |
| Mattermost | mattermost/mattermost | TypeScript + Go | ~11 years | ~36k+ stars, ~22k+ commits | Open-core / mixed license | Enterprise collaboration platform |
| Rocket.Chat | RocketChat/Rocket.Chat | TypeScript | ~11 years | ~45k+ stars, ~29k+ commits | Open-source / commercial ecosystem | Secure collaboration platform |
| Matrix Synapse | element-hq/synapse | Python + Rust | ~12 years | Large Matrix ecosystem | AGPL/commercial | Matrix homeserver / protocol platform |
| MongooseIM | esl/MongooseIM | Erlang | ~13+ years | ~1.7k stars, ~20k commits | Open-source + enterprise ecosystem | Scalable XMPP messaging core |
| ejabberd | processone/ejabberd | Erlang | 20+ years | ~6.7k stars, ~10k+ commits | GPL v2 | XMPP/MQTT/SIP realtime platform |
| Openfire | igniterealtime/Openfire | Java | 20+ years | ~3k stars, ~12k+ commits | Apache-2.0 | XMPP server |
| Zulip | zulip/zulip | Python + TypeScript | ~11+ years | ~25k stars, ~70k commits | Apache-2.0 | Topic-based team chat |
| Centrifugo | centrifugal/centrifugo | Go | ~10+ years | ~10.3k stars, ~1.8k commits | Apache-2.0 | Realtime messaging delivery layer |
| LiveKit | livekit/livekit | Go | ~5 years | ~18.8k stars, ~3.7k commits | Apache-2.0 | WebRTC SFU for voice/video |
| Jitsi Videobridge | jitsi/jitsi-videobridge | Kotlin + Java | 10+ years | ~3.1k stars, ~5.1k commits | Apache-2.0 | WebRTC SFU / video routing |
| mediasoup | versatica/mediasoup | Node.js + native worker | 8+ years | ~7.3k stars | ISC | Low-level WebRTC SFU toolkit |
| Janus Gateway | meetecho/janus-gateway | C | 10+ years | Mature WebRTC gateway | GPL-3.0 | General-purpose WebRTC gateway |
| SRS | ossrs/srs | C++ | 10+ years | Large media-server project | MIT | Realtime/live streaming media server |
| Chatwoot | chatwoot/chatwoot | Ruby + Vue/JS | ~6-7 years | ~29k stars | Open-source + commercial | Customer support inbox |
| Dendrite | element-hq/dendrite | Go | ~8-9 years | Small/medium | Apache-2.0 | Matrix homeserver; not strong fit for this use case |
9. Required Chat Features
| Feature | Priority | Description |
|---|---|---|
| Private one-to-one chat | Must-have | Direct messaging between two users. |
| Group chat | Must-have | Multi-user conversation rooms. |
| Channels | Must-have | Public/private channel-style communication. |
| Private groups | Must-have | Restricted-access groups. |
| Role and permission model | Must-have | Owner/admin/moderator/member permission rules. |
| User blocking | Must-have | Users must be able to block unwanted communication. |
| Remove user from group/channel | Must-have | Admin/moderator control over membership. |
| Message sync across devices | Must-have | Mobile/web sessions must stay consistent. |
| Message delivery/read status | Should-have | Sent/delivered/read/typing states. |
| Moderation workflow | Must-have | Report, block, mute, remove, ban, audit. |
| Admin APIs | Must-have | Backend management from admin services. |
| File/media messages | Should-have | Attachments, images, videos, voice messages. |
| Push notification integration | Must-have | FCM/APNS integration. |
| Voice call | Must-have | Prefer external SFU such as LiveKit. |
| Video call | Must-have | Prefer external SFU such as LiveKit. |
| Group call | Must-have | Requires SFU architecture. |
10. Chat Feature Comparison Table
Reading note: This table is wide. On mobile, scroll horizontally to review all columns.
| Project | Private Chat | Group Chat | Channel | Private Group | Role/Permission | User Blocking | Voice Call | Video Call | Group Call | Comment |
|---|---|---|---|---|---|---|---|---|---|---|
| OpenIM | Native | Native | Partial/custom | Native/custom | Partial/custom | Partial/custom | External | External | External | Strong chat-core candidate; use LiveKit for calls. |
| Tinode | Native | Native | Native/topic-based | Native | Native/granular | Native | Partial | Partial | External/planned | Good MVP fit; call should be separated for production. |
| Mattermost | Native | Native | Native | Native | Native | Partial | Native/Calls | Native/Calls | Native/Calls | Mature but team-collaboration oriented. |
| Rocket.Chat | Native | Native | Native | Native | Native RBAC/ABAC | Native/Partial | Native/integration | Native/integration | External/integration | Feature-rich but heavy. |
| Matrix Synapse | Native via rooms | Native via rooms | Native via rooms/spaces | Native | Native power levels | Native/Partial | External MatrixRTC | External MatrixRTC | External MatrixRTC | Strong protocol platform; complex. |
| MongooseIM | Native via XMPP | Native via MUC | Partial/PubSub | Native MUC | Native ACL/modules | Custom/module | External | External | External | Very strong messaging core. |
| ejabberd | Native via XMPP | Native via MUC | Partial/PubSub | Native MUC | Native ACL/modules | Custom/module | External/SIP-related | External | External | Mature and scalable. |
| Openfire | Native via XMPP | Native via MUC | Partial | Native MUC | Plugins/ACL | Plugin/custom | External | External | External | Secondary option. |
| Zulip | Native | Native streams | Native streams | Native private streams | Native | Partial | External | External | External | Good engineering, product mismatch for Telegram-like UX. |
| Stoat/Revolt | Native | Native | Native/server-channel | Native | Native permission logic | Partial | External | External | External | Interesting Discord-like model but riskier. |
| Tailchat | Native | Native | Native/group-space | Native | Partial/plugin | Partial | External | External | External | Lower production confidence. |
| Chatwoot | Partial | No | No | No | Agent/team permissions | No | No | No | No | Not a user-to-user social chat backend. |
| Dendrite | Native Matrix | Native Matrix | Native Matrix | Native Matrix | Matrix power levels | Native/Partial | External | External | External | Weak fit due to production/HA limitations. |
11. Architecture and Extensibility Comparison
| Project | Architecture Quality | Extension Model | Dirty-Code Risk | Product Fit | Score |
|---|---|---|---|---|---|
| Custom Go + Centrifugo + LiveKit | Very high potential | Fully product-owned | Low if designed well | Very high | 95% potential |
| OpenIM | High | REST API, webhooks, SDK, microservices | Medium-low | High | 88% |
| Mattermost | High | Plugins, APIs, webhooks | Medium | Medium | 82% |
| Matrix Synapse | High but complex | Matrix protocol, modules, ecosystem | Medium-high due to complexity | Medium/specialized | 78% |
| Tinode | Medium-high | Plugins, custom auth, server-side extensions | Medium | High for MVP | 76% |
| Rocket.Chat | Medium-high | Apps-Engine, marketplace apps, integrations | Medium-high if deeply customized | Medium | 76% |
| MongooseIM | High | XMPP modules, Erlang extensions | Medium-high for non-Erlang teams | Medium | 76% |
| ejabberd | High | XMPP modules, plugins | Medium-high for non-Erlang teams | Medium | 74% |
12. Kubernetes Readiness Comparison
Reading note: This table is wide. On mobile, scroll horizontally to review all columns.
| Project / Stack | K8s Install | Multi-Pod / HA | Realtime Scaling | External State | Observability | Operational Complexity | K8s Score |
|---|---|---|---|---|---|---|---|
| Custom Go + Centrifugo + LiveKit | Strong if designed | Excellent | Excellent | Excellent | Excellent | High engineering cost | 88% |
| OpenIM + LiveKit | Strong | Strong | Strong | Strong | Medium/Strong | Medium | 86% |
| Mattermost | Strong | Strong | Strong | Strong | Strong | Medium | 83% |
| Rocket.Chat | Strong | Strong | Strong | Strong | Strong | Medium/High | 82% |
| MongooseIM | Strong | Excellent | Excellent | Strong | Strong | High if Erlang unfamiliar | 80% |
| Matrix Synapse | Medium/Strong | Medium/Strong | Medium/Strong | Strong | Medium | High | 74% |
| Tinode + LiveKit | Medium | Medium | Medium | Strong | Medium | Medium | 70% |
| ejabberd | Medium | Excellent | Strong | Strong | Medium | High if Erlang unfamiliar | 69% |
| Openfire | Weak/Medium | Medium | Medium | Medium | Weak/Medium | Medium | 57% |
| Zulip | Weak/Medium | Weak/Medium | Weak/Medium | Medium | Medium | Medium | 52% |
| Chatwoot | Weak/Medium | Weak/Medium | Weak | Medium | Medium | Medium | 49% |
| Dendrite | Not suitable | Weak | Weak | Medium | Weak | High | Reject |
13. High-Volume Message Speed and Stability Ranking
| Rank | Option | Speed | Stability | Big Message Load Fit | Notes |
|---|---|---|---|---|---|
| 1 | Custom Go + Centrifugo + Kafka/NATS + PostgreSQL/CockroachDB | Excellent | Excellent | 95% | Best long-term architecture; maximum control. |
| 2 | MongooseIM | Very good | Excellent | 86% | Erlang/XMPP platform designed for large installations. |
| 3 | ejabberd | Very good | Excellent | 84% | Very mature Erlang/OTP realtime platform. |
| 4 | OpenIM | Very good potential | Good/Very good | 82% | Strong Go-based chat-core candidate; must be benchmarked. |
| 5 | Centrifugo as realtime layer | Excellent | Very good | 81% as component | Not full chat server; excellent realtime layer. |
| 6 | Mattermost | Good | Very good | 76% | Mature but collaboration-oriented. |
| 7 | Rocket.Chat | Medium/Good | Good/Very good | 72% | Mature but heavier product stack. |
| 8 | Matrix Synapse | Medium | Good | 70% | Strong protocol but operationally heavy. |
| 9 | Tinode | Medium/Good | Medium | 66% | Good MVP candidate; beta-quality and license risk. |
| 10 | Openfire | Medium | Medium | 60% | Not first choice for this use case. |
| 11 | Zulip | Medium | Medium | 58% | Product model mismatch. |
14. Voice, Video, and Live Streaming Solution Comparison
| Solution | Type | Language | Scaling | Speed / Latency | Stability | K8s Readiness | Best Use |
|---|---|---|---|---|---|---|---|
| LiveKit | WebRTC SFU | Go | Excellent | Excellent | Excellent | Excellent | Voice/video/group calls |
| mediasoup | Low-level WebRTC SFU toolkit | Node.js + native worker | Excellent if engineered | Excellent | Excellent | Custom | Custom media architecture |
| Jitsi Videobridge | WebRTC SFU / meeting stack | Kotlin + Java | Strong | Good | Excellent | Good/Medium | Meeting-style conferencing |
| Janus Gateway | General-purpose WebRTC gateway | C | Strong | Excellent | Excellent | Custom/Medium | Advanced WebRTC gateway use cases |
| Ion-SFU | WebRTC SFU | Go | Medium/Good | Good | Medium | Medium | Custom Go-heavy call stack |
| SRS | Realtime streaming server | C++ | Strong | Good/Excellent for streaming | Strong | Medium/Good | Live broadcast, RTMP/WebRTC/HLS |
| OvenMediaEngine | Low-latency streaming server | C++ | Good | Good | Good | Medium | Live streaming/broadcast |
| BigBlueButton | Web conferencing platform | Java/Groovy/Scala/JS | Medium | Good | Good | Heavy | Education/meeting platform |
| FreeSWITCH / Asterisk | SIP/PBX/media gateway | C | Strong | Good for SIP/voice | Excellent | Custom | Telephony/SIP bridge |
15. Chat Server and Voice/Video Integration Comparison Table
| Chat Server | LiveKit | Jitsi | mediasoup | Janus | SRS/OvenMediaEngine | Recommended Integration |
|---|---|---|---|---|---|---|
| OpenIM | Excellent | Good | Custom | Custom | Good for broadcast | Chat server handles messages; LiveKit handles calls. |
| Tinode | Excellent | Good | Custom | Custom | Good for broadcast | Chat server handles messages; LiveKit handles calls. |
| Custom Go Backend | Excellent | Good | Excellent | Excellent | Excellent | Backend owns call lifecycle and token generation. |
| Mattermost | Possible | Possible | Custom | Custom | Limited | Use native calls first; external only if needed. |
| Rocket.Chat | Possible | Good | Custom | Custom | Limited | Use existing call/integration model or LiveKit if replacing. |
| Matrix Synapse | Excellent via MatrixRTC/Element Call | Possible | Custom | Custom | Limited | Use MatrixRTC/LiveKit path. |
| MongooseIM | Good/custom | Good/custom | Custom | Good/custom | Limited | Requires custom signaling and XMPP integration. |
| ejabberd | Good/custom | Good/custom | Custom | Good/custom | Limited | Requires custom signaling and XMPP integration. |
| Openfire | Good/custom | Good/custom | Custom | Custom | Limited | Possible but not first choice. |
16. Which Chat Servers Have Their Own Voice/Video?
| Project | Own Voice/Video? | Production Confidence | Recommendation |
|---|---|---|---|
| Mattermost | Yes, Mattermost Calls | Medium/High | Possible, but validate consumer/mobile UX and scale. |
| Rocket.Chat | Yes/integration-based | Medium/High | Possible, but may not be ideal for a custom product architecture. |
| Matrix Synapse | No direct media SFU | Medium/High via MatrixRTC | Use LiveKit/Element Call path. |
| Tinode | Partial; group calls planned/not ideal | Medium/Low | Prefer LiveKit. |
| OpenIM | No; external expected | High as chat core | Use LiveKit. |
| MongooseIM | No native social media SFU | Medium | Use external SFU. |
| ejabberd | SIP-related platform capability, not social group call core | Medium | Use external SFU. |
| Zulip | External meeting integrations | Medium | Not core fit. |
17. Recommended Architecture Options
Option A: Practical Open-Source Start
OpenIM
+ LiveKit
+ PostgreSQL / MongoDB
+ Redis
+ S3 / MinIO
+ FCM / APNS
+ Kubernetes
+ Prometheus / Grafana / Loki
Use when: The team wants a real open-source chat core with Go, SDKs, user/group/message management, K8s deployment, and room to customize.
Main risk: Validate permission model, observability, message ordering, load behavior, and customization quality.
Option B: Telegram-Like MVP Comparison
Tinode
+ LiveKit
+ PostgreSQL / MongoDB
+ Redis
+ S3 / MinIO
+ Kubernetes
Use when: The team wants a quick Telegram/WhatsApp-like MVP with a Go backend.
Main risk: GPL-3.0 backend and beta-quality warning must be reviewed before production commitment.
Option C: Best Long-Term Architecture
Custom Go Backend
+ Centrifugo
+ Kafka or NATS
+ PostgreSQL / CockroachDB
+ Redis
+ LiveKit
+ S3 / MinIO
+ Kubernetes
+ OpenTelemetry
+ Prometheus / Grafana
+ Loki / ELK
Use when: The organization wants full ownership of domain logic, permissions, moderation, audit, data model, and scale strategy.
Main risk: Higher engineering cost, slower MVP, stronger backend and DevOps expertise required.
Option D: Stable Messaging Core
MongooseIM or ejabberd
+ external LiveKit
+ custom integration layer
Use when: Messaging stability and clustering are more important than Go/TypeScript familiarity.
Main risk: Erlang/XMPP skill requirements and product customization complexity.
18. Final Shortlist
| Priority | Candidate | Why |
|---|---|---|
| 1 | OpenIM + LiveKit | Best balance of open-source, Go, chat-core fit, K8s potential, and extensibility. |
| 2 | Custom Go + Centrifugo + LiveKit | Best long-term architecture if team capacity is strong. |
| 3 | Tinode + LiveKit | Best Telegram-like MVP comparison; validate license and scale. |
| 4 | MongooseIM | Best stable messaging-core alternative if Erlang/XMPP is acceptable. |
| 5 | Mattermost | Mature fallback, but product mismatch for consumer chat. |
| 6 | Rocket.Chat | Feature-rich fallback, but heavier and more product-oriented. |
19. Recommended PoC Plan
Phase 1: Technical Spike
| Task | Output |
|---|---|
| Deploy OpenIM on Kubernetes | Working cluster with 2-3 replicas where possible. |
| Deploy LiveKit on Kubernetes | Working room creation and token generation. |
| Build chat adapter service | Auth sync, user projection, room creation, call token generation. |
| Test private chat | User A to User B message delivery. |
| Test group chat | 100, 1,000, 10,000 member scenarios. |
| Test channel/broadcast | Measure fan-out and message delay. |
| Test reconnect/recovery | Mobile client disconnect/reconnect behavior. |
| Test permissions | Owner/admin/member/remove/block policies. |
| Test voice/video | 1:1 and group call using LiveKit. |
Phase 2: Load and Stability Test
| Test | Target |
|---|---|
| WebSocket concurrency | 50k, 100k, 250k simulated connections |
| Message throughput | 1k, 5k, 10k messages/sec baseline |
| Group fan-out | 1k, 10k, 100k subscribers |
| Message ordering | Verify ordering rules per conversation |
| Redis/DB failure test | Confirm recovery behavior |
| Rolling update test | No major message loss during deployment |
| Observability check | Metrics, logs, traces, dashboards |
| Backpressure behavior | System must degrade safely under overload |
Phase 3: Product and Security Validation
| Area | Validation |
|---|---|
| Auth integration | JWT/OIDC/custom auth compatibility. |
| Data ownership | Where messages, memberships, and permissions live. |
| Privacy/compliance | Deletion, export, retention, audit requirements. |
| Moderation | Report, block, mute, remove, ban, audit. |
| Admin APIs | Required backend operations. |
| Media security | Signed URLs, virus scan, content moderation hooks. |
| License/legal | Confirm production and commercial use constraints. |
20. Key Risks
| Risk | Impact | Mitigation |
|---|---|---|
| Choosing a project only because it is popular | High | Use weighted technical scoring and PoC. |
| Deep fork of a product-oriented platform | High | Prefer integration-friendly chat core or custom backend. |
| Weak permission model | High | Validate RBAC/ABAC before adoption. |
| Realtime scaling failure | High | Load test WebSocket/presence/fan-out early. |
| Voice/video inside chat server | Medium/High | Use dedicated SFU such as LiveKit. |
| License conflict | High | Legal review before production use. |
| Operational complexity | Medium/High | Evaluate K8s, metrics, logs, backups, upgrade path. |
| Vendor/open-core feature boundary | Medium | Confirm which required features are truly open-source. |
21. Final Decision Scoring Table
Reading note: This table is wide. On mobile, scroll horizontally to review all columns.
21.1 Final Score Weights
| Criterion | Weight |
|---|---|
| Maintainability | 15% |
| Speed / high-volume messaging | 15% |
| Feature fit | 15% |
| Scaling / Kubernetes / HA | 20% |
| Security / permission model | 15% |
| Expandability | 10% |
| External user-management support | 5% |
| Support / community / enterprise confidence | 5% |
21.2 Final Ranked Scoring Table
| Rank | Candidate | Maintainable | Speed | Features | Scaling | Security | Expandable | External User Mgmt | Support | Total | Decision |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Custom Go Backend + Centrifugo + LiveKit | 8.5 | 9.5 | 9.0 | 9.5 | 9.0 | 9.5 | 10.0 | 7.0 | 91% | Best long-term architecture |
| 2 | OpenIM + LiveKit | 8.0 | 8.5 | 8.5 | 8.5 | 7.5 | 8.5 | 8.5 | 7.5 | 82% | Best practical open-source start |
| 3 | Mattermost | 8.5 | 7.5 | 7.0 | 8.0 | 8.5 | 7.5 | 7.5 | 9.0 | 79% | Mature fallback; collaboration-oriented |
| 4 | MongooseIM + LiveKit | 7.5 | 9.0 | 6.5 | 9.0 | 8.0 | 7.0 | 6.5 | 7.5 | 79% | Strong stable messaging core if Erlang/XMPP is acceptable |
| 5 | Rocket.Chat | 7.5 | 7.0 | 8.0 | 8.0 | 8.5 | 7.5 | 7.5 | 9.0 | 78% | Feature-rich fallback |
| 6 | ejabberd + LiveKit | 7.2 | 9.0 | 6.0 | 9.2 | 7.8 | 6.8 | 6.5 | 8.0 | 77% | Very stable; Erlang/XMPP friction |
| 7 | Matrix Synapse + MatrixRTC/LiveKit | 7.5 | 7.0 | 7.5 | 7.5 | 9.0 | 7.0 | 7.0 | 8.0 | 76% | Strong protocol/security; complex |
| 8 | Tinode + LiveKit | 7.0 | 6.8 | 8.5 | 6.8 | 6.5 | 7.5 | 7.0 | 6.0 | 71% | Good MVP; license/stability risk |
| 9 | Zulip | 8.5 | 6.5 | 6.0 | 6.5 | 7.8 | 7.0 | 6.5 | 8.5 | 71% | Good engineering; product mismatch |
| 10 | Stoat/Revolt + LiveKit | 7.0 | 6.5 | 7.8 | 6.5 | 6.5 | 7.5 | 6.5 | 5.0 | 68% | Interesting, but risky |
| 11 | Openfire + LiveKit | 6.5 | 6.5 | 5.5 | 6.0 | 7.0 | 6.5 | 6.0 | 7.0 | 63% | Secondary XMPP option |
| 12 | Tailchat + LiveKit | 6.5 | 5.5 | 7.0 | 5.5 | 5.5 | 7.0 | 6.0 | 5.0 | 60% | Low production confidence |
| 13 | Chatwoot | 7.0 | 5.5 | 3.5 | 5.5 | 6.5 | 5.0 | 4.0 | 8.0 | 56% | Not suitable; support inbox |
| 14 | Dendrite | 6.5 | 4.0 | 5.0 | 2.0 | 7.0 | 6.0 | 6.5 | 4.0 | 49% | Reject |
21.3 Final Scoring Interpretation
| Category | Best Candidate | Reason |
|---|---|---|
| Best total long-term architecture | Custom Go Backend + Centrifugo + LiveKit | Highest control over performance, permissions, scaling, user-management integration, and maintainability. |
| Best ready open-source starting point | OpenIM + LiveKit | Best practical balance between Go, IM/chat features, Kubernetes potential, and integration flexibility. |
| Best pure messaging stability | MongooseIM / ejabberd | Strong Erlang/XMPP clustering and stability profile, but higher customization and team-skill friction. |
| Best mature enterprise fallback | Mattermost / Rocket.Chat | Strong support and maturity, but product model is closer to collaboration than consumer social chat. |
| Best MVP-only comparison | Tinode + LiveKit | Good Telegram-like feature fit, but license and production stability must be validated. |
| Best voice/video infrastructure | LiveKit | Best fit for voice, video, and group calls as a separate media layer. |
22. Final Recommendation
The recommended next step is:
Start PoC with:
OpenIM + LiveKit
In parallel, keep this as the long-term architectural target:
Custom Go Backend + Centrifugo + Kafka/NATS + PostgreSQL/CockroachDB + Redis + LiveKit
The reason:
- OpenIM + LiveKit gives the team the fastest practical path using open-source components.
- Custom Go + Centrifugo + LiveKit gives the cleanest long-term ownership of business logic, permissions, moderation, auditing, and high-volume message delivery.
- Tinode + LiveKit is useful as a secondary MVP comparison, but license and production stability must be reviewed carefully.
- Mattermost and Rocket.Chat are mature but are better understood as collaboration platforms, not ideal consumer-messaging cores.
- MongooseIM and ejabberd are technically strong for messaging stability, but Erlang/XMPP introduces team and product-customization friction.
23. Decision Request for Product/Architecture Team
| Question | Needed Decision |
|---|---|
| Is the product consumer-social, enterprise-collaboration, gaming/community, or support-chat oriented? | Determines whether OpenIM/Tinode, Mattermost/Rocket.Chat, MongooseIM/ejabberd, or Chatwoot makes sense. |
| Is Matrix/federation/E2EE a hard requirement? | Determines whether Synapse should remain in scope. |
| Are Go-based components preferred strongly? | Helps prioritize OpenIM, LiveKit, Centrifugo, custom Go backend. |
| Are GPL/AGPL components allowed? | Determines whether Tinode/Stoat/Synapse are legal options. |
| Is MVP speed more important than long-term ownership? | Determines OpenIM/Tinode vs custom architecture. |
| Is there DevOps capacity for K8s multi-service operation? | Determines operational feasibility. |
| What is the target load for first production phase? | Required for load test design. |
24. Proposed Next Sprint Deliverables
| Deliverable | Owner | Description |
|---|---|---|
| OpenIM K8s PoC | Backend/DevOps | Deploy OpenIM with required dependencies. |
| LiveKit K8s PoC | Backend/DevOps | Deploy LiveKit, Redis, TURN/STUN, token generation. |
| Chat Adapter Service | Backend | Minimal service for auth/user projection/call room creation. |
| Feature Validation Report | Backend/Product | Validate private chat, group, channel, permissions. |
| Load Test Baseline | Backend/DevOps | Measure concurrency, message throughput, group fan-out. |
| Legal License Review | Legal/Management | Review Apache, GPL, AGPL, open-core risks. |
| Architecture Decision Record | Architecture Team | Record final direction after PoC. |
25. Top 1 Recommended Tool Stack for Implementing a Chat Server
This section summarizes the single best recommended implementation stack for the first production-oriented PoC.
The goal is not to choose one repository that does everything. The goal is to choose the best combination of tools where each component has a clear responsibility and can scale independently.
25.1 Top 1 Recommended Stack
| Layer | Top 1 Tool | Why This Tool |
|---|---|---|
| Chat Core | OpenIM | Best practical open-source starting point for an embeddable chat/IM backend. It is closer to application-integrated chat infrastructure than a full collaboration product. |
| Voice / Video / Group Calls | LiveKit | Best fit for scalable WebRTC voice, video, and group calls. It should handle media routing, call rooms, WebRTC signaling, TURN/STUN support, and participant media sessions. |
| Realtime Delivery for Long-Term Custom Architecture | Centrifugo | Best optional realtime layer if the architecture later moves toward a custom Go backend. Strong for WebSocket/SSE/gRPC/WebTransport delivery, presence, recovery, and high-volume realtime events. |
| Message Queue / Async Pipeline | Kafka or NATS | Needed for high-volume message processing, event distribution, retries, backpressure handling, audit pipelines, and future scale. |
| Primary Database | PostgreSQL or CockroachDB | PostgreSQL is simpler for MVP and production start. CockroachDB can be evaluated later if globally distributed SQL or stronger horizontal database scaling becomes necessary. |
| Cache / Presence / Rate Limits | Redis | Required for cache, distributed locks, rate limits, presence support, routing, and realtime coordination. |
| Media Storage | S3-compatible storage / MinIO | Required for attachments, images, videos, voice messages, and future media workflows. |
| Push Notifications | FCM + APNS | Required for mobile push notifications on Android and iOS. |
| Deployment Platform | Kubernetes | Required for horizontal scaling, rolling updates, service isolation, resource control, and production operations. |
| Monitoring | Prometheus + Grafana | Required for metrics, dashboards, alerting, capacity planning, and SLO tracking. |
| Logging | Loki or ELK | Required for centralized logs, incident debugging, and production support. |
| Tracing | OpenTelemetry | Required for tracing message flow across chat, realtime, database, queue, and call services. |
25.2 Top 1 Architecture
Client Applications
|
| REST / WebSocket / Push
v
Chat Adapter Service
|
+--> OpenIM
| - private chat
| - group chat
| - channels
| - message history
| - membership projection
| - chat permissions
|
+--> LiveKit
| - voice call
| - video call
| - group call
| - media routing
| - call room management
|
+--> Redis
| - cache
| - presence
| - rate limits
| - distributed coordination
|
+--> PostgreSQL / MongoDB / CockroachDB
| - persistent data
| - message metadata
| - conversation state
|
+--> S3 / MinIO
| - attachments
| - media files
|
+--> FCM / APNS
| - mobile push notifications
|
v
Kubernetes
|
+--> Prometheus / Grafana
+--> Loki / ELK
+--> OpenTelemetry
25.3 Top 1 PoC Validation Checklist
| Validation Area | Required Test |
|---|---|
| Kubernetes deployment | Deploy OpenIM and LiveKit in K8s with separate services and external dependencies. |
| Private chat | Validate one-to-one messaging, message ordering, reconnect, and multi-device sync. |
| Group chat | Test 100, 1,000, and 10,000 member groups. |
| Channels | Test channel creation, admin permissions, broadcast behavior, and subscriber fan-out. |
| Permissions | Validate owner/admin/moderator/member behavior. |
| Blocking | Validate blocked user cannot message or interact incorrectly. |
| User removal | Validate removing users from groups/channels. |
| Voice call | Validate 1:1 audio calls through LiveKit. |
| Video call | Validate 1:1 video calls through LiveKit. |
| Group call | Validate group call with realistic participant count. |
| Push notification | Validate offline message notifications through FCM/APNS. |
| Load test | Measure baseline at 1k, 5k, and 10k messages/sec. |
| WebSocket concurrency | Test 50k, 100k, and 250k simulated connections. |
| Failure recovery | Restart pods, Redis, DB, and LiveKit nodes to check recovery behavior. |
| Observability | Confirm metrics, logs, traces, dashboards, and alerts. |
| Security | Validate auth integration, permission enforcement, and token expiration. |
| License | Confirm Apache/GPL/AGPL/open-core constraints before production commitment. |
26. Telegram-Like Chat Technology Comparison
Reading note: This table is wide. On mobile, scroll horizontally to review all columns.
This section compares technologies specifically from the perspective of building a Telegram-like chat experience.
26.1 Score Meaning
| Score | Meaning |
|---|---|
| 90-100 | Excellent Telegram-like fit |
| 80-89 | Strong fit |
| 70-79 | Possible fit with important gaps |
| 60-69 | Weak or specialized fit |
| Below 60 | Not recommended for Telegram-like chat |
26.2 Telegram-Like Chat Technology Comparison Table
| Rank | Technology / Stack | Private Chat | Groups | Channels | Private Groups | Permissions | Voice / Video | K8s / Scaling | Telegram-Like Fit | Score |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Custom Go Backend + Centrifugo + LiveKit | Excellent | Excellent | Excellent | Excellent | Excellent | Excellent via LiveKit | Excellent | Best long-term Telegram-like architecture, but highest engineering cost. | 92% potential |
| 2 | OpenIM + LiveKit | Strong | Strong | Medium / extendable | Strong / extendable | Medium / extendable | Strong via LiveKit | Strong | Best practical open-source starting point. Good IM/chat-core fit with external call infrastructure. | 88% |
| 3 | Tinode + LiveKit | Strong | Strong | Strong / topic-based | Strong | Strong / granular | Strong via LiveKit | Medium | Closest ready-made Telegram/WhatsApp-like MVP option, but license and production stability must be validated. | 84% |
| 4 | Matrix Synapse + MatrixRTC / LiveKit | Strong | Strong | Medium / rooms-spaces model | Strong | Strong / power levels | Strong via external media | Medium / complex | Strong protocol platform, but heavier and less natural for a custom Telegram-like product. | 76% |
| 5 | Rocket.Chat | Strong | Strong | Strong | Strong | Strong | Medium / integration-based | Strong | Feature-rich, but closer to team collaboration than mobile-first Telegram-like social messaging. | 74% |
| 6 | Mattermost | Strong | Strong | Strong | Strong | Strong | Medium / native calls | Strong | Mature and stable, but Slack-like/team-collaboration model is not ideal for Telegram-like consumer chat. | 72% |
| 7 | Stoat / Revolt + LiveKit | Strong | Strong | Strong / Discord-like | Strong | Medium / strong | External | Medium | Good community/channel model, but Rust, AGPL, and maturity risks make it less safe. | 70% |
| 8 | MongooseIM + LiveKit | Strong via XMPP | Strong via MUC | Medium / PubSub | Strong | Strong / modules | External | Excellent | Very stable messaging core, but XMPP/Erlang product customization is harder. | 68% |
| 9 | ejabberd + LiveKit | Strong via XMPP | Strong via MUC | Medium / PubSub | Strong | Strong / modules | External | Excellent | Very scalable and mature, but not naturally Telegram-like without significant custom product work. | 66% |
| 10 | Openfire + LiveKit | Strong via XMPP | Medium / strong | Medium | Medium / strong | Medium | External | Medium | Mature XMPP server, but not a strong Telegram-like foundation. | 60% |
| 11 | Zulip | Strong | Medium / streams | Medium / streams | Strong | Strong | External | Medium | Excellent engineering, but topic/stream model does not match Telegram-like messaging well. | 58% |
| 12 | Chatwoot | Weak / support inbox | Weak | No | No | Agent/team-based | No | Medium | Customer-support platform, not a Telegram-like chat server. | 40% |
| 13 | Dendrite | Strong via Matrix | Strong via Matrix | Medium | Strong | Strong | External | Weak for this use case | Not suitable because it is not production-ready for the required HA/scaling path. | 35% |
27. Source Links
This document is based on global public research from official project repositories and documentation pages, including:
| Project | Source |
|---|---|
| OpenIM | https://github.com/OpenIMSDK/Open-IM-Server |
| Tinode | https://github.com/tinode/chat |
| Mattermost | https://github.com/mattermost/mattermost |
| Rocket.Chat | https://github.com/RocketChat/Rocket.Chat |
| Matrix Synapse | https://github.com/element-hq/synapse |
| MongooseIM | https://github.com/esl/MongooseIM |
| ejabberd | https://github.com/processone/ejabberd |
| Openfire | https://github.com/igniterealtime/Openfire |
| Zulip | https://github.com/zulip/zulip |
| Centrifugo | https://github.com/centrifugal/centrifugo |
| LiveKit | https://github.com/livekit/livekit |
| Jitsi Videobridge | https://github.com/jitsi/jitsi-videobridge |
| mediasoup | https://github.com/versatica/mediasoup |
| Janus Gateway | https://github.com/meetecho/janus-gateway |
| SRS | https://github.com/ossrs/srs |
| Chatwoot | https://github.com/chatwoot/chatwoot |
| Dendrite | https://github.com/element-hq/dendrite |
28. Final Global Recommendation
For a generic large-scale chat platform, the recommended next step is:
Start PoC with:
OpenIM + LiveKit
The recommended long-term target is:
Custom Go Backend
+ Centrifugo
+ Kafka/NATS
+ PostgreSQL/CockroachDB
+ Redis
+ LiveKit
The recommended decision is to start with OpenIM + LiveKit, while designing the integration layer so selected parts can later migrate to a custom backend without rewriting the entire chat product.
This keeps the first implementation realistic while preserving a clean long-term architecture.
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