Together AI VS Polygres
Together AI과 Polygres을(를) 비교해 보세요. Together AI과 Polygres의 차이점은 무엇인가요?
당신은 좋아할지도 모릅니다
요약
Together AI 요약
Together AI 방문 페이지
Polygres 요약
Polygres turns Postgres into working memory for AI agents. Retrieve structured rows, connected relationships, semantic matches, and full-text results through one hybrid API. All without a separate vector store, graph database, or sync pipeline. Build grounded agents over the data you already have, with relational, graph, and vector context joined at the source. Use the managed cloud or self-host with our open source components. Polygres is currently free to use, just sign up!
Polygres 방문 페이지
세부 정보 비교
Together AI 세부정보
| 카테고리 | AI 개발자 도구, AI API 개발, AI 모델, 오픈소스 AI 모델, 대형 언어 모델 LLMs |
| Together AI 웹사이트 | https://www.together.ai?utm_source=toolify |
| 추가된 시간 | 6월 22 2025 |
| Together AI 가격 | -- |
Polygres 세부정보
| 카테고리 | AI 개발자 도구, AI 에이전시, AI 지식 그래프, AI API 개발, AI 검색 엔진 |
| Polygres 웹사이트 | https://polygres.com?utm_source=toolify |
| 추가된 시간 | 8월 26 2026 |
| Polygres 가격 | -- |
사용량 비교
Together AI을 어떻게 사용하나요?
Users can interact with Together AI through easy-to-use APIs for serverless inference or deploy models on custom hardware via dedicated endpoints. Fine-tuning is available through simple commands or by controlling hyperparameters via API. GPU clusters can be requested for large-scale training. The platform also offers a web UI, API, or CLI to start or stop endpoints and manage services. Code execution environments are available for building and running AI development tasks.
Polygres을 어떻게 사용하나요?
Create a Polygres managed instance or install the open-source components on an existing PostgreSQL database. Connect your schema and use the SDK or retrieval API to submit a natural-language query with options such as graph traversal depth, filters, and token limits. Polygres combines relational, graph, vector, and text results into one ranked, token-ready context block that can be passed directly to an AI agent.
Together AI과 Polygres의 장점 비교하기
Together AI의 핵심 기능
- Serverless Inference API for open-source models
- Dedicated Endpoints for custom hardware deployment
- Fine-Tuning (LoRA and full fine-tuning)
- Together Chat app for open-source AI
- Code Sandbox for AI development environments
- Code Interpreter for executing LLM-generated code
- GPU Clusters (Instant and Reserved) with NVIDIA GPUs (GB200, B200, H200, H100, A100)
- Extensive Model Library (200+ generative AI models)
- OpenAI-compatible APIs
- Accelerated Software Stack (e.g., FlashAttention-3, custom CUDA kernels)
- High-Speed Interconnects (InfiniBand, NVLink)
- Robust Management Tools (Slurm, Kubernetes)
Polygres의 핵심 기능
- Unified relational, graph, vector, and full-text retrieval
- Native graph traversal over existing PostgreSQL foreign keys
- Fused hybrid search with dense HNSW, sparse, filtered, and semantic retrieval
- Token-ready context assembly for grounded AI agents
- Shortest-path, neighborhood, relationship, and multi-hop graph queries
- Managed cloud hosting and open-source self-hosting
- PostgreSQL-native data retrieval without a separate vector store or sync pipeline
사용 사례 비교
Together AI의 사용 사례
- Accelerating AI model training and inference for enterprises (e.g., Salesforce, Zoom, InVideo)
- Building AI customer support bots that scale to high message volumes (e.g., Zomato)
- Developing production-grade AI applications by unlocking data for developers and businesses
- Creating next-generation text-to-video models (e.g., Pika)
- Building cybersecurity models (e.g., Nexusflow)
- Achieving simpler operations, improved latency, and greater cost-efficiency for AI models (e.g., Arcee AI)
- Developing custom generative AI models from scratch
- Performing multi-document analysis, codebase reasoning, and personalized tasks
- Managing complex tool-based interactions and API function calls
- Generating and debugging code with advanced LLMs
- Executing visual tasks with advanced visual reasoning and video understanding
- Data tasks such as classification and structured data extraction
Polygres의 사용 사례
- Build grounded AI agents that retrieve customer records, orders, tickets, and related history
- Investigate failed transactions by combining semantic search with order, payment, and dispute relationships
- Create user-memory systems that retrieve relevant past interactions and connected data
- Query Wikipedia-scale datasets using hybrid indexes and graph relationships
- Provide support agents with ranked, database-backed context
- Develop recommendation and discovery systems using existing PostgreSQL data
Together AI과 Polygres의 다른 요금제 비교
Together AI
Varies by model and token count
Prices are per 1 million tokens (input and output for Chat, Multimodal, Language, Code; input only for Embedding; image size/steps for Image models). Batch inference is available at an introductory 50% discount. Specific model prices range from $0.06 to $7.00 per 1M tokens depending on model size and type.
Varies by GPU type, per minute/hour
Deploy models on customizable GPU endpoints with per-minute billing. Supports various NVIDIA GPUs like RTX-6000, L40, A100, H100, H200. Prices range from $0.025/minute ($1.49/hour) for RTX-6000/L40 to $0.083/minute ($4.99/hour) for H200.
Per 1M Tokens processed
Pricing is based on model size, dataset size, and number of epochs. Supervised Fine-tuning (LoRA) ranges from $0.48 to $2.90 per 1M tokens. Full Fine-tuning ranges from $0.54 to $3.20 per 1M tokens. DPO (LoRA) ranges from $1.20 to $7.25 per 1M tokens. DPO (Full FT) ranges from $1.35 to $8.00 per 1M tokens.
Starting at $1.30/hour
State-of-the-art clusters with NVIDIA Blackwell and Hopper GPUs (H200, H100, A100) for optimal AI training and inference. H200 starts at $2.09/hr, H100 at $1.75/hr, A100 at $1.30/hr. GB200 and B200 pricing requires contact.
Per hour or per session
Together Code Sandbox is priced per vCPU ($0.0446/hour) and per GiB RAM ($0.0149/hour). Together Code Interpreter is priced per session ($0.03 for 60 minutes).
Polygres
$0 / forever
Open-source pgGraph and pgVector, runnable on any PostgreSQL instance, with community support.
$16 / month
Managed cloud database hosting with email and community Discord support. Currently free for now.
$256 / month minimum usage
Automated vertical and horizontal scaling, email and community Discord support, private Discord or Slack channel, and support hours from 8:00 AM to 5:00 PM.
$4,096 / month minimum usage
Coming soon. Includes dedicated database infrastructure, custom compliance, high availability, 24/7 support, and dedicated support and uptime SLAs.
Together AI의 트래픽
Together AI은(는) 785.1K 월간 방문과 00:02:17 평균 방문 기간을 가진 것입니다. Together AI의 방문당 페이지 수는 3.46이고 이탈률은 42.03%입니다.
최신 웹사이트 트래픽
| 월 방문자 수 | 785.1K |
| 평균·방문시간 | 00:02:17 |
| 방문당 페이지 수 | 3.46 |
| 이탈률 | 42.03% |
Polygres의 트래픽
Polygres은(는) 29.2K 월간 방문과 00:00:44 평균 방문 기간을 가진 것입니다. Polygres의 방문당 페이지 수는 1.61이고 이탈률은 68.04%입니다.
최신 웹사이트 트래픽
| 월 방문자 수 | 29.2K |
| 평균·방문시간 | 00:00:44 |
| 방문당 페이지 수 | 1.61 |
| 이탈률 | 68.04% |
지리적 트래픽
Together AI의 상위 5 국가/지역은 다음과 같습니다:United States 35.41%, India 9.66%, China 3.54%, Germany 2.81%, Indonesia 2.71%
상위 5 국가/지역
 | 35.41% |
 | 9.66% |
 | 3.54% |
 | 2.81% |
 | 2.71% |
지리적 트래픽
Polygres의 상위 3 국가/지역은 다음과 같습니다:United States 84.49%, India 15.16%, Mexico 0.34%
상위 3 국가/지역
| 84.49% |
| 15.16% |
 | 0.34% |
웹사이트 트래픽 소스
Together AI에 대한 6가지 주요 트래픽 소스는 다음과 같습니다.직접 41.57%, vs_sourcesSearchOrganic 33.43%, vs_sourcesSearchPaid 9.28%, 추천 7.01%, vs_sourcesSocialOrganic 3.68%, vs_sourcesGenAi 3.25%, 메일 1.34%, vs_sourcesDisplayAds 0.24%, vs_sourcesSocialPaid 0.18%, vs_sourcesAffiliate 0.01%
직접 | 41.57% |
vs_sourcesSearchOrganic | 33.43% |
vs_sourcesSearchPaid | 9.28% |
추천 | 7.01% |
vs_sourcesSocialOrganic | 3.68% |
vs_sourcesGenAi | 3.25% |
메일 | 1.34% |
vs_sourcesDisplayAds | 0.24% |
vs_sourcesSocialPaid | 0.18% |
vs_sourcesAffiliate | 0.01% |
웹사이트 트래픽 소스
Polygres에 대한 6가지 주요 트래픽 소스는 다음과 같습니다.직접 43.28%, vs_sourcesSocialOrganic 34.37%, vs_sourcesSearchOrganic 14.81%, 추천 4.00%, 메일 1.48%, vs_sourcesGenAi 0.93%, vs_sourcesDisplayAds 0.49%, vs_sourcesAffiliate 0.25%, vs_sourcesSearchPaid 0.25%, vs_sourcesSocialPaid 0.12%
직접 | 43.28% |
vs_sourcesSocialOrganic | 34.37% |
vs_sourcesSearchOrganic | 14.81% |
추천 | 4.00% |
메일 | 1.48% |
vs_sourcesGenAi | 0.93% |
vs_sourcesDisplayAds | 0.49% |
vs_sourcesAffiliate | 0.25% |
vs_sourcesSearchPaid | 0.25% |
vs_sourcesSocialPaid | 0.12% |
Together AI 또는 Polygres 중 어느 것이 더 낫습니까?
Together AI은(는) Polygres보다 약간 더 인기가 있을 수 있습니다. 보시다시피 Together AI의 월간 방문수는 785.1K회이고 Polygres의 월간 방문수는 29.2K회입니다. 따라서 더 많은 사람들이 Together AI을(를) 선택합니다. 따라서 사람들이 소셜 플랫폼에서 Together AI을(를) 더 많이 추천할 가능성이 있습니다.
Together AI의 평균 방문 기간은 00:02:17이고 Polygres의 평균 방문 기간은 00:00:44입니다. 또한 Together AI의 방문당 페이지 수는 3.46이고 이탈률은 42.03%입니다. Polygres의 방문당 페이지 수는 1.61이고 이탈률은 68.04%입니다.
Together AI의 주요 사용자는 United States, India, China, Germany, Indonesia이며 분포는 35.41%, 9.66%, 3.54%, 2.81%, 2.71%입니다.
Polygres의 주요 사용자는 United States, India, Mexico이며 분포는 84.49%, 15.16%, 0.34%입니다.
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