SimplyRetrieve vs Vectara

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SimplyRetrieve vs Vectara Comparison
Priyansh Khodiyar's avatar
Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare SimplyRetrieve and Vectara across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.

Overview

Welcome to the comparison between SimplyRetrieve and Vectara!

Here are some unique insights on SimplyRetrieve:

SimplyRetrieve is an open-source RAG stack you run on your own hardware. It keeps data in-house and pairs with open-source LLMs, giving developers full visibility into the pipeline.

Expect hands-on setup—GPU drivers, Python deps, scripts—before you’re up and running.

And here's more information on Vectara:

Vectara caters to teams that need precision. Its APIs, SDKs, and flexible deployment options (even VPC or on-prem) let you decide exactly how ingestion and retrieval behave. If tweaking search weights and balancing semantic vs. keyword results sounds exciting, Vectara will feel at home.

Just know that the setup and ongoing tuning are a bit heavier than one-size-fits-all tools.

Enjoy reading and exploring the differences between SimplyRetrieve and Vectara.

Detailed Feature Comparison

Features
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SimplyRetrieve
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Vectara
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Data Ingestion & Knowledge Sources
  • Uses a hands-on, file-based flow: drop PDFs, text, DOCX, PPTX, HTML, etc. into a folder and run a script to embed them.
  • A new GUI Knowledge-Base editor lets you add docs on the fly, but there’s no web crawler or auto-refresh yet.
  • Pulls in just about any document type—PDF, DOCX, HTML, and more—for a thorough index of your content (Vectara Platform).
  • Packed with connectors for cloud storage and enterprise systems, so your data stays synced automatically.
  • Processes everything behind the scenes and turns it into embeddings for fast semantic search.
  • Lets you ingest more than 1,400 file formats—PDF, DOCX, TXT, Markdown, HTML, and many more—via simple drag-and-drop or API.
  • Crawls entire sites through sitemaps and URLs, automatically indexing public help-desk articles, FAQs, and docs.
  • Turns multimedia into text on the fly: YouTube videos, podcasts, and other media are auto-transcribed with built-in OCR and speech-to-text. View Transcription Guide
  • Connects to Google Drive, SharePoint, Notion, Confluence, HubSpot, and more through API connectors or Zapier. See Zapier Connectors
  • Supports both manual uploads and auto-sync retraining, so your knowledge base always stays up to date.
Integrations & Channels
  • Ships with a local Gradio GUI and Python scripts for queries—no out-of-the-box Slack or site widget.
  • Want other channels? Write a small wrapper that forwards messages to your local chatbot.
  • Robust REST APIs and official SDKs make it easy to drop Vectara into your own apps.
  • Embed search or chat experiences inside websites, mobile apps, or custom portals with minimal fuss.
  • Low-code options—like Azure Logic Apps and PowerApps connectors—keep workflows simple.
  • Embeds easily—a lightweight script or iframe drops the chat widget into any website or mobile app.
  • Offers ready-made hooks for Slack, Zendesk, Confluence, YouTube, Sharepoint, 100+ more. Explore API Integrations
  • Connects with 5,000+ apps via Zapier and webhooks to automate your workflows.
  • Supports secure deployments with domain allowlisting and a ChatGPT Plugin for private use cases.
  • Hosted CustomGPT.ai offers hosted MCP Server with support for Claude Web, Claude Desktop, Cursor, ChatGPT, Windsurf, Trae, etc. Read more here.
  • Supports OpenAI API Endpoint compatibility. Read more here.
Core Chatbot Features
  • Runs a retrieval-augmented chatbot on open-source LLMs, streaming tokens live in the Gradio UI.
  • Primarily single-turn Q&A; long-term memory is limited in this release.
  • Includes a “Retrieval Tuning Module” so you can see—and tweak—how answers are built from the data.
  • Combines smart vector search with a generative LLM to give context-aware answers.
  • Uses its own Mockingbird LLM to serve answers and cite sources.
  • Keeps track of conversation history and supports multi-turn chats for smooth back-and-forth.
  • Reduces hallucinations by grounding replies in your data and adding source citations for transparency. Benchmark Details
  • Handles multi-turn, context-aware chats with persistent history and solid conversation management.
  • Speaks 90+ languages, making global rollouts straightforward.
  • Includes extras like lead capture (email collection) and smooth handoff to a human when needed.
Customization & Branding
  • Default Gradio interface is pretty plain, with minimal theming.
  • For a branded UI you’ll tweak source code or build your own front end.
  • Full control over look and feel—swap themes, logos, CSS, you name it—for a true white-label vibe.
  • Restrict the bot to specific domains and tweak branding straight from the config.
  • Even the search UI and result cards can be styled to match your company identity.
  • Fully white-labels the widget—colors, logos, icons, CSS, everything can match your brand. White-label Options
  • Provides a no-code dashboard to set welcome messages, bot names, and visual themes.
  • Lets you shape the AI’s persona and tone using pre-prompts and system instructions.
  • Uses domain allowlisting to ensure the chatbot appears only on approved sites.
L L M Model Options
  • Defaults to WizardVicuna-13B, but you can swap in any Hugging Face model if you have the GPUs.
  • Full control over model choice, though smaller open models won’t match GPT-4 for depth.
  • Runs its in-house Mockingbird model by default, but can call GPT-4 or GPT-3.5 through Azure OpenAI.
  • Lets you choose the model that balances cost versus quality for your needs.
  • Prompt templates are customizable, so you can steer tone, format, and citation rules.
  • Taps into top models—OpenAI’s GPT-4, GPT-3.5 Turbo, and even Anthropic’s Claude for enterprise needs.
  • Automatically balances cost and performance by picking the right model for each request. Model Selection Details
  • Uses proprietary prompt engineering and retrieval tweaks to return high-quality, citation-backed answers.
  • Handles all model management behind the scenes—no extra API keys or fine-tuning steps for you.
Developer Experience ( A P I & S D Ks)
  • Interaction happens via Python scripts—there’s no formal REST API or SDK.
  • Integrations usually call those scripts as subprocesses or add your own wrapper.
  • Comprehensive REST API plus SDKs for C#, Python, Java, and JavaScript (Vectara FAQs).
  • Clear docs and sample code walk you through integration and index ops.
  • Secure API access via Azure AD or your own auth setup.
  • Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat. API Documentation
  • Offers open-source SDKs—like the Python customgpt-client—plus Postman collections to speed integration. Open-Source SDK
  • Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
Integration & Workflow
  • Run it locally: prep a GPU box, drop data, run prepare.py to embed, then chat.py for the Gradio UI.
  • Updating content means re-running scripts or using the new Knowledge tab; scaling is a manual process.
  • Plugs into Azure services like Logic Apps and Power BI for end-to-end automation.
  • Low-code connectors and REST endpoints drop search and chat into any custom app.
  • APIs let you wire Vectara into CRM, ERP, or ticketing systems for bespoke workflows.
  • Gets you live fast with a low-code dashboard: create a project, add sources, and auto-index content in minutes.
  • Fits existing systems via API calls, webhooks, and Zapier—handy for automating CRM updates, email triggers, and more. Auto-sync Feature
  • Slides into CI/CD pipelines so your knowledge base updates continuously without manual effort.
Performance & Accuracy
  • Open-source models run slower than managed clouds—expect a few to 10 + seconds per reply on a single GPU.
  • Accuracy is fine when the right doc is found, but smaller models can struggle on complex, multi-hop queries.
  • Tuned for enterprise scale—expect millisecond responses even with heavy traffic (Microsoft Mechanics).
  • Hybrid search blends semantic and keyword matching for pinpoint accuracy.
  • Advanced reranking and a factual-consistency score keep hallucinations in check.
  • Delivers sub-second replies with an optimized pipeline—efficient vector search, smart chunking, and caching.
  • Independent tests rate median answer accuracy at 5/5—outpacing many alternatives. Benchmark Results
  • Always cites sources so users can verify facts on the spot.
  • Maintains speed and accuracy even for massive knowledge bases with tens of millions of words.
Customization & Flexibility ( Behavior & Knowledge)
  • Lets you tweak everything—KnowledgeBase weight, retrieval params, system prompts—for deep control.
  • Encourages devs to swap embedding models or hack the pipeline code as needed.
  • Fine-grain control over indexing—set chunk sizes, metadata tags, and more.
  • Tune how much weight semantic vs. lexical search gets for each query.
  • Adjust prompt templates and relevance thresholds to fit domain-specific needs.
  • Lets you add, remove, or tweak content on the fly—automatic re-indexing keeps everything current.
  • Shapes agent behavior through system prompts and sample Q&A, ensuring a consistent voice and focus. Learn How to Update Sources
  • Supports multiple agents per account, so different teams can have their own bots.
  • Balances hands-on control with smart defaults—no deep ML expertise required to get tailored behavior.
Pricing & Scalability
  • Free, MIT-licensed open source—no fees, but you supply the GPUs or cloud servers.
  • Scaling means spinning up more hardware and managing it yourself.
  • Usage-based pricing with a healthy free tier—bigger bundles available as you grow (Bundle pricing).
  • Plans scale smoothly with query volume and data size, plus enterprise tiers for heavy hitters.
  • Need isolation? Go with a dedicated VPC or on-prem deployment.
  • Runs on straightforward subscriptions: Standard (~$99/mo), Premium (~$449/mo), and customizable Enterprise plans.
  • Gives generous limits—Standard covers up to 60 million words per bot, Premium up to 300 million—all at flat monthly rates. View Pricing
  • Handles scaling for you: the managed cloud infra auto-scales with demand, keeping things fast and available.
Security & Privacy
  • Entirely local: all docs and chat data stay on your own machine—great for sensitive use cases.
  • No built-in auth or enterprise security—lock things down in your own deployment setup.
  • Encrypts data in transit and at rest—and never trains external models with your content.
  • Meets SOC 2, ISO, GDPR, HIPAA, and more (see Azure Compliance).
  • Supports customer-managed keys and private deployments for full control.
  • Protects data in transit with SSL/TLS and at rest with 256-bit AES encryption.
  • Holds SOC 2 Type II certification and complies with GDPR, so your data stays isolated and private. Security Certifications
  • Offers fine-grained access controls—RBAC, two-factor auth, and SSO integration—so only the right people get in.
Observability & Monitoring
  • An “Analysis” tab shows which docs were pulled and how the query was built; logs print to the console.
  • No fancy dashboard—add your own logging or monitoring if you need broader stats.
  • Azure portal dashboard tracks query latency, index health, and usage at a glance.
  • Hooks into Azure Monitor and App Insights for custom alerts and dashboards.
  • Export logs and metrics via API for deep dives or compliance reports.
  • Comes with a real-time analytics dashboard tracking query volumes, token usage, and indexing status.
  • Lets you export logs and metrics via API to plug into third-party monitoring or BI tools. Analytics API
  • Provides detailed insights for troubleshooting and ongoing optimization.
Support & Ecosystem
  • Open-source on GitHub; support is community-driven via issues and lightweight docs.
  • Smaller ecosystem: you’re free to fork or extend, but there’s no paid SLA or enterprise help desk.
  • Backed by Microsoft’s support network, with docs, forums, and technical guides.
  • Enterprise plans add dedicated channels and SLA-backed help.
  • Benefit from the broad Azure partner ecosystem and vibrant dev community.
  • Supplies rich docs, tutorials, cookbooks, and FAQs to get you started fast. Developer Docs
  • Offers quick email and in-app chat support—Premium and Enterprise plans add dedicated managers and faster SLAs. Enterprise Solutions
  • Benefits from an active user community plus integrations through Zapier and GitHub resources.
Additional Considerations
  • Great for offline / on-prem labs where data never leaves the server—perfect for tinkering.
  • Takes more hands-on upkeep and won’t match proprietary giants in sheer capability out of the box.
  • Hybrid search + reranking gives each answer a unique factual-consistency score.
  • Deploy in public cloud, VPC, or on-prem to suit your compliance needs.
  • Constant stream of new features and integrations keeps the platform fresh.
  • Slashes engineering overhead with an all-in-one RAG platform—no in-house ML team required.
  • Gets you to value quickly: launch a functional AI assistant in minutes.
  • Stays current with ongoing GPT and retrieval improvements, so you’re always on the latest tech.
  • Balances top-tier accuracy with ease of use, perfect for customer-facing or internal knowledge projects.
No- Code Interface & Usability
  • Basic Gradio UI is developer-focused; non-tech users might find the settings overwhelming.
  • No slick, no-code admin—if you need polish or branding, you’ll build your own front end.
  • Azure portal UI makes managing indexes and settings straightforward.
  • Low-code connectors (PowerApps, Logic Apps) help non-devs integrate search quickly.
  • Complex indexing tweaks may still need a tech-savvy hand compared with turnkey tools.
  • Offers a wizard-style web dashboard so non-devs can upload content, brand the widget, and monitor performance.
  • Supports drag-and-drop uploads, visual theme editing, and in-browser chatbot testing. User Experience Review
  • Uses role-based access so business users and devs can collaborate smoothly.

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Final Thoughts

We hope you found this comparison of SimplyRetrieve vs Vectara helpful.

If local control and privacy outweigh convenience, SimplyRetrieve is a solid DIY route. Just be ready for the ongoing maintenance that comes with a self-hosted system.

Vectara’s depth and enterprise-grade features are a big win when you need custom deployments. If you’re after a fast, plug-and-play experience, be ready for extra configuration work.

Stay tuned for more updates!

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Priyansh Khodiyar's avatar

Priyansh Khodiyar

DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.