Gemini Enterprise vs Onyx: which to choose

Gemini Enterprise vs Onyx: when each option fits

Choose Gemini Enterprise when Google Cloud already holds your identity and documents, and your team wants no platform operations to run. Choose Onyx when the index, database and model serving must run inside your own cloud accounts or an air-gapped network, or when you need to keep model choice open so you can switch providers or host models yourself. Most renewal and residency decisions come down to which of those two requirements is non-negotiable. A Google-managed service fits organizations whose Workspace or Google Cloud estate is the center of gravity, whose security team is satisfied with Google's documented controls, and who would rather buy an operated service than staff a search platform. Confirm with Google the current Gemini Enterprise connector list, how it handles permissions for each source, and its pricing, since no figures for those are supplied here.

Onyx fits when the platform itself has to sit under your control. Its documented deployment runs the document index, database and processing as a self-contained set of services that you can deploy with Docker, Kubernetes, Helm or Terraform, and it can work with self-hosted models through Ollama, LiteLLM or vLLM. Onyx also syncs source permissions, so answers only draw on documents a user can already see in the source application. The Community Edition is MIT licensed, while code in the ee directories falls under the Onyx Enterprise License, so check which features your team needs before you commit. Onyx is also offered as Onyx Cloud, which changes the residency picture, so ask where that managed service stores indexed content.

The decision turns on four questions. First, do the connectors cover your specific sources, such as SharePoint, Confluence, Jira, Slack or Salesforce, and can you list them against your own inventory in the Onyx connectors directory and Google's current list. Second, does permission fidelity hold for each source, tested with real user accounts rather than assumed. Third, where may indexed content and conversation logs legally sit, given that the index is a copy of your documents. Fourth, who will operate the stack: a Google-managed service shifts upgrades and monitoring to the vendor, while a self-hosted Onyx deployment makes your team responsible for them. Write those four answers down before you request a quote, because they define the scope.

Which option fits which situation

This table matches common buyer situations to the better fit between Gemini Enterprise and self-hosted Onyx, with the supplied fact behind each answer. Where the answer depends on a Gemini Enterprise capability you have not yet confirmed, the cell says so, so treat those rows as questions for your vendor review.

Situation	Better fit	Why
Google Workspace-heavy estate with Drive and Gmail as main sources	Depends on confirmation	Onyx has Google Drive and Gmail connectors and syncs permissions. Confirm the Gemini Enterprise connector list and permission behavior for your exact sources before deciding.
Mixed Microsoft and Google sources (SharePoint, OneDrive, Teams, Drive, Slack)	Onyx	The Onyx connectors directory includes SharePoint, OneDrive, Outlook, Microsoft Teams, Google Drive, Gmail and Slack, and Onyx syncs source permissions so answers only use documents each user can already see.
Strict residency with self-hosted models in infrastructure you control	Onyx	Onyx deploys with Docker, Kubernetes, Helm or Terraform inside your environment and works with self-hosted models through Ollama, LiteLLM or vLLM, so index, database and inference can stay in your locations.
Air-gapped or disconnected network	Onyx	Onyx documents an air-gappable, self-hosted deployment in which the document index, database and processing run in a self-contained set of services. Gemini Enterprise is a Google-managed service, so confirm any offline option with Google before assuming one exists.
Need to use a non-Google LLM provider or a self-hosted model	Onyx	Onyx supports Anthropic, OpenAI and Gemini as well as self-hosted models through Ollama, LiteLLM and vLLM. Confirm which models Gemini Enterprise offers in your region and whether you can bring your own.
Small team with no platform engineers	Gemini Enterprise, unless you accept operating Onyx	Gemini Enterprise is Google-managed. Onyx Cloud is a managed option, or Onyx Lite offers a lighter self-hosted footprint, but self-hosting Onyx Standard means you own upgrades, the index and model servers.
Need Enterprise-only controls such as RBAC, SCIM and audit of query history	Depends on edition	Onyx lists SSO through Google OAuth, OIDC or SAML, SCIM provisioning, role-based access control and query history auditing as enterprise features, which sit in the Enterprise Edition. Confirm the license terms for your needs.
Agents that must connect to internal tools with minimal build work	Depends on confirmation	Onyx ships agents and actions in its Community Edition. Confirm which Gemini Enterprise agent connectors and actions your teams already use before comparing rebuild effort.

How Onyx matches Gemini Enterprise connectors and permissions

The key point for this section is that Onyx connects to 50+ applications and syncs their permissions, so an answer only draws on documents the user can already see in the source application. That behavior is the control to test first, because a search assistant is only as safe as the access list it inherits. Onyx's repository includes connectors for SharePoint, OneDrive, Outlook, Microsoft Teams, Google Drive, Gmail, Confluence, Jira, Slack, Salesforce and other sources, and you can review the full set in the Onyx connectors directory. Do not assume the same coverage from Gemini Enterprise. Export its current connector list from your Google Cloud console, then mark each source your staff actually use as supported by Onyx, supported only through a custom build, or missing.

Permission sync matters most in two situations. The first is a mixed estate, where Microsoft 365 holds mail, Teams and SharePoint while Google Workspace holds Drive and Gmail, because each source enforces its own sharing model and a single connector mistake can expose files across the boundary. The second is sources with fine-grained sharing, such as SharePoint sites with broken inheritance, Drive files shared through groups or link settings, and Confluence spaces with page-level restrictions. Ask Onyx's team, in writing, how each connector maps those permission objects and how often it re-syncs them. Confirm these points in your own environment rather than relying on the README summary.

A proof of concept should test three things with named test accounts. First, revoke a user's access in the source application, wait for the next sync, and confirm the user can no longer retrieve the document in chat, which exposes stale permissions. Second, add a source that is not connected, or a folder outside the indexed scope, and confirm that answers do not cite it, which exposes unindexed sources and gaps that users might otherwise assume are covered. Third, compare results for a user in each department against what that user sees in the native application. Record every mismatch with the connector name, the object type and the sync timestamp, so the findings feed directly into your go or no-go decision.

Capabilities compared from supplied facts

This table compares the capabilities that matter most when replacing Gemini Enterprise with Onyx, from connectors and permission handling to model choice and air-gap support. Gemini Enterprise cells list what to confirm with Google, because this page does not assert its feature set. Onyx cells name the edition that carries each feature, so you can check RBAC and enterprise controls against your licensing needs before you commit.

Capability	Gemini Enterprise	Onyx (edition noted)
Connectors	Confirm with Google which data sources its connectors cover, and which are available in your edition and region.	Connectors for SharePoint, OneDrive, Outlook, Teams, Google Drive, Gmail, Confluence, Jira, Slack and Salesforce, plus 50+ applications overall (Community Edition).
Permission handling	Confirm with Google how indexed content is filtered by each user's existing access in source systems, and how that filtering behaves for every connector.	Syncs source permissions so answers only draw on documents the user can already see in the source application (Community Edition, per the Onyx README).
Identity and provisioning	Confirm with Google which SSO protocols and user provisioning options your Google Cloud identity setup supports.	SSO through Google OAuth, OIDC or SAML with SCIM user provisioning (listed among enterprise features; confirm the edition that includes SCIM in your version).
Role-based access control and query auditing	Confirm with Google which admin roles, audit logs and query records are included and how they can be exported.	RBAC, usage analytics and query history auditing are listed as enterprise features (Enterprise Edition, not Community Edition).
Model choice	Confirm with Google which models are available in your region and which are global-only.	Self-hosted models through Ollama, LiteLLM or vLLM, plus Anthropic, OpenAI and Gemini APIs (Community Edition).
Agents and actions	Confirm with Google which agents are included, how they are built, and which actions can reach external systems.	Agents and actions are covered by Community Edition under the MIT license.
Deployment options	Managed by Google Cloud as a Google-operated service. Confirm with Google any options for customer-controlled hosting.	Self-hosted with Docker, Kubernetes, Helm or Terraform, or Onyx Cloud as a managed service (self-hosted open source and Enterprise Edition for self-hosting with premium features).
Air-gap support	Confirm with Google whether any deployment can run without outbound connections to Google services.	Documented as air-gappable, with the document index, database and processing inside a self-contained set of services (documented in the Onyx README).
Where indexed content is stored	Confirm with Google the regions where indexes, conversation logs and model processing are stored.	Stored in infrastructure you operate, including Postgres, Vespa or OpenSearch for the index, Redis and model servers.

Onyx Community, Enterprise and Cloud compared

The Community Edition is MIT licensed and covers retrieval-augmented generation, AI chat, agents and actions. Your team installs, configures, upgrades and monitors it inside your own cloud account, data center or air-gapped network, so the index, database and model traffic stay where you put them. This option fits organizations with platform engineering capacity that want full control and can run without the premium administration features.

Operator: Your platform or IT team runs every component, including backups, patching and sizing.
Deployment profiles: Onyx Standard includes vector and keyword indexing, background sync workers, model inference servers, object storage and Redis. Onyx Lite offers chat and agents without a vector database or background workers.
Infrastructure: Standard needs Postgres, Vespa or OpenSearch for the index, Redis and model servers. Lite needs fewer services.
Deployment methods: Docker, Kubernetes, Helm or Terraform.
Release baseline: Onyx v4.9.2 was released on October 15, 2026, according to its GitHub releases page. Confirm the version you deploy and the matching Helm chart before you start.

Confirm with your team which profile matches your user count, source list and offline requirements, and check the current Community feature list against the project documentation before relying on it for access control decisions.

Where indexed content and conversations live

Gemini Enterprise and Onyx both index company content and store conversations, but they put that data in different places and under different controls. The cards below cover where each index and chat history lives, how identity is handled, and what evidence your own team must produce regardless of which product you choose.

Gemini Enterprise index and chat storage

Gemini Enterprise is a Google Cloud managed service, so the index built from your connected sources and the conversation history are held in Google-operated infrastructure. Confirm with Google the region where indexed content is stored, the region where inference runs, whether any data is used for model training, and how long conversations and index copies are retained. Get these terms in writing before you connect sensitive sources such as mail or finance repositories.

Onyx index, database and object storage

Onyx runs in your own account or cluster. Its document index, Postgres database, Redis and object storage are deployed as a self-contained set of services with Docker, Kubernetes, Helm or Terraform, so the data sits in buckets, volumes and databases you provision. Document your storage classes, backup targets and encryption settings, because those choices decide where indexed content lives and who can restore it.

Identity and permission sync

Gemini Enterprise respects access controls of the sources it connects, and Onyx syncs source permissions so answers only draw on documents a user can already see in the source application. Test both products with a restricted test user in each connected source, including shared drives, direct messages and private channels. Record which identity provider issues the sign-in and how group membership flows into each product.

Keys, logs and administrative access

With Onyx, your team holds the database credentials, model provider keys and encryption keys, and controls who can reach the cluster. Gemini Enterprise keys and administrative actions sit with Google Cloud, so you depend on Google's audit records and the logs you can export from your own Google Cloud project. Decide who may read query history, and confirm where Onyx audit and query logs are written before go-live.

Data flow diagrams and access records

Auditors will ask for data flow diagrams that show each source, index, model call and user, plus access records for every component. This evidence is required whichever product you run, and for Onyx you must produce it from your own infrastructure. DeployOpen prepares these systems, controls and evidence for compliance assessments, but it does not issue audit reports or attestations. Independent auditors and certification bodies assess the evidence.

Responsibility for upgrades and patches

Google operates the Gemini Enterprise service, including its infrastructure and updates. With Onyx, your team or your implementation partner owns the patching cadence for Postgres, the index engine, Redis, model servers and the Onyx release itself. Write down who applies security fixes, how quickly, and how a failed upgrade is rolled back, since this becomes part of your compliance evidence.

What drives the cost of each option

Gemini Enterprise and a self-hosted Onyx deployment charge for different things, so the totals do not compare line for line. Use the components below to build a like-for-like view: which costs are fixed, which scale with users and documents, and which fall on your own staff. No prices are published here, so treat every figure as something to obtain in writing.

Gemini Enterprise seats and allowances

Gemini Enterprise is a recurring subscription, so the main cost is the seat count and the contract terms that come with it. Ask Google to state in writing what the seat price covers, which query or credit allowances apply, and what happens when usage exceeds them. Also ask how storage above the included amount is billed, since indexed content grows with every connector you add. Confirm whether connectors, agents and the EU multi-region option carry separate charges.

Onyx infrastructure for index and database

Running Onyx yourself is a recurring infrastructure cost for the Postgres database, the Vespa or OpenSearch index, Redis and object storage. These costs rise with document volume and with how many sources you sync. Onyx Lite drops the vector database and background workers, which lowers this line, but it is a different deployment with different capabilities. Ask your platform team to size each component against your document count before comparing totals.

GPU or API model charges

Model costs depend on your choice. Self-hosted models through Ollama, LiteLLM or vLLM need GPU or CPU capacity that you buy or rent and keep running, with cost driven by model size and query volume. Proprietary providers such as OpenAI, Anthropic or Gemini bill per token, so the cost moves with usage rather than headcount. Ask whether Gemini Enterprise's bundled models are priced separately from the Onyx model bill you would pay directly.

Onyx Enterprise Edition licensing

Onyx Community Edition is MIT licensed and covers RAG, chat, agents and actions. Features under the ee directories fall under the Onyx Enterprise License, and the Enterprise Edition adds premium features such as RBAC. Whether you need these depends on your access model and audit requirements. This is a recurring license cost that you should request in writing from Onyx, along with what is included in support.

Staff time for upgrades and monitoring

In a self-hosted deployment your team carries upgrades, patching, backups, monitoring and connector maintenance, which recur across the life of the system. Gemini Enterprise moves this work to Google. Estimate the hours per month for your platform and security staff, and include the one-time effort of the initial build, permission mapping and migration. Ask Onyx for a written scope covering installation, hardening and handover, and whether ongoing support is a retainer.

Sizing exercise and written quotes

The one-time sizing exercise converts your user count, document volume, sync frequency and query volume into infrastructure and model figures. Use the same inputs for every option so the comparison is fair. Request a written quote from Google covering seats, allowances, storage and any regional premium, and a written scope from DeployOpen or another implementer covering build, support and retainers. Compare totals over the same term, with one-time and recurring costs listed separately.

What a move from Gemini Enterprise to Onyx involves

The move runs as a sequence of phases: map sources and permissions, prove the permission model in a non-production Onyx deployment, settle on models, rebuild agents, run both systems side by side, and then retire the old tenant with a documented data exit. Each phase closes with a check that tells you whether to proceed.

Inventory sources, permissions and users
List every connected source, shared drive, site and group that Gemini Enterprise searches today, and record who can see what in each one. Note which sources carry the most sensitive content, which users rely on agents and which data must stay in a specific region. Your IT or platform team does this with input from the content owners. It is done when each source has an owner, a permission model and a named validation test.
Stand up a non-production Onyx deployment
Choose the target environment, such as your own cloud account, a data center or an air-gapped network, and deploy Onyx there using Docker, Kubernetes, Helm or Terraform. Decide between Onyx Standard, which includes vector and keyword indexing, background sync workers and model servers, and Onyx Lite, which omits the vector database and background workers. Confirm the infrastructure list with the Onyx deployment documentation before sizing. It is done when a test instance runs in an environment that matches your security baseline.
Reconnect sources and validate permission sync
Connect a small set of sources in the test environment and confirm that Onyx syncs their permissions, so answers only draw on documents the user can already see in the source application. Create test accounts that mirror your real access groups, including users who should see nothing in restricted folders. Compare results against the source applications, and record every mismatch with the connector and the permission type involved. It is done when the test accounts return the same visible documents as the source systems, and each gap has a documented fix or an accepted exception.
Choose models and test answer quality
Decide whether each use case runs on a self-hosted model through Ollama, LiteLLM or vLLM, or on a proprietary API provider such as Anthropic, OpenAI or Gemini. Factor in where prompts and retrieved content will be processed, the GPU or API spend, and which model your legal team has approved. Build a test set of real questions from pilot users and score the answers. It is done when each model choice has a recorded quality result, a data location and an owner who accepts the trade-off.
Rebuild agents and actions
Inventory every Gemini Enterprise agent, its data sources, its instructions and its actions, then rebuild each one in Onyx's agents and actions features. Remove any agent that no longer has an owner, and confirm that any action touching external systems uses credentials stored and scoped in your own environment. Owners sign off on behavior against the test set. It is done when each retained agent passes its owner's review and has documented access rules.
Run both systems in parallel while users switch
Move pilot groups first, keep Gemini Enterprise available for them, and collect feedback on answer quality, permission behavior and missing sources. Add groups in waves, with a clear rule for which system is the default for each team. Monitor query history and usage in both systems so that adoption and gaps are visible. It is done when all in-scope groups use Onyx as their default and open issues have a resolution or a documented workaround.
Retire the old tenant and handle data exit
Before disabling Gemini Enterprise, export what you need for records, confirm which indexed content and conversation data the Google-managed service holds, and request deletion where your retention policy and contract require it. Revoke connectors and service accounts that granted access to source systems, and update your records of processing and data flow diagrams. Confirm the deletion steps and timelines with Google and your contract terms. It is done when the export is archived, deletion is confirmed in writing and no source system still trusts the retired service.

Questions buyers ask before choosing Onyx

How much effort and cost does a self-hosted Onyx deployment add?

Onyx itself is MIT licensed in its Community Edition, so the software line is usually zero, and the real cost is the infrastructure and people to run it. The documented Onyx Standard deployment includes Postgres, Vespa or OpenSearch for the index, Redis, model servers and object storage, so you pay for compute, storage and backups in your own cloud or data center. Model cost depends on your choice: self-hosted models on GPUs carry hardware or reserved capacity costs, while API models bill per token to the provider. Ongoing work includes upgrades, monitoring, backup testing and connector maintenance. Ask any quote to split one-time setup from recurring infrastructure, staff time and model usage. Onyx Lite, which drops the vector database and background workers, can reduce the footprint for smaller use cases, and you should confirm which edition covers the features you need, such as RBAC or SCIM, before you size the stack.

How long does a migration from Gemini Enterprise take?

The timeline depends on the number and type of sources, how much permission mapping you need to verify, how many agents you rebuild, and whether users run both systems in parallel. Connector setup is often quicker than validation, because you must confirm that each user sees the same documents in Onyx that they could see in the source application. Sources with complex sharing models, such as large SharePoint estates or shared drives with nested groups, usually take the longest. Agent rebuilding depends on how many workflows teams actually use. No duration applies to every organization, so ask any implementation partner for a timeline built from a written scope that lists sources, agents, identity integration and cutover criteria. A fixed-scope engagement with agreed deliverables makes that timeline easier to hold.

What skills and access does the buyer's team need to run Onyx?

You need people who can operate the platform where it runs, which typically means cloud or data center administration, Kubernetes or Docker operations if you use Helm or containers, and identity administration for SSO through Google OAuth, OIDC or SAML and for SCIM provisioning. Your team also needs administrator access to each source you connect, such as Google Workspace, Microsoft 365, Confluence, Jira, Slack and Salesforce, so connector service accounts can read content and permissions. Storage, networking and backup administrators are needed for the index and database. Plan for a named owner for connector credentials and for the model provider account if you use API models. If one of these areas is thin in your team, that gap is usually the first thing to close before the project starts.

Can our own team deploy and operate Onyx without outside help?

A capable platform team can deploy Onyx with Docker, Kubernetes, Helm or Terraform using the project's documentation, and many teams do the proof of concept themselves. The harder work is production hardening, permission validation across many sources, identity integration, backup and restore testing, upgrades on a regular cadence, and documenting controls for auditors. Whether you need help depends on how many of those skills you already have and how much time your staff can give to the project alongside existing duties. DeployOpen plans, implements, integrates, hardens, backs up, upgrades and documents self-hosted platforms in your infrastructure under fixed-scope engagements, and it offers retainers for ongoing support. Outside help is worth considering when the project has a fixed deadline, when no one on the team has run the stack in production, or when the permission model is complex.

How can we verify that Onyx permission sync matches the source systems?

Onyx syncs source permissions, so answers should only draw on documents a user can already see in the original application. You verify this with a test plan rather than by trusting the setting. Choose test users in each relevant group, record which documents each can see in the source system, then ask the same questions in Onyx and check that restricted documents do not appear. Repeat after group membership changes, after folder sharing changes and after a sync interval, because stale permissions are the usual failure. Use the query history and usage analytics that Onyx lists among its enterprise features to review results, and confirm which of those features your edition includes. Ask your security team to sign off on the test cases and keep the results as evidence.

Which model providers can Onyx use alongside self-hosted models?

Onyx supports self-hosted models through Ollama, LiteLLM and vLLM, and it also works with proprietary providers such as Anthropic, OpenAI and Gemini. This lets you mix options, for example running an internal model for sensitive sources and a hosted model for general questions, although you should set those routing rules in writing. Each provider has its own data terms, retention and region options, so review them before you send internal content through any API. Model choice also changes cost and hardware needs: self-hosted models need GPU capacity sized to your concurrency, while API models shift that cost to usage. Confirm model support and version compatibility against the current Onyx documentation before you commit to a model stack.

What should we confirm with Google before a Gemini Enterprise renewal decision?

Ask Google for the current seat and usage terms, how connectors and permission handling work for each source you use, which features and models are available in the regions where your data must sit, and how indexed content and conversation data are stored, retained and deleted. Ask which items are included and which are billed separately, such as query allowances, storage overage or additional connectors. Request the data processing and security documentation in writing, plus the audit evidence and exports you would need during an assessment. Get the answers to these questions before you compare them with an Onyx deployment, so the cost and control comparison uses the same facts on both sides.

How DeployOpen helps evaluate and implement Onyx

DeployOpen plans, implements, integrates, hardens, documents and supports self-hosted open-source platforms inside your own cloud accounts, data centers or air-gapped networks. For Gemini Enterprise vs Onyx, we start by testing which of your sources, permissions and models must stay under your control before any build begins.

How we scope

Inventory which sources, such as Google Drive, SharePoint, Slack or Jira, hold content your teams search today.
Confirm how user permissions must carry over, and test whether Onyx's permission sync matches your access rules.
Agree the model strategy in writing: self-hosted models through Ollama, LiteLLM or vLLM, or a hosted provider.

How we build

Deploy Onyx with Docker, Kubernetes, Helm or Terraform inside your own infrastructure, including air-gapped networks where required.
Configure connectors, SSO through Google OAuth, OIDC or SAML, and SCIM provisioning against your identity provider.
Test that answers only draw on documents each user can already see in the source application, and document the results.

How we hand over

Provide written documentation of the architecture, data locations, backup routines and upgrade steps for your platform team.
Map Onyx Community and Enterprise features to your requirements, so license decisions are recorded before go-live.
Prepare controls and evidence for your compliance assessment, while independent auditors issue any formal opinion.

How we support

Ongoing support, upgrades and continuous testing are available as a retainer after handover.
Plan version upgrades against Onyx release notes and the Helm chart, testing each change in a staging environment first.
Confirm support boundaries, response expectations and retainer terms in the written scope before work starts.

Gemini Enterprise vs Onyx