OpenCTI vs Yeti: which to choose

OpenCTI vs Yeti: which platform fits your team

A CTI or security team with both platforms on its shortlist is usually choosing between two different jobs: running a structured intelligence knowledge base for many feeds and analysts, or giving DFIR analysts a repository they can query during an investigation. OpenCTI fits the first job. It organizes intelligence as STIX-based entities and relationships, imports data through a large connector ecosystem including MISP, MITRE and CVE connectors, and suits a team that can operate the full dependency stack: Elasticsearch 8.0 or later or OpenSearch 2.9 or later, Redis 7.1 or later, RabbitMQ 3.11 or later and S3-compatible storage. Yeti fits the second job. It is a Python and FastAPI platform on ArangoDB that stores DFIQ objects, forensic artifact definitions, Sigma and YARA rules and reusable queries next to indicators, with Timesketch and MITRE ATT&CK integration. It suits analysts who need those artifacts at hand without operating a large cluster.

Four questions should drive the decision. First, the data model: if your intelligence must map to STIX objects for partners or tooling, OpenCTI's model is the native fit, while Yeti's model centers on artifacts and investigative objects. Second, operating load: count who will patch, scale and back up the OpenCTI dependencies, and compare that with a smaller Yeti deployment. Confirm the current versions with each vendor before you size hardware, since OpenCTI ships frequent releases and Yeti's current release is 2.12.0. Third, Enterprise Edition: audit logs, playbooks and automation, organization segregation and OpenID, LDAP or SAML SSO in OpenCTI all require a paid Enterprise Edition subscription. If your controls depend on those features, price them into the comparison from the start, and ask the vendor what the subscription includes.

Fourth, and often decisive, is who does the daily work. An intelligence team that curates feeds and produces reports will get more from OpenCTI's knowledge base. An incident responder who needs to pivot from an indicator to an artifact definition or a Sigma rule during a case will usually find Yeti closer to the workflow. Many teams run both, so write down which analysts open each platform and for what task before you commit. If you need an implementation plan, a scoped review of your data flows, identity integration and backup requirements is the practical next step, and DeployOpen can prepare that scope in writing.

Which team and scenario favors OpenCTI or Yeti

This table matches common team situations to the platform that usually fits better and the condition that decides it. Read each row against your own team's skills, infrastructure and workflow, since several answers depend on who will operate the platform day to day.

Scenario	Better fit	Condition that decides it
CTI team consolidating feeds	OpenCTI	Choose it when the goal is one STIX-based knowledge base that imports many feeds through connectors and relates entities over time. Confirm which connectors your feeds need in the current release.
DFIR team building investigation context	Yeti	Choose it when analysts need to store DFIQ objects, forensic artifact definitions, Sigma and YARA rules and reusable queries next to indicators, with Timesketch and MITRE ATT&CK integration.
Team with a platform engineering function	OpenCTI	A team that can run Elasticsearch or OpenSearch, Redis, RabbitMQ and S3-compatible storage, and maintain connectors, can absorb the dependency stack. Without that capacity, the footprint becomes the main risk.
Small team with limited operations capacity	Yeti	Yeti is built on Python, FastAPI and ArangoDB, which means fewer separate services to operate. Confirm the deployment footprint and backup approach for your environment before committing.
Team needing SSO, audit logs or organization segregation	Depends on edition	In OpenCTI, audit logs, playbooks and automation, organization segregation and OpenID, LDAP or SAML configuration require Enterprise Edition. Ask Yeti's maintainers which identity and audit features exist in the open-source release before deciding.
Team importing MISP data	OpenCTI	OpenCTI offers a MISP connector and STIX-based entities, so it suits teams that want MISP events inside a graph. If the team mainly shares indicators with communities, MISP itself may fit better than either platform.
Team whose main need is sharing intelligence	Neither alone	Both platforms store intelligence, but neither is positioned as a community sharing hub. Confirm sharing and export needs against MISP, which synchronizes events and exports to STIX, CSV and detection rule formats.
Team that needs both graph context and forensic queries	Depends on skills	Running both can cover the gap, but it doubles integration and upkeep. Decide based on whether analysts or engineers will maintain connectors, rules and queries.

How OpenCTI's dependency stack changes day-to-day operations

OpenCTI is a single platform in name, but its day-to-day load comes from the services around it: a GraphQL platform, Python connectors and four supporting data and messaging services. Yeti, built on Python, FastAPI and ArangoDB, has a smaller set of moving parts, so the operational comparison depends on how many of these components your team can run, patch and restore.

Stateless platform and GraphQL API

OpenCTI's platform layer serves a GraphQL API and is described as stateless, so state sits in the backing services rather than in the application tier. For operations, this means scaling and replacing platform nodes is simpler, but backups must cover every stateful service, not just the application. Confirm with the vendor documentation how your chosen version handles configuration, secrets and upgrade order across nodes before you commit to a topology.

Python workers and connectors

Data flows into OpenCTI through Python workers and connectors, including MISP, MITRE and CVE connectors. Each connector is a separate process that needs its own configuration, credentials, scheduling and log review. On-call staff should expect failures to appear here first, such as an upstream feed change or an expired API key, and should check how many connectors your intelligence program actually depends on before sizing the on-call rota.

Search index: Elasticsearch or OpenSearch

OpenCTI requires Elasticsearch 8.0 or later or OpenSearch 2.9 or later. Your team must pick one, and the choice drives index sizing, cluster health monitoring, snapshot policy and the upgrade path for the search layer. Confirm which engine your platform team already operates and supports, because a search cluster that is under-monitored is a common source of slow queries and stalled imports.

Redis, RabbitMQ and S3 storage

OpenCTI also needs Redis 7.1 or later, RabbitMQ 3.11 or later and S3-compatible object storage. Redis and RabbitMQ carry queued work between components, so a stalled queue can look like a stalled platform. The S3 bucket holds files attached to intelligence objects. Each service adds its own patching cycle, TLS certificates, access policy and restore test, so ask whether your team or DeployOpen will own those runbooks.

Yeti's Python, FastAPI and ArangoDB build

Yeti is built in Python with FastAPI and stores its data in ArangoDB. That is a smaller count of named services than OpenCTI's stack, with a single database engine to back up, monitor and upgrade. The trade-off is that ArangoDB is the one data store your team must know well, and you should confirm its clustering, backup tooling and support requirements against the Yeti project and ArangoDB documentation for your environment.

OpenCTI vs Yeti feature by feature

This table compares OpenCTI and Yeti on license, data model, connectors, integrations, Enterprise Edition features, backend footprint and release status. Read each row as a fit question: OpenCTI centers on a STIX knowledge base with a heavier service stack, while Yeti centers on DFIR artifacts, rules and queries. Where a cell says to confirm, ask the vendor before assuming parity.

Capability	OpenCTI	Yeti
License	Apache-2.0 for Community Edition; Enterprise Edition files need a paid subscription	Apache-2.0 for the platform repository
Core data model	STIX-based entities and relationships for structured threat intelligence	DFIQ objects, forensic artifact definitions, Sigma and YARA rules, reusable queries
Connectors and imports	Connectors for MISP, MITRE and CVE sources, run by Python workers	Supported import sources are not confirmed here; ask Yeti which sources it ingests
Integrations	Confirm which integrations beyond connectors your OpenCTI version supports	Timesketch and MITRE ATT&CK integration
Enterprise features	Audit logs, playbooks and automation, organization segregation, OpenID, LDAP or SAML SSO	Confirm with Yeti whether any features sit behind a paid tier before budgeting
Backend footprint	GraphQL API with Elasticsearch or OpenSearch, Redis, RabbitMQ and S3-compatible storage	Python with FastAPI and ArangoDB
Current release	7.261016.0, released October 16, 2026	2.12.0, released October 2, 2026
Best fit team	Teams maintaining a shared, structured CTI knowledge base across analysts	DFIR teams keeping artifacts, detection rules and queries beside intelligence

What Apache-2.0 and the Enterprise Edition License each cover

The OpenCTI Community Edition is licensed under Apache-2.0, according to the LICENSE file in the OpenCTI-Platform/opencti repository. Apache-2.0 is a permissive open-source license, so the code outside the Enterprise files can be used, modified and deployed inside your own infrastructure without a license fee. Your costs in this model are the infrastructure, the staff who run it and any external support you buy.

No license fee for Community code: The Apache-2.0 files carry no subscription requirement in the supplied license terms.
Self-hosted deployment: You run the platform and its dependencies in your own cloud accounts, data centers or air-gapped networks.
Connectors remain part of the stack: Import connectors such as MISP, MITRE and CVE are used as documented in the OpenCTI documentation.
Enterprise-only features are excluded: Audit logs, playbooks and automation, organization segregation and OpenID, LDAP or SAML SSO are not part of this tier.
Your team owns operations: Upgrades, backups and monitoring of the dependency stack fall to you or to a services partner.

Before relying on this tier, confirm with the vendor which files in your chosen release fall under Apache-2.0 and which are marked Enterprise Edition.

What drives the running cost of each platform

Running cost for OpenCTI and Yeti comes from different places. OpenCTI carries a heavier service stack and, for some controls, a paid Enterprise Edition, while Yeti shifts more of the effort onto analysts who build and tune its content. The cards below name who pays for each item, what is one-time and what recurs, and what to request in a written quote.

Service dependency infrastructure

OpenCTI needs an Elasticsearch or OpenSearch cluster, Redis, RabbitMQ and S3-compatible storage alongside the platform and its connectors. Your infrastructure team pays for compute, storage, backups and monitoring for each of these, and that spend recurs every month for as long as the stack runs. Ask the vendor or your implementation partner to size each dependency against your expected indicator volume and connector count, and to state which components are shared with existing services. Yeti runs on a smaller stack built around ArangoDB, so compare the component lists before comparing hosting bills.

Upgrade and connector maintenance staff time

Both platforms need someone to apply releases, test connectors and repair broken imports. OpenCTI uses a separate LTS track with an lts suffix, so teams must choose which line to follow and plan each upgrade across the platform, its workers and its connectors. This labor is internal and recurs with every release cycle. Before you commit, estimate how many connectors your team will run, who owns each one, and how long a failed import can go unnoticed. Request a written statement of which upgrade tasks the partner will perform and which remain with your staff.

Enterprise Edition subscription cost

If you need SSO through OpenID, LDAP or SAML, audit logs, playbooks or organization segregation in OpenCTI, you need the Enterprise Edition under a paid subscription. The vendor or reseller bills that subscription, and it recurs for the life of the deployment. Yeti's Apache-2.0 license does not carry an equivalent paid tier in the supplied facts, so confirm which access controls you need before pricing. Ask for the subscription price, renewal terms, the feature list tied to each tier, and what happens to access if the subscription lapses.

Analyst time on artifacts and queries

Yeti stores forensic artifact definitions, DFIQ objects, Sigma and YARA rules and reusable queries next to threat intelligence. Analysts or detection engineers pay for this in hours spent writing, reviewing and retiring that content, and the cost recurs as investigations change. The labor is not licensing, so it does not appear on a vendor quote. Estimate how many analysts will contribute content, who approves changes, and how often rules need review. Ask your team to pilot one investigation type before treating the staffing estimate as final.

Support and retainer options

Your team can run either platform with internal staff alone, or buy ongoing support, upgrades and continuous testing as a retainer. DeployOpen offers retainers, and most engagements are fixed-scope with deliverables agreed in writing before work starts. The retainer cost recurs, while the initial implementation is a one-time scope. Decide which tasks your staff can absorb, then request a written scope that lists upgrades, connector support, hardening and backup responsibilities, along with response expectations and what is excluded.

Moving intelligence between OpenCTI and Yeti without losing context

This sequence moves indicators, reports and investigative context from one platform to the other while keeping both systems running long enough to prove the result. The output is a documented mapping, a verified data set in the target platform and a retired source with a recorded retention decision.

Inventory sources, connectors and consumers
The platform owner lists every feed, connector and downstream consumer that touches the current platform, including OpenCTI connectors such as MISP, MITRE and CVE imports, and any direct API users. For each item, record the owner, the data type, the update frequency and whether the consumer reads from the platform or writes to it. The step is done when the team has a signed inventory that shows which sources will be rebuilt in Yeti, which will be dropped and which need an owner decision. Confirm with each source provider whether its feed terms allow storage in the target platform.
Map STIX entities to Yeti objects
The data owner and an analyst compare OpenCTI's STIX-based entities and relationships with Yeti's object model, which covers indicators, DFIQ objects, forensic artifact definitions and reusable queries. Each OpenCTI entity type gets a documented target, a lossy field list and a note where no direct equivalent exists. Expect that STIX relationship semantics do not map one to one onto Yeti links, so the mapping document should state how each relationship type will be represented. The output is a reviewed mapping table that the team signs before any data moves.
Decide history, provenance and retention rules
Before migrating, the CISO, legal or records owner and the DFIR lead decide what history comes across: full revision history, original source attribution, confidence scores, sightings and the audit trail that OpenCTI Enterprise Edition provides for audit logs. Decide which records are kept in the source archive only and which are copied. Ask the vendor or your own counsel how long each dataset may be retained and who owns it when a feed licence ends. The step closes when a written retention and ownership decision exists for each data class.
Rebuild connectors, rules and queries by hand
Connectors, ingestion jobs, playbooks and saved searches do not carry over as working configuration. The integration engineer rebuilds each feed as a Yeti ingestion path or a scheduled job, recreates Sigma and YARA rule references and rewrites analyst queries in Yeti's query model. Automation that depended on OpenCTI playbooks needs its own design and testing in the target. The step is complete when every item on the inventory has a rebuilt equivalent and a test showing the same indicators arrive from the same source.
Migrate a test data set and reconcile counts
The team exports a bounded sample from OpenCTI, loads it into a Yeti test instance and compares object counts, relationship counts and sample records field by field against the mapping table. Analysts check that MITRE ATT&CK references and Timesketch links, where used, resolve correctly. Discrepancies are logged with a decision to fix, accept or drop. The output is a reconciliation report with every accepted loss recorded, which becomes the evidence for the production cutover.
Run both platforms in parallel
Both platforms ingest the same feeds for an agreed overlap period set by the data owner, and analysts record which platform they used for each investigation or lookup. The integration engineer compares alert outputs, enrichment results and dashboard figures between the two. The step closes when discrepancies have been resolved or formally accepted and analysts confirm that the target platform answers the questions the old one answered. Ask the vendor or community for guidance on which parallel-run approach suits your feed volume.
Retire the old platform and archive its data
The team switches consumers to the target, disables feeds on the old platform, and takes a final export or backup under the retention rule set earlier. The archive is tested for restore before the live instance is shut down, and access to the archive is limited to the owners named in the decision record. Credentials, connector secrets and service accounts are revoked. The output is a retirement record listing the final backup location, its restore test result and the date each data class was removed from the live system.

Where OpenCTI and Yeti implementations usually run long

Most overruns on OpenCTI start with the service stack, not the platform itself. OpenCTI depends on Elasticsearch 8.0 or later or OpenSearch 2.9 or later, Redis 7.1 or later, RabbitMQ 3.11 or later and S3-compatible storage, and each of these needs its own sizing, backup, patching and failure testing inside your environment. Connector configuration adds to this: every connector (MISP, MITRE, CVE and others) has its own schedule, credentials and volume, and teams often discover late that nobody owns the connector queue or decides which feeds stay enabled. Identity is the other common delay. If you plan to use OpenID, LDAP or SAML, or organization segregation, you need Enterprise Edition, so confirm the licensing decision before designing roles, because retrofitting groups and organizations after data has been loaded is slow. Upgrades need a plan as well: choose between the standard release line and the separately published lts builds, and agree how often you will move between them.

Yeti projects tend to run long on content and workflow rather than infrastructure. Yeti stores DFIQ objects, forensic artifact definitions, Sigma and YARA rules and reusable queries, and someone must decide which of these to import, who curates them and how they are reviewed before analysts rely on them. The analyst workflow is the second decision: which investigations start in Yeti, how indicators move from Timesketch and MITRE ATT&CK mappings into case work, and where analysts record findings. Teams that skip this step end up with a populated repository that few people use. Ask the implementation partner to document the Timesketch integration path and test it with a sample investigation, and confirm which Yeti version and integration behavior your team will validate before go-live.

A written scope for either platform should settle five things before work starts: the data model you will use and who approves changes to it, the list of connectors or content sources with named owners, the identity design including licensing for SSO and organization segregation, the sizing basis for the dependency stack and its backup targets, and the upgrade policy with a test environment. For Yeti, add the artifact and rule content to import, the analyst workflow and the Timesketch integration test. Ask for these items as deliverables with acceptance criteria, so that the quote reflects the actual work rather than an assumed one.

What buyers ask before hiring help with OpenCTI or Yeti

What drives the cost of an OpenCTI deployment?

The main drivers are the size and shape of the stack you run, the number of connectors you enable, and how much integration work your environment needs. OpenCTI runs a GraphQL platform with Python workers and connectors, and depends on Elasticsearch 8.0 or later or OpenSearch 2.9 or later, Redis 7.1 or later, RabbitMQ 3.11 or later and S3-compatible storage, according to the OpenCTI deployment overview. Each of those components needs hosting, sizing, backups and patching, so the infrastructure footprint is often the largest variable. Community Edition has no license fee, but you still pay for the infrastructure, the people who run it, and any services you buy. Ask any provider for a written scope that lists components, connectors, environments, backup targets and handover documentation, since these determine the quote.

Can a DFIR team run Yeti without outside help?

A DFIR team with Python and database experience can run Yeti in-house, but the work is more than installing a package. Yeti is built in Python with FastAPI and ArangoDB and is licensed under Apache-2.0, according to the Yeti GitHub repository. Your team must own the database operations, upgrades, access control and integration with your forensic tools, such as Timesketch and your Sigma and YARA rule workflows. Check whether your analysts can maintain the database and test upgrades against your current release, which was 2.12.0 on October 2, 2026, according to the Yeti GitHub releases page. If nobody on the team has that skill set, outside help for the initial build and handover is a common choice.

How much work do SSO and Enterprise Edition features add to OpenCTI?

Enterprise features add licensing cost and integration work, and they are not part of Community Edition. Audit logs, playbooks and automation, organization segregation and SSO through OpenID, LDAP or SAML require OpenCTI Enterprise Edition, which requires a paid subscription, according to the OpenCTI LICENSE file. Before you scope SSO, confirm which identity provider you use, how groups map to OpenCTI roles, and whether your security team needs audit logs for evidence. Ask the vendor for the current subscription terms and confirm them in writing, since they are not part of the supplied facts for this comparison. Each identity provider integration is its own piece of configuration and testing.

Can a team move intelligence data between OpenCTI and Yeti?

Moving data between them is possible in principle but needs a mapping exercise, not a simple import. OpenCTI models intelligence as STIX-based entities and relationships and imports data through connectors, while Yeti stores DFIQ objects, forensic artifact definitions, Sigma and YARA rules and reusable queries, according to the OpenCTI usage overview and the Yeti website. Some objects will map cleanly, and others, such as forensic artifact definitions, may have no direct equivalent. Ask for a field-by-field mapping, a sample export, and a test import into a non-production instance before you commit to a migration. Count the effort of validating the results, because that is usually the part that takes the longest.

What does a team need to provide to start a fixed-scope engagement?

A team needs to provide a clear description of the target environment, the access and decision-makers, and the requirements that define done. DeployOpen works from written scope, and most engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work starts. Prepare the hosting target, such as your cloud account, data center or air-gapped network, along with the identity provider details, the list of connectors and data sources you need, and the backup and retention rules that apply to your data. Name a technical owner who can approve changes. Confirm during scoping which items fall inside the agreed deliverables and which would be a separate change.

Does DeployOpen issue audit reports for a threat intelligence platform?

No. DeployOpen prepares systems, controls and evidence for compliance assessments, but independent auditors and certification bodies issue audit reports, attestations and certifications. If your organization must show evidence for an assessment, ask the provider which evidence it will prepare, such as configuration records, access settings and backup test results, and ask your auditor which of those they need. Confirm the assessment scope with your auditor before the work starts, so the evidence matches what they will review.

Is ongoing support needed after OpenCTI or Yeti goes live?

Most teams need some ongoing work after go-live, such as upgrades, patching, backups and connector maintenance. DeployOpen offers ongoing support, upgrades and continuous testing as retainers, separate from the initial fixed-scope engagement. Decide whether your own staff will handle these tasks, or whether a retainer will cover them. Ask any provider what the retainer covers, how upgrades are tested before they reach production, and how they document changes. Keep in mind that OpenCTI and Yeti release at different cadences, so plan for regular upgrade reviews either way.

How DeployOpen helps choose, implement or migrate

DeployOpen plans, implements, integrates, hardens, backs up, documents and supports self-hosted open-source platforms inside your own infrastructure, so the choice between OpenCTI and Yeti is tested against your data, your connectors and your team's workflow before anything is built. Engagements are fixed-scope, with scope and deliverables agreed in writing before work starts.

How we scope

Map which intelligence sources, sharing partners and investigation workflows the platform must serve in your environment
Confirm which connectors, data imports and STIX or forensic object types your team needs on day one
Agree in writing whether Enterprise Edition features such as audit logs, SSO and playbooks are in scope

How we build

Size and deploy the supporting services each platform depends on, such as search, queue, cache and object storage, within your cloud or data center
Configure connectors, identity integration and access segregation against the scope you approved
Test ingestion, search and integration paths, including any security testing you have scoped separately

How we hand over

Document the architecture, dependency versions, configuration and connector setup as delivered in your environment
Provide runbooks for backup, restore, upgrades and routine operator tasks your team will own
Walk your analysts and platform staff through daily use so ownership is clear before handover closes

How we support

Offer ongoing support, upgrades and continuous testing as a retainer after handover, based on your written agreement
Plan upgrade windows for the release line you choose, including long-term support builds where available
Review connector health and integration changes with your team on the cadence set in the retainer

OpenCTI vs Yeti