Graylog vs ELK Stack: which to choose

Graylog vs ELK Stack: when each one fits

Choose Graylog when your team wants log collection, routing and alerting working out of the box: its inputs (syslog, GELF and Beats), streams, processing pipelines and event definitions are built in, and a small operations group can run them without assembling the parts. Choose a self-built Elastic Stack of Elasticsearch, Logstash and Kibana when Kibana flexibility matters more to you, or when your engineers already know Elastic tooling well enough to build and maintain the pipeline, dashboards and alert logic themselves. Both can feed a SIEM later, so the first decision is about the layer you will operate every day, not the end state.

Three things should drive the decision. The first is licensing: Graylog Open is licensed under the Server Side Public License version 1 (SSPL-1.0), which is not OSI approved, while the Elastic source code is available under the Elastic License 2.0 (the default distribution), SSPL 1.0 or AGPLv3, with AGPLv3 being the OSI-approved option. Have legal review what each license permits for your internal and any customer-facing use. The second is paid editions: Graylog Enterprise and Graylog Security are paid, with archive, correlation and prebuilt detection content in those tiers, and Elastic places detection engine, anomaly detection, case management and SSO under its paid subscriptions. Ask each vendor which features your use case needs, then price those features, not the base product.

The third is operating effort, which sits mostly in the search backend. Graylog stores configuration in MongoDB and indexes logs in Graylog Data Node or self-managed OpenSearch, and Graylog documents Data Node as the recommended option. A self-built Elastic Stack needs you to size and run the Elasticsearch cluster, its node roles and its three master-eligible nodes for high availability. Before deciding, sketch your daily ingest, retention and the number of people who will patch, upgrade and back up the cluster, and confirm the current supported versions with each vendor.

Which platform fits which log management scenario

This table matches common log management scenarios to the platform that usually fits better, with the condition under which the other one wins. Read each row against your own team skills, licensing rules and retention needs, and confirm any edition or feature detail with the vendor before you commit.

Scenario	Better fit and reason	The other platform wins when
Small security team that needs alerts quickly	Graylog. Inputs, streams, processing pipelines and event definitions with PagerDuty, Slack and email notifications are built into Graylog Open, so a small team can start alerting without assembling the pieces first.	The team already has Kibana and Elastic detection skills, or needs the prebuilt detection and case management features that Elastic lists in its paid tiers.
Platform team with existing Elasticsearch skills	Elastic Stack. Engineers who already run Elasticsearch, Logstash and Kibana can reuse their operating practice, node roles and tooling, and avoid learning a second server layer.	Your team does not want to own Logstash pipelines and Kibana dashboards, and prefers Graylog streams and pipelines as the single configuration surface.
Regulated team that needs tiered retention	Depends on edition. Graylog documents index rotation and retention, and its paid Enterprise edition adds a data lake with archive restore and data tiering. Elastic data tiers (hot, warm, cold, frozen) are a native node role option. Confirm the tiering and archive behavior you need with each vendor in writing.	Graylog Open alone is the constraint: it has retention that deletes the oldest indices but no data tiering or archive restore, so budget for Enterprise or design a tiering approach on Elastic.
Team that must avoid SSPL	Elastic Stack, if you select the AGPLv3 option. Elastic's licensing FAQ says AGPLv3 was added to offer an OSI-approved open source option, alongside ELv2 and SSPL. Confirm which license applies to the exact build and components you deploy.	Never for Graylog, since Graylog Open is licensed under SSPL-1.0, which is not OSI approved. Graylog remains the better fit only if SSPL is acceptable to your legal team.
Organization that needs SAML or OIDC single sign-on from day one	Graylog, if your edition covers it. Graylog documents user authentication options in its docs, so confirm the exact SSO methods for your edition before you plan around them.	Elastic lists SAML and OpenID Connect single sign-on under its Enterprise subscription, so the Elastic Stack wins when that tier is already in your budget and contract.
Team that wants a SIEM layer without building detection content	Graylog Security, which the pricing page and product pages describe with prebuilt threat detection content, compliance packs and MITRE ATT&CK mapped rules, priced per the vendor's published plan. Confirm current content and pricing in writing.	Elastic Security, if your team prefers Elastic's detection engine and its free Basic tier as the starting point, or already runs Elastic endpoint features.
Team that expects to grow log volume without a licensing review	Elastic Stack on self-managed Basic, if the features you need stay in the free tier, since its licensing does not depend on Graylog-style processed data minimums. Confirm what Basic includes for your use case.	Graylog Open has no volume limits, so volume alone does not push you to pay. The paid Graylog editions are licensed on processed data, so review that model before scaling ingest.

Graylog vs ELK Stack: how the architectures differ

Graylog and a self-built Elastic Stack both separate log ingestion, configuration, and search storage, but the number of moving parts and who owns each one differ. The cards below cover the components you would deploy and operate, plus the cluster rules that shape day-to-day work.

Graylog server nodes

Graylog servers ingest logs through inputs such as syslog, GELF and Beats, then route them through streams and processing pipelines before search and alerting. Your team runs these nodes itself. Graylog's multi-node guide recommends three Graylog and MongoDB nodes behind a load balancer, with is_leader set to false on follower Graylog nodes. Check how many nodes your ingest volume and availability target require before choosing a layout.

MongoDB for configuration

Graylog keeps configuration and metadata in MongoDB, not in the search cluster, so MongoDB is a separate component with its own upgrades and backups. For Graylog 7.0 to 7.2, the compatibility matrix lists MongoDB 7.x up to 8.2.x. For medium to large deployments, the multi-node guide calls for MongoDB as a replica set. Confirm the MongoDB version against the matrix before each Graylog upgrade.

Search backend: Data Node or OpenSearch

Log data lives in a search backend. Graylog recommends Graylog Data Node, which installs and manages OpenSearch for you. Alternatively, your team can run self-managed OpenSearch within the supported range, which Graylog documents as 1.1.x to 3.7.x for Graylog 7.0 to 7.2. Use of OpenSearch 1.x is deprecated and will be removed in Graylog 8.0, so plan that upgrade early.

Elasticsearch as the search core

In an ELK build, Elasticsearch stores and searches the data, and your team owns its node roles, shards and tiers. Elasticsearch node roles include master-eligible, data, ingest and coordinating-only, and a highly available cluster needs at least three master-eligible nodes. Under the Elastic Stack, that three-node minimum is the first cluster rule to budget for, and it applies before any log volume is planned.

Logstash and Kibana in the pipeline

Logstash handles parsing and transformation, and Kibana provides search, dashboards and the UI for the stack. In a self-built ELK deployment, your team wires these together and owns each upgrade path. Graylog combines ingestion, pipelines, search and alerting in one server tier, so the number of separately versioned services is the key architectural difference to count when estimating operating effort.

Support lifecycles and version pinning

Each Elastic major release has a maintenance window set by Elastic's end-of-life schedule, and the 8.x line reaches end of maintenance on January 15, 2027, while 9.x runs to October 15, 2027. Graylog ties its supported OpenSearch and MongoDB ranges to each release line. Map every component in your stack to its published end-of-life date and confirm the pairing with the vendor before you commit.

Inputs, streams, alerts and Kibana flexibility compared

This table compares how Graylog and a self-built Elastic Stack handle ingestion, routing, alerting, retention, SIEM content and access control. Read each row against your team's skills: Graylog bundles more of the log workflow into one product, while the Elastic Stack leaves more assembly to you but gives Kibana's open-ended analysis. The main takeaway is that the right answer depends on whether you want a packaged workflow or a toolkit you shape yourself.

Capability	Graylog	Self-built Elastic Stack (Elasticsearch, Logstash, Kibana)
Built-in inputs	Graylog Open ingests over inputs such as syslog, GELF and Beats, configured in the web interface. Matters most for a small team that wants collection running without writing pipeline code.	Ingestion is handled by Logstash, Beats and Elastic Agent, each configured separately. Matters when you already run Beats or Agent fleets and want one pipeline tool to maintain.
Streams and processing pipelines	Streams route messages to index sets and alert rules, and processing pipelines transform them. Useful when routing rules must be visible to operators without editing config files.	Routing and transformation live in Logstash pipeline configuration and Elasticsearch ingest pipelines. Better suited to teams comfortable managing pipeline code under version control.
Search and dashboards	Graylog Open provides search and dashboards in its own interface, which covers common log investigation tasks. Confirm whether your analysts need features beyond these before committing.	Kibana offers open-ended exploration, custom visualizations and query flexibility. Matters when analysts build their own analysis beyond standard dashboards. Confirm the Kibana features your license tier includes.
Alerting and notifications	Event definitions run for real-time and historical monitoring, with notifications to PagerDuty, Slack and email listed on the Graylog Open product page. Suits small teams that want alerts without building rule infrastructure.	Alerting depends on the Elastic subscription tier. Confirm which alerting features your tier includes, since anomaly-based alerting is limited to paid tiers under the subscription page.
Index retention	Index rotation by message count, size or time, with retention that deletes the oldest indices. Covers most retention needs, though archiving and data tiering sit in paid Graylog editions.	Index lifecycle and data tiers (hot, warm, cold, frozen) are part of the Elasticsearch node model. Gives finer control over storage cost, but you design and operate the policies yourself.
SIEM content	Prebuilt Illuminate detection content, correlation and reporting sit in paid Graylog Enterprise or Graylog Security editions, not Graylog Open. Confirm the content included in your edition before planning detections.	Detection engine, machine learning and case management are listed under Platinum, which is no longer sold to new customers, and endpoint protection under Enterprise. Confirm current availability with Elastic before planning around any tier.
SSO and access control	Single sign-on and user authentication options are described in Graylog's authentication documentation. Confirm which methods your edition supports against your identity provider.	Basic tier includes TLS, native users and role-based access control. SAML and OpenID Connect single sign-on, plus field- and document-level security, are listed among paid features. Confirm your tier before designing access.
Kibana-style exploration	Not a direct equivalent. Graylog's search is built for log investigation and alert workflows, not general-purpose visual analysis.	Kibana is the main option when analysts need custom dashboards, saved visualizations and broad data exploration across indices. Choose this path if that flexibility is a core requirement.

What Graylog and the Elastic Stack license and charge for

Graylog Open is licensed under the Server Side Public License version 1 (SSPL-1.0) from Graylog 4.0 in 2020 onward, replacing the GPL v3 used by earlier releases. SSPL is not OSI approved, so legal and procurement teams should review it separately from the zero license fee. The paid tiers are priced on processed data rather than users or devices. According to the Graylog pricing page, Graylog Enterprise starts at 15,000 US dollars per year and Graylog Security starts at 18,000 US dollars per year, each with a minimum of 10 GB per day or 100 Graylog Compute Units.

Graylog Open: Free, with no volume limits and community support. Inputs, streams, processing pipelines, search, dashboards and event-based alerts are included.
Graylog Enterprise: Adds a data lake with archive restore, data tiering, a correlation engine and 24/7 support.
Graylog Security: Adds SIEM features such as risk scoring, anomaly detection, investigations, compliance packs and prebuilt threat detection content.
Recurring cost: Paid editions renew yearly and scale with the data volume you process, so a sustained increase in ingest raises the tier you need.

Before you request a quote, confirm the processed-data volume per day, whether you need archive restore or correlation, and whether the minimum applies to your ingest.

What drives the running cost of each stack

Running either stack costs more than licenses. The cards below separate one-time build work from recurring storage, people, paid editions, upgrades and support, so you can compare written quotes on the same basis.

Storage and retention footprint

Storage is usually the largest recurring infrastructure line. Graylog's index guidance sizes log storage as daily ingest times retention days times 120 percent, and the same logic applies to an Elasticsearch cluster you run yourself. Retention length, replica count, hot and cold tiering and the message journal (which Graylog advises sizing at 3 to 5 times daily ingest on SSDs) all raise the footprint. Ask each vendor or partner to state the assumed ingest, retention, replicas and disk type behind its storage estimate.

Skills for each stack

Graylog pairs a Graylog server layer with MongoDB and a search backend, so your team needs operators who understand streams, pipelines and index rotation, plus database and search cluster administration. A self-built Elastic Stack asks for Elasticsearch node roles, Logstash pipelines and Kibana content management, which is more assembly work for a small team. Budget recurring staff time for both, and ask who on your side will hold on-call responsibility for the pipeline.

Paid edition fees

Graylog Open is free, but index archiving, correlation, reporting and prebuilt detection content sit in paid Graylog Enterprise or Graylog Security editions. Graylog's pricing page lists Enterprise from 15,000 US dollars per year and Security from 18,000 US dollars per year, each with a minimum of 10 GB per day or 100 Graylog Compute Units. On the Elastic side, Platinum is no longer sold to new customers, and detection, anomaly detection and SSO features sit in Enterprise. Confirm which features your use case needs before pricing either side.

Upgrade and end-of-life effort

Every stack needs recurring upgrade work, and the timing depends on supported release lines. Elastic maintains core stack 8.x until January 15, 2027 for end of maintenance, with 8.x support ending July 15, 2027, and 9.x end of maintenance on October 15, 2027. Graylog 7.2 requires MongoDB 7.x to 8.2.x and OpenSearch 1.1.x to 3.7.x, and OpenSearch 1.x use is deprecated for Graylog 7.0 and later. Ask for upgrade effort per release line and who tests compatibility across the search, dashboard and collector versions.

Support contracts and quotes

Graylog Enterprise and Security include 24/7 support in their paid tiers, while Graylog Open relies on community support. Elastic support depends on the subscription tier you buy. DeployOpen offers ongoing support, upgrades and continuous testing as retainers and prices fixed-scope work from a written scope, without a published price list. When you request a quote, ask for the scope, the licensed data volume, the support hours, the upgrade cadence included and what is excluded.

Graylog vs ELK Stack switching: what transfers and what is rebuilt

This sequence shows which parts of a log management estate carry over when moving between Graylog and a self-built Elastic Stack, and which parts must be rebuilt and checked before cutover.

Inventory every log source and its purpose
Your team lists each log source, its transport (syslog, Beats, agents, HTTP or API pulls), its owner and the business or security use it serves. Log sources transfer as a concept, but the connection method does not, so this inventory becomes the map for every later step. Think of a source as the stable asset and its collection path as disposable. The step is done when every source has an owner, a transport and a named consumer, and the list has been reviewed by the security and platform teams.
Document retention and index design decisions
Your team records the retention periods, legal hold needs and hot or cold storage expectations for each log class, along with the index design knowledge that worked on the current platform, such as how indices were split, rotated and sized. Retention policy and design reasoning transfer between platforms, even though the implementation does not. Graylog rotates indices by message count, size or time and deletes the oldest indices under its retention settings, while Elasticsearch uses index lifecycle concepts and data tiers, so the decisions must be translated rather than copied. The step is done when a written retention and design register exists and has been approved by the data owner.
Map access roles and identity sources
Your team maps current users, groups and roles onto the target platform, noting which authentication methods are available in the edition you plan to run. Graylog and Elastic handle roles, realms and single sign-on differently, and some SSO or field-level controls depend on the paid tier of each platform, so the role model must be checked against the edition you license, not assumed. Confirm the licensing position for each required feature with the vendor before you design roles around it. The step is done when a role matrix exists that lists every required permission and the edition that provides it.
Rebuild inputs, pipelines and parsers
Your team recreates collection in the target platform: Graylog inputs, streams and processing pipelines on one side, or Beats, Elastic Agent and Logstash pipelines on the other. Parsing logic usually has to be rewritten because Graylog pipeline rules and Logstash filter configurations are not interchangeable, so each parser is tested against sample messages from the real source. The step is done when each source produces normalized fields in the target platform that match the field names your searches and detections depend on.
Rebuild dashboards, event definitions and alert rules
Your team rebuilds the searches, dashboards, event definitions and Kibana or Graylog alert rules that analysts use every day. Detection logic does not port as a file copy: each rule must be rewritten in the target format, its thresholds re-tested, and its notification channels reconnected, for example to email, Slack or PagerDuty where the chosen edition supports them. The step is done when every rule in the inventory has a target equivalent, a documented owner and a test that shows it fires on known-bad sample events.
Run both platforms in parallel
Your team keeps collecting into the existing platform while the new one receives the same sources, and compares alert volumes, field coverage and search results between the two. Parallel running is the usual way to find parsing gaps and detection drift before cutover, because a rule that looks correct can fire on different fields or miss events that the old platform caught. The step is done when each detection has matched or been explained on both platforms, and the discrepancy log is empty or accepted in writing.
Cut over and retire the old platform on a set plan
Your team switches analyst workflows, notification routing and any upstream forwarders to the new platform, then keeps the old cluster read-only for historical search until the agreed retention window ends. Before retiring it, confirm that archived data is exported in a form the new platform or your records system can still read. The step is done when forwarders point only to the new platform, the old platform is read-only, and the data owner has signed off on the retirement and archive plan.

Where Graylog and Elastic Stack projects usually run long

Most schedule overruns on either stack come from work that the product page does not show. A Graylog build starts with the platform itself: Graylog server nodes, a MongoDB deployment that holds configuration and metadata, and a search backend, which Graylog documents as Graylog Data Node or self-managed OpenSearch within the supported version range. For medium to large deployments, the multi-node guide describes three Graylog and MongoDB nodes with MongoDB as a replica set, three Data Nodes on their own cluster, a load balancer, and is_leader set to false on follower nodes. Retention tuning is where teams slip. Index rotation by message count, size or time and deletion of the oldest indices need to match the storage sizing formula in Graylog's system architecture guidance, and the message journal needs fast disks sized to the ingest rate. Confirm the ingest volume and retention period in writing before anyone sizes the cluster.

An Elastic Stack build splits the same work across more components. Logstash pipeline design is usually the largest item, because every source needs its parsing, field normalization and dead-letter handling written and tested before dashboards can be trusted. Index lifecycle policies then have to map hot, warm, cold and frozen tiers to the node roles of the Elasticsearch cluster, and a highly available cluster needs at least three master-eligible nodes. Security configuration adds role mapping for single sign-on: SAML or OpenID Connect integration, and the mapping of identity provider groups to Kibana and index roles, which is often unfinished at go-live. Dashboards and alerts from any earlier system must also be rebuilt by hand, since they do not carry over automatically. Licensing is a late decision that causes rework, because features such as SSO, field-level security and anomaly-based alerting sit in paid subscription tiers that should be confirmed against Elastic's subscription page before the design is frozen.

Both projects slip most often at the same two points: log parsing and SSO role mapping. DeployOpen plans and implements these pieces inside the client's own cloud accounts, data centers or air-gapped networks, under a written scope that names the sources, pipelines, tiers, identity mappings and deliverables before work starts. Ask any implementation partner, including DeployOpen, to list the log sources in scope, the parsing and mapping tests that will run, and the owner of each licensing decision, so the effort is visible before the quote is accepted.

Questions buyers ask before choosing Graylog or the Elastic Stack

What does a self-hosted Graylog or Elastic Stack deployment cost to run?

Most of the cost is people time and infrastructure, not the software itself, because Graylog Open and the Elastic Basic tier are free to download. Graylog Enterprise is priced from 15,000 US dollars per year and Graylog Security from 18,000 US dollars per year, according to Graylog's pricing page, with a minimum of 10 GB per day or 100 Graylog Compute Units. Recurring costs include servers or cloud instances, storage sized to daily ingest times retention, licenses for any paid tier, and the staff who patch, tune and respond to alerts. Ask any vendor or partner for a quote built from a written scope that names log volume, retention, node count and on-call coverage.

How long does a log management deployment take to stand up?

The duration depends on scope rather than on the product alone. A single-node Graylog build with a few log sources is a different project from a multi-node cluster with a MongoDB replica set, a separate search cluster, a load balancer and parsing for dozens of sources. Graylog's multi-node guide recommends three Graylog and MongoDB nodes plus three Data Nodes for medium to large deployments, and the Elastic Stack adds design work for node roles and tiers. DeployOpen works from a written scope with agreed deliverables and timelines, so the schedule should be set there, not guessed from this page.

What must our team provide before an implementation starts?

Three inputs decide whether a log platform works in the first month: the log sources, the storage and hardware, and the people who will act on alerts. List every source you need (firewalls, identity systems, cloud audit trails, endpoints, applications) with its expected daily volume and format. Confirm where storage will live, which hardware or cloud accounts are available, and how retention must meet your policy. Name an identity provider for single sign-on, and name on-call owners who will receive and close alerts. Note that single sign-on on the Elastic side sits in paid subscriptions, so confirm that requirement early.

Can a small security team run either stack without outside help?

A small team can run either stack, but it needs someone who can own indexing, retention, upgrades and rule tuning, and that work recurs. Graylog's product is more opinionated, with inputs, streams, pipelines and event definitions in one interface, which can shorten the learning curve for a lean team. The Elastic Stack gives more control over dashboards and data, and it needs more configuration to reach the same workflow. Check the support windows: Elastic's end-of-life page lists the core 8.x maintenance end on January 15, 2027, so plan upgrades in your own calendar. Whether you can do this alone depends on your staffing, so test it against the written scope.

Is Graylog Open enough for alerting, or do we need a paid edition?

Graylog Open covers basic alerting: event definitions run real-time and historical checks, and notifications can go to PagerDuty, Slack and email, according to the Graylog Open product page. It does not include the correlation engine, which is part of Graylog Enterprise, or the prebuilt Illuminate detection content, which is part of Graylog Enterprise or Graylog Security. If your detections depend on correlating events across log types or on prepackaged threat content, price those paid editions into the decision. If you only need threshold alerts on known events, Graylog Open may be enough, and you should test that against your own rules before buying.

What do SSPL and Elastic License 2.0 mean for running a log platform inside our company?

Running either product on your own infrastructure for internal security monitoring is generally a question for your legal team, not a reason to avoid either tool, but the two licenses are not open source under the OSI definition. Graylog Open uses the Server Side Public License version 1, which Graylog adopted from 4.0 in 2020. The Elastic default distribution uses the Elastic License 2.0, while Elastic also offers AGPLv3 as an OSI-approved option. Read the license text, confirm with counsel whether offering the platform to outside parties triggers restrictions, and record the decision. Ask vendors to state in writing which license applies to the exact version you deploy.

Which parts of a log platform does DeployOpen handle, and which stay with our team?

DeployOpen plans, implements, integrates, hardens, backs up, upgrades, documents and supports self-hosted open-source platforms inside your own cloud accounts, data centers or air-gapped networks, so it can cover the build and the runbooks for either stack. DeployOpen also prepares systems, controls and evidence for compliance assessments, but independent auditors issue any audit reports or certifications. Your team still owns business decisions: which log sources matter, who acts on alerts, and what retention your regulators require. Ongoing support and upgrades are available as retainers, and most engagements are fixed-scope with written deliverables.

How DeployOpen helps choose and implement either stack

DeployOpen plans, implements, integrates, hardens, backs up, upgrades and documents self-hosted platforms inside your own infrastructure, so the choice between Graylog and a self-built Elastic Stack is made against your sources, retention and licensing position. We work from a written scope before any build starts.

How we scope

Inventory log sources, daily ingest volume and retention periods before choosing a backend or edition.
Confirm which license terms your legal and procurement teams accept, including SSPL and ELv2 obligations.
Agree in writing which Graylog or Elastic features are in scope, and which paid tiers are required.

How we build

Deploy the chosen stack in your cloud accounts, data centers or air-gapped networks, with the storage layout sized to your retention.
Configure inputs, streams, pipelines or Logstash parsing, and alert routing to your existing on-call tools.
Test alert paths and search performance against representative log samples before production cutover.

How we hand over

Deliver runbooks covering index rotation, retention, backups, upgrades and certificate handling for your team.
Document the configuration, access model and license position so auditors and assessors can review it.
Walk your operators through monitoring, troubleshooting and the upgrade path for the version you run.

How we support

Offer ongoing support, upgrades and continuous testing as a retainer after handover, if your team wants it.
Plan version upgrades around each vendor's published support windows and compatibility matrix.
Revisit the edition and storage decision when log volume, compliance scope or licensing terms change.

Graylog vs ELK Stack