Flowable or Temporal: which fits your process problem
Choose Flowable when the process itself is the product of the work: a standards-based business process model that process owners, analysts and architects need to read, change and audit. Flowable's open-source engines support BPMN, CMMN and DMN, run embedded in a Java application or as a standalone service, expose Java and REST APIs, and are licensed under Apache-2.0. Choose Temporal when engineers own the orchestration of services and want durable execution expressed as code. Temporal Server is MIT licensed, and workflows are written in Go, Java, TypeScript or Python. The decision turns on three questions: who designs and changes the process after go-live, whether people (approvers, case handlers, reviewers) are steps in the flow, and what your team can operate for years. A process model that a business analyst must edit points toward Flowable. A saga coordinating payments, inventory and notifications across microservices points toward Temporal.
Map each open question to a concrete artifact before you shortlist further. Ask who will edit the process after launch and whether they will work in BPMN diagrams or in pull requests. List every human task and decide whether it needs an inbox, a form and an SLA, which favors Flowable's task model. For service-only flows, check whether your engineers already run the languages Temporal supports and whether a Temporal Service is a platform you can staff. Temporal's self-hosted Service has several internal roles (Frontend, History, Matching and Worker services) plus a persistence store, and the Temporal Service documentation lists the components to plan for. Confirm with each vendor which persistence stores and versions your standards and security review accepts.
Treat licensing and versioning as part of the fit test, not an afterthought. Flowable's open-source engines are Apache-2.0, while Flowable sells a separate commercial platform on top, so confirm which capabilities your requirements depend on. Flowable 8.0.0 moved to Spring Framework 7 and Spring Boot 4 and dropped Spring Boot 3 support, so check that your Java stack can follow. Ask Flowable and Temporal for their current support and upgrade commitments in writing, and ask how long each version line will be maintained. Last, prototype the riskiest path on both platforms: one human approval with an escalation timer for Flowable, and one multi-service compensation flow with a forced worker failure for Temporal. The prototype result will tell you more than a feature matrix.
Which platform fits which scenario
This table maps common scenarios to the platform that usually fits better and the condition under which the other one would be the stronger choice. Read each row by first asking who owns the process logic and how long the state must survive, because those two questions drive most of the outcome.
| Scenario | Better fit | When the other platform wins |
|---|---|---|
| Loan or claims approvals with human tasks | Flowable: BPMN user tasks, assignments and audit trails let business analysts and process owners model approvals that people act on directly. | Temporal fits when approvals are really service calls with a code owner and no business-side model is needed. |
| Case management with CMMN | Flowable: supports CMMN alongside BPMN, so unpredictable, case-driven work with optional stages can be modeled as a case rather than forced into a fixed sequence. | Temporal fits when the work is a predictable code path, since CMMN case modeling is not part of its code-first model. |
| Decision tables owned by the business | Flowable: DMN decision tables can be maintained by policy or operations staff and called from BPMN processes, keeping rules out of application code. | Temporal fits when rules are tightly coupled to service logic and engineers should own every change through code review. |
| Microservice saga orchestration | Temporal: workflows written in general-purpose languages can coordinate compensating steps across services, with the event history supporting replay after failures. | Flowable fits when the saga is a business process that a process owner needs to see, edit and report on as a BPMN diagram. |
| Payment or provisioning retries across services | Temporal: retry policies and durable timers are expressed in workflow code, and execution resumes from recorded history after worker or service failures. | Flowable fits when retries are part of a documented approval or exception path that operations staff must monitor in a process console. |
| Long-running processes waiting on external events | Temporal: a workflow can wait for signals or timers over long periods, with state kept in its history rather than in application tables. | Flowable fits when waiting states are business milestones that must be visible and reportable to non-engineers. |
| Data-heavy batch flows | Neither is the default: pipelines over large datasets usually belong in a scheduler built for DAGs, so confirm fit with Apache Airflow before choosing either. | Temporal or Flowable fit only when batch steps are business-controlled or service-driven rather than scheduled data transformations. |
| Team skills and ownership | Confirm with your own team: Flowable suits Java teams who share modeling with business owners, while Temporal suits teams comfortable operating a workflow service and writing workflow code. | Choose by who will maintain the process in year three, not by the engine's feature list alone. |
How each engine is built and deployed
Flowable and Temporal differ most in where the engine lives and who operates it. One runs inside your application or as a service you already know how to run, the other is a multi-service cluster with its own persistence layer. The cards below cover what each choice means for databases, upgrades and framework versions.
Embedded engine or standalone service
Flowable's open-source engines run embedded in a Java application or as a separate service, and expose both Java and REST APIs. Embedding ties the process engine's release cycle to your application, so a team with one Spring-based product may prefer it, while a team serving many applications may prefer a shared service. Confirm which deployment shape your application architecture supports before choosing. Embedding means the engine upgrades with your application.
Temporal's self-hosted service topology
A self-hosted Temporal Service runs Frontend, History, Matching and Worker services, plus a persistence store and a visibility store. Each service scales and fails separately, which gives capacity control but adds components to monitor. Your platform team should expect to operate every tier, not only the application code that runs workflows. Ask for the expected service count and sizing guidance from your own deployment review before committing.
Who owns the database
In Flowable, the engine writes process state to the relational database your application already connects to, so database administration usually stays with the same team that runs your application data. In Temporal, the persistence and visibility stores are part of the platform itself. Decide who backs up, patches and tunes each database before go-live, and whether your DBA team has experience with the store Temporal supports in your environment.
Temporal persistence options
Temporal's tested persistence options are Cassandra, PostgreSQL and MySQL. SQLite is supported only for development and should not appear in production plans. Choosing the store determines your backup tooling, failover design and the skills your operations team needs. Check which options your organization already runs and operates at the required scale, then confirm the exact supported versions for your chosen store against the persistence documentation.
Flowable 8.0.0 and Spring Boot 4
Flowable 8.0.0, released February 27, 2026, is based on Spring Framework 7 and Spring Boot 4, and drops Spring Boot 3 support. Any Spring Boot 3 application that embeds Flowable must migrate its framework stack before or alongside the engine upgrade. Plan that migration as a dependency change across the whole application, and test custom listeners, connectors and security configuration against the new framework versions.
Staging upgrades in each model
An embedded Flowable upgrade moves with the application release train, so staging happens in the same pipeline as the product. A Temporal upgrade affects a running cluster that hosts workflows of many teams, so rollout order, version compatibility and worker deployment need a written plan. Ask each vendor, or your implementation partner, how in-flight workflows are handled during an upgrade and which test environment proves it before production.
Capability comparison: modeling, state, and extensibility
This table compares how Flowable and Temporal model work, keep long-running state, and extend into your systems, with the points you should confirm with each vendor. Read it by first deciding who authors the process, then checking which row answers your persistence and integration questions. The main takeaway is that Flowable centers on standards-based process models that business and process teams can read, while Temporal centers on code that engineers version and test like any other service.
| Capability | Flowable | Temporal |
|---|---|---|
| Modeling standards | Supports BPMN, CMMN and DMN, so process, case and decision models can be expressed in standard notations | Workflows are written as code in general-purpose languages; no BPMN, CMMN or DMN standard is part of the core model |
| Who authors the process | Process analysts and developers can model in standard notations, though the open-source engines do not ship a business-user modeling studio | Software engineers author workflows in Go, Java, TypeScript or Python and review them through code review |
| Deployment shape | Runs embedded in a Java application or as a standalone service | Runs as a self-hosted service with Frontend, History, Matching and Worker services plus data stores |
| Java and REST APIs | Exposes Java and REST APIs for engine and task operations | Client SDKs exist for its supported languages; confirm the exact API surface for your chosen SDK |
| Execution state and replay | Keeps process state in the engine database for the life of the process instance | Keeps a complete ordered event history used to replay and resume workflows after failures |
| Visual process modeling | Standard BPMN diagrams can be created with external modeling tools and deployed to the engine; confirm tooling with Flowable | No visual modeler is part of the core product; confirm whether any third-party visualization fits your process |
| Self-hosted persistence | Relational database backing confirmed by Flowable documentation; confirm supported databases for your version | Tested options are Cassandra, PostgreSQL and MySQL, with SQLite for development only |
| Human tasks and user interface | Human task handling is part of BPMN modeling; confirm the task UI and identity integration details with Flowable | Human-in-the-loop steps are built in code; confirm how your team wants to expose approvals and interfaces |
What is open source and what is paid
The Flowable open-source engines support the BPMN, CMMN and DMN standards and are licensed under Apache-2.0. You can run them embedded in a Java application or as a standalone service, and use the Java and REST APIs without a license fee for the engine itself. Flowable also sells a separate commercial platform on top of the open-source engines, so the paid layer is an addition you choose, not a replacement for the engine.
- Engine license: Apache-2.0 covers the open-source BPMN, CMMN and DMN engines, subject to the terms of that license.
- Commercial platform: Flowable's paid product sits on top of the engines. Confirm which of its components you actually need before you buy.
- Support and maintenance: Ask whether a paid agreement is required for vendor support, security fix timing or upgrade assistance.
- Deployment choice: The engines run embedded or as a service, so the license cost does not depend on the hosting model.
- Version currency: Flowable 8.0.0 was released on February 27, 2026. Confirm the support window for the version you plan to adopt.
Ask Flowable which features in your shortlist come from the open-source engines and which require the commercial platform, and get that split in writing.
Temporal Server is licensed under the MIT license, so the self-hosted server can be used, modified and distributed under permissive terms. The Temporal SDKs and workflow code you write for Go, Java, TypeScript and Python are part of your own application. Temporal's hosted offering and any enterprise features are separate commercial matters, and the open-source server does not define what they include.
- Server license: MIT covers Temporal Server as published in the temporalio/temporal repository.
- Self-hosted cost: You carry the infrastructure and operations for the Frontend, History, Matching and Worker services plus the persistence and visibility stores.
- Hosted offerings: Confirm what Temporal Cloud or any managed service includes, how it is priced, and which features are limited to it.
- Enterprise features: Ask whether any capability you need, such as specific security or support features, is available only under a paid agreement.
- Version currency: Current lines include v1.32, with v1.32.1 released on October 8, 2026. Confirm the support policy for the release you adopt.
Before you commit, ask Temporal in writing which features are open source, which belong to hosted or enterprise offerings, and what support is included.
Open-source licenses are short documents, but their effect on your organization depends on how you deploy, modify, bundle and offer the software. Both Apache-2.0 and MIT are permissive, yet each carries notice and attribution obligations, and any commercial add-on has its own contract. Your legal and procurement teams should review the actual license texts and vendor agreements that apply to your deployment rather than rely on a summary.
- Source of truth: Read the license file in the exact repository and release you will deploy, not a secondary description.
- Bundled components: Check the licenses of dependencies, container images and plugins you add, since they may differ from the core engine.
- Commercial terms: Review the order form, support terms and any restrictions on use, hosting or redistribution.
- Change risk: Ask how the vendor will communicate license or edition changes, and what notice you receive.
- Exit terms: Confirm your right to keep running a version you have already deployed if the commercial relationship ends.
DeployOpen does not provide legal advice on licensing, so have counsel confirm these points for your environment.
How identity and access integrate with each platform
Flowable and Temporal place identity in different layers. Flowable sits inside your Java application or service, so user task access and API security follow your application's stack. Temporal separates the server, the API clients and the workers that run code, so service identity and network boundaries carry more of the design.
Java embedding and application security
When Flowable runs embedded in a Java application, the engine inherits the security model of that application. Task inboxes, process administration and engine APIs are protected by whatever your application uses for authentication and authorization. Confirm with Flowable's documentation how its Java APIs expect the calling context to be established, and whether identity is passed in from your application or resolved by the engine. Test this with a real user task before committing to a design.
REST API authentication
Flowable exposes REST APIs alongside its Java APIs, so every endpoint that starts processes, claims tasks or reads variables needs an authentication decision. Decide which callers may act on which process definitions, and whether service accounts are separate from human users. Confirm the supported authentication mechanisms, token handling and how authorization is enforced per endpoint with the current Flowable documentation for your version.
SSO for user task inboxes
Business users reach Flowable through task inboxes, forms or your own portal, so single sign-on usually belongs in the application layer rather than the engine. Map how a corporate identity provider's groups become candidate groups for tasks, and how a user's access ends when they leave a role. Confirm how your chosen front end integrates with the identity provider, and test the reassignment path for tasks held by departed staff.
API access to Temporal
Temporal clients start, signal and query workflows through the Temporal Service's API, and the Frontend service is the entry point for those calls. Decide which applications may start or terminate workflows, and whether operators get separate credentials from automation. Confirm with the Temporal Service documentation which authentication and authorization options apply to your deployment, since the server and client settings differ by setup.
Service identities for workers
Temporal workers run your workflow and activity code, and they connect to the Temporal Service over the network. Each worker fleet is a distinct workload that calls downstream systems with its own credentials, so give it a service identity scoped to what its activities need. A shared database account across workers is the most common shortcut to avoid. Confirm how workers authenticate to the server in your environment, and rotate those credentials through your normal secrets process.
Network boundaries between components
A self-hosted Temporal deployment has several internal services and persistence stores that should not be reachable from general networks. Plan segmentation so only workers and approved clients reach the Frontend, and only the History, Matching and Worker services reach the persistence layer. For Flowable, the equivalent question is which database and external systems the embedded engine can reach. Confirm the required connectivity with the Temporal documentation for your version before drawing firewall rules.
Audit of process decisions
Auditors will ask who approved a decision, who changed a process definition and which identity triggered a workflow run. Flowable records process history in its database, and Temporal keeps an ordered event history per workflow, but neither automatically answers every access question. Define what must be logged in your identity provider, your API gateway and your application, and confirm which audit features each platform provides in its current documentation before relying on them.
What drives the running cost of each
This table compares the recurring and one-time cost drivers for Flowable and Temporal, from database and cluster infrastructure to skills, support and upgrades. Use it to build a quote request, since neither platform's cost is fixed by its license alone.
| Cost driver | Flowable | Temporal |
|---|---|---|
| Licensing | Open-source engines are Apache-2.0 licensed with no license fee. Flowable sells a separate commercial platform, so confirm in writing whether any commercial component is in scope. | Temporal Server is MIT licensed. Confirm with Temporal whether any managed or enterprise offering is in scope for your quote. |
| Infrastructure | Engines run embedded in a Java application or as a service. Recurring cost is the application hosting plus a relational database for process state. | A self-hosted Temporal Service runs Frontend, History, Matching and Worker services plus persistence and visibility stores. Recurring cost is the cluster plus the database, which is usually larger than a single embedded engine. |
| Database | Process, task and history data sit in one relational database. Ask how its size and backup window grow with process volume and history retention. | Tested persistence options are Cassandra, PostgreSQL and MySQL, with SQLite for development only. Ask which store your team will operate and who owns its tuning and backups. |
| Skills | Business analysts and architects model BPMN, CMMN and DMN, and Java developers maintain the embedded engine. Recurring cost is mostly Java and process-modeling capacity. | Developers write workflows in Go, Java, TypeScript or Python, so SDK expertise is needed. Operating a distributed cluster also requires people who understand persistence and failover. |
| Support and retainers | Ask whether vendor support is needed for the open-source engines or only for a commercial platform. Ongoing DeployOpen support and upgrades are available as retainers, scoped in writing. | Ask whether vendor support is needed for the open-source server or only for a managed service. Ongoing DeployOpen support, upgrades and testing are available as retainers, scoped in writing. |
| Upgrades | Flowable 8.0.0, released February 27, 2026, is based on Spring Framework 7 and Spring Boot 4 and drops Spring Boot 3 support. Budget effort for application framework migration if you run Spring Boot 3 today. | Temporal ships on regular release lines, including v1.32. Plan recurring effort for server version upgrades and SDK updates across the services that run workflows. |
| Editions | Community engines are free to use under Apache-2.0. Commercial editions add features and support, so confirm which edition your requirements need before quoting. | Server is MIT licensed. Confirm which features, such as multi-cluster or managed hosting, require a paid offering, and price them separately. |
| One-time versus recurring | One-time: modeling, integration and hardening. Recurring: hosting, database, Java maintenance, upgrades and support. | One-time: workflow design, SDK integration and cluster build. Recurring: cluster operations, persistence, SDK upgrades and on-call support. |
Moving between Flowable and Temporal later
This sequence shows a team how to carry business knowledge across the boundary between a BPMN engine and a code-first durable execution platform, and how to run both during cutover without losing work in flight. Running instances rarely migrate directly, so the plan focuses on definitions, decisions and operating practice.
Inventory processes by owner and lifecycle
Before choosing a direction, list each process or service flow, who owns its business rules, how often it changes, and how long a single instance can stay open. Tag each as human-centric (approvals, case handling, reviews) or service-centric (system-to-system sequences, retries, saga-style compensation). Engineering leads and process owners do this together. The output is a register that shows which items suit a BPMN engine, which suit durable code, and which need both. Confirm the category with the process owner before anything is rebuilt.
Separate transferable assets from engine-specific code
Mark what carries over unchanged: written requirements, process narratives, decision tables as business artifacts, glossary terms, and the reasoning behind exception paths. Flowable's DMN decision tables are standards-based artifacts that business analysts can review directly, which makes them easier to keep as the source of truth. Engine-specific pieces such as service task bindings, listeners, and Java delegates are not portable. The output is a signed-off list of assets that will move and a separate list of code that will be rewritten.
Decide which side owns the process definition
Name the system of record for each process. In a BPMN-first design, the diagram is the artifact that business and engineering review together. In a Temporal design, the workflow code is the artifact, and the business view must be produced from documentation or generated diagrams. Record who can change a definition, how changes are reviewed, and where the decision logic lives. Confirm with your compliance lead whether the auditor expects a model, code, or both as evidence of process control.
Rebuild one pilot process on the target engine
Pick one low-risk process that has a clear start, end, and measurable outcome. Rebuild it on the target platform: BPMN models into Temporal workflow code and activities, or workflow code into BPMN and service tasks in Flowable. Reuse the decision tables from step two so business rules do not change during the move. Run the pilot against recorded test inputs and compare outcomes with the original. The pilot is complete when outputs match on agreed cases and the team can explain any difference.
Define the rule for in-flight instances
Decide, per process, how instances that already started will finish. Common options are letting them complete on the old engine, draining them over a window, or restarting them on the new engine from a defined checkpoint. Running instances hold state in engine-specific formats, so direct migration is rarely practical. Document the rule, the cutoff date for new starts, and who approves exceptions. The output is a written drain plan that operations and business owners have signed.
Run both engines during cutover with routing rules
Operate the old and new engines in parallel. New process starts go to the target engine once a process passes its pilot. Existing instances continue on the source engine until they close. Route inbound events, such as messages and timers, by process identifier so each event reaches exactly one engine. Monitor both sides with the same dashboards and alert thresholds. The phase ends when the source engine has no open instances for the migrated processes and the routing table shows no remaining traffic.
Rebuild monitoring, support runbooks and retirement
Recreate operational visibility on the target platform: instance search, failure alerts, retry and compensation handling, and audit trails for business users. Update support runbooks so operators know where to look for a stuck process. Retire the source engine only after the drain is complete and logs are archived under your retention policy. Keep a record of the decisions made during the move, which will serve as evidence for change management and any compliance assessment. The output is a closed cutover record and a decommissioning checklist.
Where implementation projects usually run long
Most delays on a Flowable project start before any Java code is written, with process ownership. Someone must own each BPMN, CMMN or DMN definition, approve changes to it, and decide which decisions stay in a DMN table and which move into service code. When that owner is unclear, models get rebuilt by developers, business reviewers stop trusting the diagrams, and rework lands late. Implementation also means planning the Java integration (embedding the engine in a Spring application or running it as a service), choosing the database and schema upgrade approach before go-live, and designing the user task interfaces that people will actually use to complete work. Ask the vendor or your integrator to confirm which Spring Framework and Spring Boot versions the chosen Flowable release supports, since Flowable 8.0.0 dropped Spring Boot 3 support, and plan the upgrade path for your existing application stack.
Temporal projects tend to run long for different reasons. The first is service decomposition: teams must decide which steps belong in a workflow, which belong in activities that call external systems, and how long-running state maps onto that split. The second is determinism. Workflow code must produce the same decisions when replayed from the event history, so engineers need to route time, randomness, and external calls through the SDK and Temporal's versioning mechanisms rather than calling them directly. Violations often surface only in testing or after a worker restarts, which makes them expensive to find. Worker deployment, the Frontend, History, Matching and Worker services of a self-hosted Temporal Service, and the persistence and visibility stores each need capacity planning and on-call ownership. Confirm your supported persistence choice against the Temporal persistence documentation before you commit to a store.
Questions buyers ask before choosing or hiring help
Does Flowable or Temporal cost more to run in production?
Neither open-source core carries a license fee under its terms, so the cost difference sits in infrastructure, people and operations. Flowable's engines are Apache-2.0 licensed and run embedded in a Java application or as a service, so the main recurring costs are the application runtime, the database and the staff who maintain BPMN, CMMN and DMN models. Temporal Server is MIT licensed, but a self-hosted Temporal Service runs Frontend, History, Matching and Worker services plus persistence and visibility stores such as Cassandra, PostgreSQL or MySQL, which usually means a larger operating footprint. Ask every quote for infrastructure sizing for each stack, who patches and upgrades each component, and what monitoring and backup testing are included.
How long does a Flowable or Temporal implementation take?
No single duration fits both platforms, because the timeline depends on how many processes or services are in scope, how many integrations exist, and how much of the design must be hardened and documented. A rollout of a few approval processes against existing systems is scoped very differently from a set of durable service workflows that need retries, compensation and several programming languages. We do not give a figure here because no researched figure supports one for either platform, and a number without a written scope would be guesswork. Most DeployOpen engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work starts, so the timeline follows from the scope. Ask for a phased plan with named milestones and a description of the first production process.
What does a Flowable or Temporal project need from our internal team?
Both platforms need people who will own the runtime after go-live, and the skill mix differs. Flowable projects need Java and Spring-literate engineers, because the engines embed in Java applications, and process owners who can review BPMN, CMMN and DMN artifacts. Flowable 8.0.0 is based on Spring Framework 7 and Spring Boot 4 and drops Spring Boot 3 support, so check your current Spring versions before you commit. Temporal projects need engineers who write workflows in Go, Java, TypeScript or Python and who understand how workflow code replays from event history and how running workflows are versioned. Both need a platform owner for databases, networking, identity integration and backups. Confirm staffing levels in the written scope.
Can business analysts model processes in Flowable and Temporal?
Business analysts can model processes in Flowable using the BPMN, CMMN and DMN standards, and those models can be reviewed by people outside engineering. The executable details, such as service tasks, data mappings and error paths, still need developer work. Temporal workflows are written as code in general-purpose languages, so in practice analysts describe the process and engineers implement it. Temporal fits service orchestration better than process designs that the business owns directly. Whether analysts can change live models depends on your governance: confirm which modeling tools your organization will use, who approves changes, and how a new model version reaches production. Test analyst-led modeling in a pilot before you rely on it.
Can our own engineers do the implementation without an outside partner?
Yes, if your team has the skills described above and time to build operating practices. Both engines are open source, so there is no vendor gate to start a proof of concept. Production is harder: backups, upgrades, security hardening, identity integration and evidence for audits all take sustained effort. Temporal's self-hosted service has more components to run, and Flowable adds application-level responsibilities, so the gap usually shows up in operations more than in building the first process. DeployOpen plans, implements, customizes, integrates, hardens, backs up, upgrades, documents and supports self-hosted open-source platforms inside your own infrastructure. Use an outside partner for the parts your team cannot staff, and write the division of work into the scope before you start.
Can we start with one engine and add the other later?
Yes, in principle, because the two platforms address different kinds of work and can run side by side. A common pattern is to keep human-approval processes on a BPMN engine and move long-running service coordination to a durable execution engine, with a clear integration boundary between them. Plan that boundary carefully: decide which system owns each process state, how messages cross it, and how you observe both. Adding the second engine later means a second runtime to patch, back up and monitor, so budget that operational load from the start. If you begin with Flowable, your BPMN models stay in an open standard. If you begin with Temporal, your process logic lives in code. Ask any partner to show the boundary design in the written scope.
Do licensing terms change the total cost of Flowable or Temporal?
For the open-source cores compared here, permissive licenses mean license fees are rarely the main cost driver. Flowable's engines are Apache-2.0 licensed, and Flowable sells a separate commercial platform on top, which you need only if you choose it. Temporal Server is MIT licensed. Confirm the license of every component in your stack, including the persistence store, database drivers and any add-ons, because those can carry different terms. Also check whether your support model needs a commercial agreement, since an open-source license does not include vendor support. Ask each quote to list every component, its license, and whether support is included or priced separately.
Does DeployOpen offer ongoing support after go-live?
Yes. Ongoing support, upgrades and continuous testing are available as retainers, which are separate from the fixed-scope implementation. A retainer covers recurring work after go-live, such as upgrades, patch handling and testing, and its scope should be written down with the same care as the build. DeployOpen does not publish a price list, so a quote follows from the written scope. For each engine, ask what is included: upgrade windows for the platform and its runtime dependencies, backup restore testing, and how incidents are handled. DeployOpen does not issue audit reports, attestations or certifications, so ask how it will prepare systems and evidence for an independent assessor.
How DeployOpen helps choose, implement or migrate
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 Flowable vs Temporal, we start by establishing which kind of process or service flow you need to run, then scope the work in writing before any build begins.
How we scope
- We confirm which processes are business-owned BPMN, CMMN or DMN models and which are code-owned service orchestrations.
- We record the hosting target, database choice, identity provider and existing Camunda or Java estate in the written scope.
- Engagements are fixed-scope, with deliverables and timelines agreed in writing before work starts.
How we build
- We install and configure the chosen engine, whether Flowable embedded in a Java application or run as a service.
- We integrate REST and Java APIs with your identity, logging and existing services, and test failure and restart behavior.
- We run security testing on the application and APIs, and prepare controls and evidence for compliance readiness reviews.
How we hand over
- We document the architecture, process model ownership, deployment steps, backup and upgrade procedures for your team.
- We deliver runbooks for persistence, state retention and recovery so operators can run the platform without us.
- We walk your engineers and process owners through the models and the handover package before closing the engagement.
How we support
- Ongoing support, upgrades and continuous testing are available as retainers once the platform is live.
- We can plan version upgrades against the engine's published release notes and your own test environment first.
- Ask us to confirm support scope, response expectations and retainer terms in the written proposal before you decide.
