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Neither Temporal nor Spring Batch can guarantee that every Java job finishes successfully. They make progress and failures visible in different ways: Spring Batch records job and step executions in a JobRepository, while Temporal distinguishes retried Workflow Task failures from failed Workflow Executions. To diagnose a job that seems to have stopped, first identify its persisted state; then use the recovery behavior appropriate to that framework rather than blindly relaunching it.
How Temporal and Spring Batch handle job progress and failure
| Concern | Spring Batch | Temporal |
|---|---|---|
| Execution model | A job is made up of steps, with execution metadata persisted by a JobRepository. Spring Batch: Configuring a Job | Java applications define Workflows, Activities, and Workers. Temporal Java SDK developer guide |
| How progress is recovered | Restart behavior depends on the persisted execution state and job and step configuration. Completed steps are normally skipped on restart, though configuration can allow them to run again. Job configuration and step restart configuration | Workflow history supports replay and recovery. A retried Workflow Task is not the same as a new Workflow Execution run. Temporal: Tasks |
| What happens after a process or task failure | An abrupt JVM or host failure can leave a repository record in STARTED; the repository may not know that the process is gone. Recovery requires an operator decision. Spring Batch: Advanced Metadata Usage | A failed Workflow Task is retried while the Workflow Execution remains open. A failed Workflow Execution closes; another run requires an applicable retry policy. Temporal: Tasks |
| Retry behavior | Configure retries for selected transient exceptions, accounting for the Spring Batch version in use. Spring Batch: Retry | Retry behavior depends on whether a task or execution failed and on the configured policy; not every failure means an execution will restart. Temporal: Tasks |
Why did my Spring Batch job stop without failing?
“Stopped without failing” can describe several different states, so start with the recorded execution rather than the process log alone. Find the exact JobInstance and its JobExecution, then inspect the job’s BatchStatus and ExitStatus alongside those of each StepExecution. Spring Batch records execution state in the JobRepository, but those fields do not always tell the same story.
In particular, a job-level COMPLETED status does not by itself prove every step succeeded. Flow transitions can result in a completed job even when a step failed, so check step outcomes as well as the job outcome. The framework documents how flow transitions affect execution: Controlling Step Flow.
Also check whether the process ended cleanly and whether the JobRepository is durable and configured as expected. If the JVM or host disappeared abruptly, the repository may still say STARTED because it did not receive a final update. A STARTED record is evidence of the recorded state, not proof that the worker is still running.
How to recover a Spring Batch job stuck in STARTED
- Identify the exact execution. Use the JobInstance and JobExecution records to confirm the job parameters and execution you intend to recover. Check job-level and step-level BatchStatus and ExitStatus before acting.
- Establish whether the old process is actually gone. Check the relevant process or host and logs. Do not assume that a stale-looking repository entry alone proves there is no work still in progress.
- Check restart safety. Confirm the job and steps are restartable and understand which completed steps will be skipped or run again. A step start limit may also prevent another start. The restart rules are described in the Spring Batch restart reference.
- Make an explicit recovery decision. Spring Batch documents recovery using JobOperator and warns that changing the execution state to FAILED or ABANDONED is an operator decision, not an automatic response to a crash. Verify that changing state is safe for the business process before doing so. See Advanced Metadata Usage.
- Restart only after reconciling side effects. Check which records, files, messages, or external systems the previous attempt may already have changed. Then restart through your supported operational procedure and monitor the resulting execution.
Do not blindly relaunch with identical parameters or manually change repository state just to clear STARTED. The appropriate recovery depends on whether the prior process is still active, what it completed, and whether repeating its work is safe.
Does Temporal automatically retry a failed workflow?
Not every kind of Temporal failure triggers the same behavior. A Workflow Task failure is a task-level failure: the service retries the task while the Workflow Execution remains open. A Workflow Execution failure is different: it closes that execution, and another run depends on a configured retry policy. Temporal describes this distinction in its Tasks documentation.
Rank #2
When investigating a Temporal failure, determine whether the recorded event is a Workflow Task failure or a Workflow Execution failure, and check the execution’s status and history. Seeing task failures does not by itself mean the business workflow has permanently failed; seeing a closed execution does not mean another run will begin unless the applicable policy calls for one.
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Choose based on the shape of the work and the recovery model your team needs—not on a universal claim that one framework is more reliable. Spring Batch’s job-and-step model suits batch-oriented processing where persisted execution metadata, step boundaries, and restart behavior are central. Temporal’s Workflow, Activity, and Worker model suits applications designed around workflow execution and history-based recovery. These are differences in programming and operations models, not a performance ranking.
- Favor Spring Batch when the work naturally divides into batch steps and the team needs to inspect and restart job or step executions through its batch metadata and operational procedures.
- Favor Temporal when the team wants to model a Java application as Workflows and Activities and operate on Workflow histories, task failures, and execution retry policies.
- Evaluate either carefully when steps perform non-transactional external side effects, retries may repeat work, or recovery requires coordinating application state with framework state. Define idempotency or reconciliation behavior for those operations.
There is no head-to-head throughput or reliability benchmark in the cited framework documentation, so it cannot establish that either choice is faster or more reliable for every workload. Validate the fit against the application’s transaction boundaries, checkpointing needs, retry granularity, operational skills, and deployment and versioning constraints.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to check before enabling retries
Retry should target errors that may resolve when attempted again, not serve as a blanket response to every exception. Decide which failures are transient, what retry limits and timeouts are appropriate, and how operators will detect repeated failures. Most importantly, make any external side effects safe to repeat or provide a way to reconcile them before retrying.
Rank #4
Version matters for Spring Batch retry examples. The cited Spring Batch 6.0 reference identifies version 6.0.5 and says framework retry uses the core retry feature from Spring Framework 7.0, not Spring Retry. Applications on Spring Batch 5.x or earlier may differ; check the exact dependency versions and the matching documentation before applying configuration examples. See Retry and Configuring Retry Logic.
Quick Recap
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Operational safeguards for either framework
- Record an execution or workflow identifier where operators can find it, alongside the relevant application logs.
- Alert on executions that remain active longer than expected, repeated failures, and work that has not made progress.
- Document who can make recovery decisions and how to verify side effects before retrying or restarting.
- Test crash and retry scenarios against the application’s actual persistence, transaction boundaries, and external integrations.
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