Flower® orchestrates data movement and processing across storage systems and databases: validate, filter, aggregate, transform and deliver. Build declarative flows with recovery, protection and operational visibility integrated, from edge to cloud.
Connect systems, orchestrate execution, process data in motion and govern delivery. Flower brings these capabilities together through declarative flows, with operating policies built into the platform.
01
Connect & orchestrate
Storage, files & databases
Move data between clouds, private networks and database endpoints, using the systems you already operate.
Scheduling & orchestration
Define schedules, file selection and concurrency. Coordinate execution through shared operating policies.
Batch & streaming processing
Process byte streams and records as data moves, and run recurring deliveries with configured resource limits.
Credentials & secret stores
Load secrets and certificates from supported cloud vaults, enterprise stores or local sources to fit your access model.
02
Process & protect
Filtering & aggregation
Select useful records, remove duplicates, group and aggregate data before it reaches downstream platforms.
Transformation & formats
Map fields, convert types and transcode formats such as CSV, JSON, Avro and Parquet within the data flow.
Validation & data quality
Check structure, values and business rules. Route invalid input according to the configured rejection or quarantine policy.
Encryption & compression
Encrypt, decrypt, compress and decompress streams within the processing chain, with configured keys and formats.
03
Verify & govern
Self-healing & retries
Recover from transient failures with bounded retries and backoff for safe operations. Escalate when policy limits are reached.
Integrity & reconciliation
Reconcile source and destination state and verify completion on supported copy paths. Define acceptance checks for transformed output.
Lineage & lifecycle
Track execution and data movement. Apply explicit policies for archiving, retention, cleanup and quarantine.
Proactive alerts & visibility
Use events, logs, metrics and configured alerts to identify failures and give operators the context needed to act.
Declarative flows
Define the outcome. Put the operating logic to work.
Build flows without programming: declare endpoints, data rules and operating policies in a compact, readable configuration. Scheduling, processing, recovery and monitoring work together within Flower.
Set endpoints, credentials, paths and the data to select.
02
Compose the processing rules
Combine validation, filtering, aggregation, transformation and protection using built-in steps.
03
Set the operating policy
Choose schedules, safe retry limits, quarantine, retention and alerts. Flower executes the configured flow.
Recovery in action
Keep the flow moving. Bring exceptions into focus.
Flower applies bounded retries to operations that are safe to repeat, isolates invalid input and reports exceptions requiring attention. Explore those decisions on one illustrative route: compressed CSV from Amazon S3, processed into Parquet and delivered to Azure Blob.
Explore the recovery policyorders-001.csv.gz
01SourceAmazon S3CSV · gzip
02{ }Validate, filter, aggregate and transformFlowerCSV → Parquet
03DestinationAzure BlobParquet
✓ Delivered
The sample passes validation and is converted to Parquet. The illustration shows the completed delivery path; actual acceptance checks depend on the configured endpoint and transformation.
↻ Waiting to retry
A temporary destination failure pauses delivery. Retry-safe work follows bounded attempts and backoff. Restore the destination to explore recovery; exhausted policies require operator attention.
! Quarantined
The sample contains an invalid record. This scenario quarantines the entire source file and blocks downstream delivery. Retrying unchanged data would not fix the validation failure.
✓ Recovered within the retry policy
The destination is available again and the retry-safe operation completes. Source cleanup remains a separate configured decision. This is an illustrative sequence, not a measured recovery time.
A native Go runtime, deployable as a single executable, brings the same declarative approach to embedded devices, private servers and cloud infrastructure. Place processing near the source and tune concurrency and buffers to the workload.
01
Edge & embedded
Select, validate and prepare data close to its origin. Reduce unnecessary transfers before data leaves the device or site.
02
On-premises & private networks
Connect internal files, databases and business systems. Keep execution and access to data within your infrastructure boundaries.
03
Cloud & hybrid platforms
Run flows alongside cloud storage and analytical services. Size workers and resources to the workload while keeping the same operating model.
Flower combines data processing and the controls that keep it running in production. The advantage is practical: fewer pieces to assemble, less routine recovery work and more control over resources and execution.
✓
Operating logic already integrated
Configure recovery, validation, quarantine and lifecycle alongside the data flow. Reuse these controls across routes and environments.
✓
Process useful data, closer to the source
Filtering, aggregation and compression can reduce the bytes sent downstream, along with bandwidth, storage and central processing requirements.
✓
Execution under your control
Choose where the runtime operates and how it reaches your systems, with no mandatory vendor-hosted control plane.
Connect cloud storage, file systems, enterprise databases and analytical platforms within the same flow. Explore the catalog for supported operations and authentication options.
Also connect enterprise secret stores and extend selected processing steps with JavaScript, Lua, WebAssembly, Starlark or AWK when your workload needs custom logic. The full catalog details the supported operations for each integration.
Experience is the starting point. Evidence closes the decision.
Flower has operated continuously since 2019 on high-volume telecommunications flows and business-critical financial data. Evaluate your own workload with an agreed correctness, recovery and resource test plan.
Flower Consulting Srl develops Flower and helps organizations assess, integrate and operate it. Agree on the workload, acceptance criteria, handover and support scope before production.
SourceAmazon S3
DestinationAzure Blob
