One platform for data, AI, and business-critical workflows.
Kestra has streamlined our data processes, reduced costs, and significantly enhanced our scalability and efficiency. It has truly been a critical asset in our digital transformation journey.
Reported by teams switching from Airflow to Kestra in production.*
Self-hosted Kestra runs on minimal infrastructure. No overprovisioned workers or complex component scaling. Deploy on your existing Kubernetes cluster or a single VM.
Eliminate weeks of operational overhead. No upgrades breaking plugins, no dependency conflicts, no executor tuning. Ship pipelines, not infrastructure.
Many orchestrators lock enterprise features behind expensive managed plans. Kestra delivers them in open source or flexible commercial licensing.
Kestra Copilot turns natural language into working pipelines using dbt, Airbyte, Spark, Snowflake, BigQuery, Databricks, and2,600+ plugins.
Pick from our production-ready Blueprints for common data workflows. Copy, customize, deploy in minutes.
Audits Microsoft Access databases for transaction ledger mismatches, unposted backlogs, and automates audit hold remediation.
Audit MySQL accounts for anonymous users, empty passwords, remote root, global admin privileges and wildcard hosts, alert Slack, and optionally drop, lock or revoke and verify, never touching the connected account.
Compute the binary log purge boundary from every replica's own read position and the last backup, alert Slack, then purge behind an approval with a re-check that fails if a needed log went missing.
Find a MySQL server whose binlog_row_image is no longer FULL and restore it after approval, proved with a real Debezium capture.
Restore an expected-OFF MySQL runtime general query log policy after a grace period and approval then prove instrumented file writes stop.
Export changed MySQL rows to date-partitioned Parquet in MinIO. Move the KV watermark only after the object is read back and verified.
Monitor MySQL for long-running uncommitted transactions holding row locks, alerting DBAs on Slack to prevent lock wait timeouts.
Proactively detect long-running uncommitted MySQL transactions and row lock contention before thread pool exhaustion occurs.
Find MySQL tables without a primary key and non-InnoDB tables, alert Slack, and optionally promote a unique NOT NULL key or add an invisible id column, then verify.
Dry-run the ALTER, copy the table with gh-ost while throttling on replica lag, verify the ghost table, and swap the tables only after a person approves. Declines and failures clean up after themselves.
Find MySQL XA branches stuck in the prepared state after a coordinator crash, age-gate them so a real in-flight commit is never touched, roll back only the orphans behind a dry-run and approval gate, then re-read XA RECOVER and fail if any targeted branch is still prepared.
Catch a MySQL server left running with InnoDB redo logging disabled after a bulk load, turn it back on behind a dry-run and approval gate, then re-read the Innodb_redo_log_enabled status variable and fail the run if crash recovery is still off.
Monitor MySQL replica Seconds_Behind_Master and IO/SQL thread statuses via SHOW REPLICA STATUS, alerting DBAs before stale read drift.
Find a MySQL replica that accepts client writes because super_read_only is OFF, set it ON behind a dry-run and approval gate, then re-read both variables and fail if the replica is still writable. An instance with no replication configured is never touched.
Continuously monitor MySQL read replica replication status, IO/SQL thread health, and alert Slack on SLA lag breaches.
Compare a bounded table's exact count with persistent InnoDB statistics then approve a locked local ANALYZE and verify its estimate.
Detect a stopped MySQL read replica thread from SHOW REPLICA STATUS, tell a transient stop apart from a data-error stop, restart only the transient case behind a dry-run and approval gate, then re-read status and fail if the threads did not resume.
Audits InnoDB data_free space across MySQL tables and recommends storage defragmentation.
Audit MySQL in-memory temporary table disk spills via performance_schema, export CSV diagnostic reports, and alert on sort buffer saturation.
Compare MySQL and PostgreSQL table row counts in DuckDB and advance PostgreSQL sequence counters to prevent cutover duplicate key collisions.
Audits Microsoft Access databases for transaction ledger mismatches, unposted backlogs, and automates audit hold remediation.
Audit MySQL accounts for anonymous users, empty passwords, remote root, global admin privileges and wildcard hosts, alert Slack, and optionally drop, lock or revoke and verify, never touching the connected account.
Compute the binary log purge boundary from every replica's own read position and the last backup, alert Slack, then purge behind an approval with a re-check that fails if a needed log went missing.
Find a MySQL server whose binlog_row_image is no longer FULL and restore it after approval, proved with a real Debezium capture.
Restore an expected-OFF MySQL runtime general query log policy after a grace period and approval then prove instrumented file writes stop.
Export changed MySQL rows to date-partitioned Parquet in MinIO. Move the KV watermark only after the object is read back and verified.
Fivetran
Snowflake
Databricks
Azure
DBT
Airbyte
MongoDB
Cassandra
PostgreSQL
MySQL
Redshift
BigQuery
ClickHouse
Redis
Elasticsearch
Kafka
Pulsar
RabbitMQ
Fivetran
Snowflake
Databricks
Azure
DBT
Airbyte
MongoDB
Cassandra
PostgreSQL
MySQL
Redshift
BigQuery
ClickHouse
Redis
Elasticsearch
Kafka
Pulsar
RabbitMQ
| Legacy orchestrators (e.g. Airflow) | Modern alternatives | Why this matters | ||
|---|---|---|---|---|
| Workflow definition | Declarative YAML | Python DAGs | Python SDKs with custom abstractions | Your existing scripts work as-is. Zero migration tax. |
| Languages supported | Any (Python, SQL, R, Bash, etc.) | Python only | Python only | Analysts use SQL, engineers use Python, ops use Bash. |
| Time to first pipeline | < 5 minutes | 1-2 hours | 30-60 minutes | Ship 10x faster. Deliver value day one. |
| Learning curve | YAML (immediate) | Framework + infrastructure setup | Framework concepts and abstractions | Junior engineers ship pipelines their first day. |
| Live DAG preview | Yes, real-time | No (deploy to see) | No (deploy to see) | See changes instantly. No deploy-to-preview cycles. |
| Event-driven triggers | Native, unlimited | Limited sensors (polling-based) | Yes, native support | React in seconds, not minutes, with real-time workflows. |
| Execution isolation | Containers per task | Shared workers | Configurable | No dependency conflicts. Ship fearlessly. |
| Built-in observability | Metrics, logs, tracing included | Requires manual setup | Setup required or cloud-dependent | Debug in minutes with full visibility out of the box. |
| Multi-language team support | SQL, Python, Bash all native | Python wrappers required | Python wrappers required | Everyone contributes using their native tools. |
| Scope beyond data | AI, infra, business workflows | Data pipelines only | Data pipelines primary focus | Future-proof your platform with one orchestrator for everything. |
| Enterprise deployment | Self-hosted or cloud | Self-managed infrastructure | Self-hosted or cloud-first | 50%+ lower TCO. Less infrastructure, less ops time. |
| Migration path | Incremental (run Airflow + Kestra in parallel) | N/A | Requires full rewrite | Move pipelines one by one, no big-bang cutover. |
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