Apache Spark
Privacy-first alternative
Why teams pick it
Keep customer data in-house with privacy-focused tooling.
Open-source alternatives to Amazon Managed Service for Apache Flink
Compare community-driven replacements for Amazon Managed Service for Apache Flink in stream processing engines workflows. We curate active, self-hostable options with transparent licensing so you can evaluate the right fit quickly.
Amazon Managed Service for Apache Flink
Run Flink applications without managing clusters; integrate with Kinesis, MSK, S3, and more to process streaming data at scale.Read more
Key stats
- 9Alternatives
- 8Active development
Recent commits in the last 6 months
- 6Permissive licenses
MIT, Apache, and similar licenses
Counts reflect projects currently indexed as alternatives to Amazon Managed Service for Apache Flink.
Start with these picks
These projects match the most common migration paths for teams replacing Amazon Managed Service for Apache Flink.
Redpanda Connect
Fastest to get started
Why teams pick it
Extensive source/sink catalog and native Docker/binary deployment
All open-source alternatives
Redpanda Connect
High-performance resilient stream processor with declarative pipelines
Active developmentFast to deployIntegration-friendlyGo
Why teams choose it
- Declarative pipelines defined in a single YAML file
- Built‑in Bloblang language for complex transformations
- At‑least‑once delivery without external state persistence
Watch for
Learning curve for Bloblang syntax
Migration highlight
Real‑time event enrichment from Pub/Sub to Redis Streams
Enriches incoming messages with computed fields using Bloblang and delivers them to Redis with at‑least‑once guarantees.
Apache Storm
Distributed real-time stream processing engine for low-latency analytics
Active developmentPermissive licenseIntegration-friendlyJava
Why teams choose it
- True real‑time processing with sub‑second latency
- Language‑agnostic multilang API for any programming language
- Fault‑tolerant topology execution with automatic retries
Watch for
Operational complexity requires Zookeeper and cluster management
Migration highlight
Real‑time fraud detection
Immediate identification and alerting of suspicious transactions
Apache Samza
Scalable, fault-tolerant stream processing with Kafka and YARN
Permissive licenseIntegration-friendlyAI-powered workflowsJava
Why teams choose it
- Simple callback‑based API comparable to MapReduce
- Managed state with automatic snapshotting and restoration
- Fault‑tolerant execution using YARN container migration
Watch for
Production deployments rely on YARN, limiting container‑native flexibility
Migration highlight
Real‑time fraud detection
Processes transaction events from Kafka, maintains per‑account state, and flags suspicious activity with exactly‑once guarantees.
Apache Spark
Fast, unified engine for large-scale data analytics
Active developmentPermissive licensePrivacy-firstScala
Why teams choose it
- Unified engine with batch and streaming support
- APIs for Scala, Java, Python, and (deprecated) R
- Built-in libraries: Spark SQL, MLlib, GraphX, Structured Streaming
Watch for
Heavy JVM memory footprint
Migration highlight
Nightly data warehouse ETL
Processes terabytes of raw logs into curated tables within minutes.
RisingWave
Real-time streaming platform with native Iceberg lakehouse support
Active developmentPermissive licenseIntegration-friendlyRust
Why teams choose it
- Sub‑100 ms end‑to‑end freshness with 10‑20 ms materialized view latency
- Native Apache Iceberg integration for continuous ingestion and table maintenance
- PostgreSQL‑compatible SQL and Python DataFrame APIs for familiar development
Watch for
Optimized for S3‑compatible object storage; other storage may need extra configuration
Migration highlight
Live financial dashboards
Deliver sub‑second price updates and analytics to traders, ensuring decisions are based on the freshest market data.
Materialize
Real-time SQL platform delivering up-to-the-second data views
Active developmentIntegration-friendlyAI-powered workflowsRust
Why teams choose it
- SQL‑native real‑time materialized views with strong consistency
- Incremental view maintenance across joins, aggregations, and JSON
- Multi‑source ingestion (Postgres, MySQL, Kafka, webhooks)
Watch for
Free community edition limited to 24 GiB memory and 48 GiB disk
Migration highlight
Real‑time operational dashboard
Dashboard queries return up‑to‑the‑second metrics without cache staleness.
Pathway
Unified Python framework for real‑time, batch, and LLM pipelines
Active developmentFast to deployIntegration-friendlyPython
Why teams choose it
- Pythonic API backed by a Rust differential dataflow engine
- Unified batch‑and‑stream processing with stateful transforms
- 300+ connectors via Airbyte plus native Kafka, PostgreSQL, GDrive, SharePoint
Watch for
Officially supports only macOS and Linux (Windows needs VM)
Migration highlight
Real‑time ETL from Kafka to PostgreSQL
Continuously ingest Kafka events, transform, and upsert into PostgreSQL with at‑least‑once guarantees.
Apache Flink
Unified engine for high-throughput, low-latency stream and batch processing
Active developmentPermissive licenseIntegration-friendlyJava
Why teams choose it
- Streaming-first runtime with unified batch support
- Exactly-once fault tolerance and natural back-pressure
- Rich APIs and libraries for graph, ML, and CEP
Watch for
Steep learning curve for advanced APIs
Migration highlight
Fraud detection in financial transactions
Detect anomalies within seconds using event-time windows and stateful processing.
Apache Beam
Unified model for batch and streaming data pipelines
Active developmentPermissive licenseIntegration-friendlyJava
Why teams choose it
- Unified programming model for batch and streaming
- Language‑specific SDKs (Java, Python, Go)
- Portable runners across multiple execution engines
Watch for
Steeper learning curve for new users
Migration highlight
Daily ETL from Cloud Storage to BigQuery
Transforms and loads daily CSV files using the DataflowRunner, ensuring reliable batch processing with automatic scaling.
Choosing a stream processing engines alternative
Teams replacing Amazon Managed Service for Apache Flink in stream processing engines workflows typically weigh self-hosting needs, integration coverage, and licensing obligations.
- 8 options are actively maintained with recent commits.
Tip: shortlist one hosted and one self-hosted option so stakeholders can compare trade-offs before migrating away from Amazon Managed Service for Apache Flink.