30 open-source projects similar to netflix/suro, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Suro alternative.
ingestr is a command-line tool for copying and syncing data between different database engines and third-party platforms without writing custom code. It functions as an ETL pipeline utility that extracts data from diverse sources and loads it into destinations. The tool features a schema-agnostic data loader that maps source fields to destination columns dynamically, removing the need for predefined static table definitions. It also operates as an incremental data synchronizer, updating destination tables by appending new records or merging changes to maintain current datasets. The system pr
A distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
Rudder Server is a customer data platform and event routing pipeline designed to collect, transform, and route customer event data from various sources to data warehouses and business tools. It functions as a customer identity resolver, linking identifiers from multiple sources to build a unified identity graph and comprehensive behavioral customer profiles. The system differentiates itself through reverse ETL capabilities, which push processed customer segments and audiences from data warehouses back into operational third-party applications. It also provides a containerized data plane for K
Build platforms that flexibly mix SQL, batch, and stream processing paradigms
Secor is a service implementing Kafka log persistence
🦎 A multi-protocol edge & service proxy. Seamlessly interface web apps, IoT clients, & microservices to Apache Kafka® via declaratively defined, stateless APIs.
Apache Pulsar is a cloud-native distributed pub-sub messaging system designed for high-performance data ingestion. It functions as a geo-replicated data streamer and a multi-tenant event streaming platform, providing a serverless stream processing engine and a tiered storage messaging broker. The system distinguishes itself by separating serving layers from storage layers to allow independent scaling of compute and data retention. It features native geo-replication to synchronize messages across different geographical regions and employs a multi-layered tenant isolation model using authentica
DEPRECATED: Data collection and processing made easy.
Scribe is a distributed log aggregation system designed to collect and route real-time log data from numerous servers to centralized storage or analysis tools. It functions as a log data pipeline and scalable collector that gathers streaming data and writes it to local disks or remote endpoints. The system employs a log routing server model that organizes incoming streams into specific buckets based on predefined configuration mappings. It supports multi-hop log forwarding, allowing data to be routed through a chain of intermediate servers to centralize logs from diverse network segments. Re
Hadoop Data Integration with various databases, ftp servers, salesforce. Incremental update, dedup, append, merge your data on Hadoop.
Benthos is a stream processing engine and data integration pipeline used for routing, transforming, and connecting data streams between diverse sources and sinks. It functions as event routing middleware and a change data capture tool, streaming real-time database modifications as discrete events for downstream processing. The system utilizes a declarative pipeline configuration, where data flow and processing logic are defined in a single static file. It features a specialized domain-specific language for mapping, filtering, and enriching data payloads, allowing for complex transformations w
Iggy is a distributed message streaming platform and multi-protocol message broker that functions as a persistent distributed log store. It provides infrastructure for publishing and consuming binary messages using an append-only log, ensuring high availability and data consistency across nodes through Viewstamped Replication. The platform is distinguished by its specialized LLM streaming infrastructure, which uses a server protocol to connect large language models to streaming data and system controls. This includes standardized protocols for context management and data bridging via HTTP or
Azure Docs is the official technical documentation repository for Microsoft Azure, the cloud computing platform. It provides comprehensive guidance on the full spectrum of Azure services, covering everything from core infrastructure components like virtual machines, Kubernetes clusters, and serverless computing to platform services for AI, machine learning, data analytics, and storage. The documentation details how to provision, manage, and govern cloud resources at scale, including policy enforcement, identity management, and cost optimization. The documentation distinguishes Azure through i
This project is a suite of software for radio interferometry imaging, specialized in the processing, analysis, and reconstruction of Very Long Baseline Interferometry (VLBI) observations. It provides tools for reconstructing images from interferometry data using regularized maximum likelihood methods and managing the end-to-end data processing pipeline from raw visibilities to final images. The software distinguishes itself with a dedicated interstellar scattering simulator that models thin-screen scattering effects and applies scattering kernels to radio images. It also features a radio imag
Kafka is a distributed event streaming platform designed for capturing, storing, and processing real-time data streams across interconnected nodes. It functions as a distributed commit log, providing a fault-tolerant storage mechanism that records state changes sequentially to ensure data consistency and durability across distributed environments. The platform distinguishes itself through a partitioned commit log architecture that enables horizontal scaling and parallel processing of data streams. It integrates a stream processing engine for continuous transformations and aggregations, while
Apache Pulsar is a cloud-native message queue and distributed publish-subscribe messaging system. It serves as a multi-tenant event streaming platform designed to route data streams for asynchronous communication between producers and consumers. The system distinguishes itself through geo-replication, synchronizing data across multiple geographic regions to ensure high availability and low latency. It implements a multi-tenant architecture that provides isolation and resource management for millions of independent topics. The platform covers high-throughput data streaming and event-driven da
A distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.
Celery is an asynchronous job processor and distributed task queue designed to offload time-consuming operations to background worker nodes. By utilizing a message-passing architecture, it decouples task producers from consumers, allowing applications to maintain responsiveness while scaling workloads across multiple isolated environments. The system functions as a distributed workload orchestrator that manages the lifecycle of deferred operations through persistent queues. It distinguishes itself by providing a pluggable transport abstraction, which allows the core task logic to remain indep
Python task queue using Redis
Cocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core focus on codebase indexing and knowledge graph extraction. The engine uses a function-graph execution model where user-defined Python functions are composed into a directed acyclic graph, and it processes data incrementally so only changed source records or code paths are re-computed, avoiding full recomputation at any scale. It supports automatic schema inference from transformation pipeline type annotations and provides full data lineage tracing, tagging every output record wi
Stream summarizer and cardinality estimator.