Open-source alternatives to Skizze

Netflix's distributed Data Pipeline

Secor is a service implementing Kafka log persistence

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

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

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

Hadoop Data Integration with various databases, ftp servers, salesforce. Incremental update, dedup, append, merge your data on Hadoop.

Build platforms that flexibly mix SQL, batch, and stream processing paradigms

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

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

KafkaT-ool

Kafka Manager is a web-based management interface and monitoring tool for Apache Kafka clusters. It serves as a central control plane for topic administration, consumer monitoring, and cluster health inspection. The project provides specialized utilities for data rebalancing and partition reassignment to distribute workloads across brokers. It also includes tools to optimize partition leadership by electing preferred replicas. The platform covers a broad range of administrative capabilities, including the creation and configuration of message topics, tracking of consumer offsets, and the col

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.

This project is an AWS pandas integration library and data pipeline framework designed to simplify the movement and transformation of data between local memory and AWS storage and analytics services. It functions as a cloud data lake toolkit and storage file manager, allowing users to read, write, and transform structured data across various cloud environments. The library distinguishes itself as a distributed compute orchestrator capable of managing clusters in environments such as EMR to process datasets that exceed the memory limits of a single machine. It also provides specialized capabil

Data ingestion engine — Singer taps to Parquet in cloud buckets

Kafkacat is a suite of command-line utilities for interacting with Apache Kafka clusters. It provides a non-JVM binary for producing and consuming messages, inspecting cluster metadata, and debugging the Kafka protocol via the terminal. The tool functions as a producer and consumer capable of pushing data from files or standard input and reading messages from specific topics and partitions. It includes a metadata inspector to retrieve cluster state and partition configurations in plain text or JSON, as well as a protocol debugger for inspecting message offsets, timestamps, and binary payloads

The Apache Kafka C/C++ library

Live import all your Google Sheets to your data warehouse

Kreuzberg is a document extraction engine that converts PDFs, Office files, images, and over 90 other formats into clean, structured text and metadata. It is built around a compiled Rust core that can be used as a native library, a command-line tool, a REST API server, or a WebAssembly module for browser-based processing. The system is designed to run entirely on self-hosted infrastructure, with no data leaving the user's environment. What distinguishes Kreuzberg is its breadth of integration surfaces and its pipeline architecture. It exposes extraction capabilities through native bindings fo

Kroxylicious, the snappy open source proxy for Apache Kafka®

Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs. The first merge library where every operation is mathematically guaranteed to converge.