Important

ChronoLog v3.0.0 is now available. The latest stable release, focused on API completeness and native extension plugins. Releases on chronolog.dev · Release notes · All releases on GitHub · Documentation

ChronoLog

Distributed Shared Tiered Log Store

A distributed and tiered shared log storage ecosystem that uses physical time to distribute log entries while providing total log ordering.

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Overview

ChronoLog is a distributed, tiered shared log store with time-based event ordering. It uses physical time for data distribution and multiple storage tiers for elastic capacity, eliminating the need for a central sequencer while keeping ingestion and query paths independently scalable.

A pluggable serving layer lets custom services run directly on the log. Shipping plugins cover SQL-like queries, key-value storage, streaming, pub/sub, Grafana visualization, and an MCP server for LLM integration.

Key Features

• No central sequencer: physical-time partitioning enables high-throughput parallel writes.
• Tiered storage: StoryChunks flow across fast and capacity tiers automatically.
• Concurrent access at scale: multi-writer, multi-reader over RDMA or TCP.
• Pluggable serving layer: extend the log with custom query and streaming services.

For more, visit chronolog.dev.

Installation

ChronoLog ships in five flavors. Pick the one that matches your environment. The full step-by-step guide for every method (including configuration, single-node and multi-node deployment) lives in the Quick Start guide on chronolog.dev.

Release archive (tarball): pre-built binaries, no toolchain required

Best for trying ChronoLog quickly on a Linux x86_64 host.

Download the tarball:

wget https://github.com/grc-iit/ChronoLog/releases/latest/download/chronolog-linux-x86_64.tar.gz

Extract it:

tar -xzf chronolog-linux-x86_64.tar.gz

Full guide → Quick Start: Release Archive

DEB package: Debian / Ubuntu

System-wide install via apt for Debian, Ubuntu, and compatible distributions.

sudo apt install ./chronolog-linux-x86_64.deb

Full guide → Quick Start: DEB Package

RPM package: RHEL / Fedora / Rocky / Alma

System-wide install via dnf (or yum) for RHEL-family distributions.

sudo dnf install ./chronolog-linux-x86_64.rpm

Full guide → Quick Start: RPM Package

Docker: containerized, single- or multi-node

Containerized deployment with ChronoLog pre-installed.

Pull the image:

docker pull ghcr.io/grc-iit/chronolog:latest

Run a container:

docker run -it --rm ghcr.io/grc-iit/chronolog:latest bash

Full guide → Quick Start: Docker · Single-node tutorial · Multi-node tutorial

Build from source: for developers and advanced users

For modifying ChronoLog, building against a custom dependency set, or targeting a platform without pre-built packages.

Clone the repository:

git clone https://github.com/grc-iit/ChronoLog.git

Enter the repo:

cd ChronoLog

Activate the Spack environment and install dependencies:

spack env activate -p .

spack install -v

Configure, build, and install:

mkdir build && cd build

cmake -DCMAKE_BUILD_TYPE=Release ..

make all

make install

Full guide → Quick Start: Build from Source

Documentation

Full documentation lives at chronolog.dev/docs:

• Getting Started: overview, core concepts, and Quick Start install paths.
• User Guide: architecture, configuration, deployment, and the data model.
• Tutorials: step-by-step walkthroughs for single- and multi-node Docker deployments.
• Contributing: build-for-development setup, code style, and contributor guidelines.

Research Network

ChronoLog evolves alongside a network of labs and institutions whose research shapes the kinds of workloads and infrastructure our system is designed to support. Argonne National Laboratory and Lawrence Livermore National Laboratory advance exascale computing, HPC system software, resource management, and large-scale telemetry. The University of Chicago leads research on distributed systems and large-scale scientific workflows for cosmology and the physical sciences. The SCI Institute at the University of Utah drives scientific visualization, in-situ analysis, and large-scale data exploration for simulation and instrument science. Ohio State University is a leader in high-performance networking, MPI, and RDMA-based communication. DePaul University works on data systems, lightweight indexing, and computational provenance. The Institute for Food Safety and Health (IFSH) applies high-throughput data analysis, genomics, and bioinformatics to food safety and public-health challenges.

                 

Interested in integrating ChronoLog into your research or systems? We welcome conversations with labs, research groups, and engineering teams working on scalable event processing, large-scale telemetry, time-ordered storage, and related problems. Reach out via GitHub Issues or contact the Gnosis Research Center.

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Gnosis Research Center
Illinois Institute of Technology
Advancing the Future of Scalable Computing and Data-Driven Discovery

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Sponsored by:

National Science Foundation (NSF CSSI-2104013)