Open-Source Databases · hyrise

hyrise

Hyrise is an open-source, in-memory columnar database system developed at HPI for research purposes. It supports comprehensive SQL, standard benchmarks (TPC-H, TPC-DS), and runs on Linux and macOS. It is not a production-ready database but rather a research platform for experimenting with data management concepts.

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Source: GitHub — github.com/hyrise/hyrise

869

GitHub stars

173

Forks

C++

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	hyrise/hyrise
Owner	hyrise
Primary language	C++
License	MIT — OSI-approved
Stars	869
Forks	173
Open issues	89
Latest release	Unknown
Last updated	2026-07-07
Source	https://github.com/hyrise/hyrise

What hyrise is

C++ columnar in-memory database with query optimization, supporting TPC-H, TPC-DS, Join Order, and Star Schema benchmarks. Features column-store architecture, comprehensive SQL support, and extensible design for research. Development is active but unmarked for production use.

Quickstart

Get the hyrise source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/hyrise/hyrise.git2cd hyrise3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Academic Research & Database Systems Study

Ideal for researchers and students investigating in-memory database optimization, query planning, and column-store architectures. The clean, flexible architecture enables experimentation with new data management concepts.

Query Optimization Prototyping

Suitable for testing novel query optimization strategies and validating performance improvements before deploying to production systems. Built-in benchmark harnesses (TPC-H, TPC-DS) enable quick performance measurement.

Educational Projects in Database Engineering

Well-suited for university courses and workshops on database internals, columnar storage, and SQL execution. Documented with step-by-step guides and contributor guidelines for learners.

Implementation considerations

Requires recent versions of clang or gcc (C++17 or later); older compiler versions not tested or supported.
Linux (Ubuntu 22.04+) is the primary target; macOS is supported for development but not for benchmarking. Plan for Linux-only production testing.
Out-of-source builds recommended; use CMake with optional relaxed build flags if encountering strict compiler warnings on unsupported systems.
Submodules required; use provided install_dependencies.sh script or Nix for reproducible dependency setup.
No official Docker image published; Dockerfile provided but requires manual checkout and dependency installation inside container.

When to avoid it — and what to weigh

Production OLTP or OLAP Workloads — Not intended for production deployments. No release versioning, no stability guarantees, and TPC-C optimization explicitly noted as 'in development with no proper optimization done yet'.
Requirement for Commercial Support or SLAs — Academic research project from HPI; no commercial support, service level agreements, or enterprise maintenance channels available.
Cross-Platform or Windows Deployment — Officially supports Linux (Ubuntu) and macOS for development only. macOS not recommended for benchmarking. No Windows support mentioned.
Mission-Critical Data Consistency — Research platform without published security audits, ACID guarantees, or production-grade failover mechanisms. Not suitable where data integrity is legally mandated.

License & commercial use

MIT License (https://opensource.org/licenses/MIT). Permissive OSI-approved license allowing use, modification, and distribution with minimal restrictions; requires attribution and includes no warranty.

MIT License permits commercial use in principle, but this is a research project without commercial backing, support contracts, or guarantees of fitness for any purpose. Any commercial deployment assumes full responsibility for maintenance, security patching, and operational risk. Requires legal review before use in commercial settings.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	High
DEV.co fit	Possible
Assessment confidence	High

Security considerations

No security audit, penetration testing results, or known vulnerability disclosure process documented. As a research codebase without production hardening, assume standard open-source security practices only: code review via GitHub, no formal security SLAs. Strict compiler flags enabled by default suggest attention to memory safety, but no ASLR, exploit mitigation, or access control mechanisms documented. Not suitable for systems handling sensitive data without additional hardening.

Alternatives to consider

PostgreSQL (with cstore_fdw or pg_partman)

Production-grade open-source database with extensive SQL support, ACID guarantees, and operational maturity. Columnar extensions available via plugins. Suitable where stability and community support are required.

Apache Druid

Open-source distributed in-memory analytics database designed for real-time OLAP workloads. Includes operational tooling, cluster management, and enterprise integrations. Better fit for production analytics than Hyrise.

DuckDB

Lightweight in-memory SQL database optimized for analytical queries, simpler to integrate than Hyrise, and actively maintained for practical use cases. Growing adoption in data science and BI tools.

Software development agency

Build on hyrise with DEV.co software developers

Hyrise is ideal for exploring database optimization and query planning in a controlled research environment. For production analytics, consider alternatives like DuckDB or PostgreSQL. Contact our team to discuss your use case and integration requirements.

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hyrise FAQ

Can I use Hyrise in production?

No. Hyrise is explicitly a research platform with no release versioning, no stability guarantees, and no commercial support. Production use is not recommended and assumes full operational responsibility.

Does Hyrise support Windows?

No. Hyrise is developed for Linux (Ubuntu recommended) with macOS support for development only. Windows is not officially supported.

What query languages does Hyrise support?

Comprehensive SQL support is documented, but specific dialect compatibility (e.g., PostgreSQL vs. MySQL syntax) and edge cases are not detailed. Testing is recommended before relying on specific SQL features.

How do I get support if I find a bug?

File an issue on GitHub. As a research project, response time and resolution are not guaranteed. Community contributions via pull requests are encouraged per CONTRIBUTING guidelines.

Work with a software development agency

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If hyrise is part of your open-source databases roadmap, our team can implement, customize, migrate, and maintain it.

Evaluate Hyrise for Your Research or Proof-of-Concept

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