Amazon Redshift
Fully managed, petabyte-scale cloud data warehouse for analytics and reporting
YTsaurus
Scalable, fault-tolerant platform for big-data storage and processing
YTsaurus delivers a multitenant, distributed storage and compute engine with MapReduce, SQL, and NoSQL capabilities, supporting exabyte-scale data, millions of cores, and seamless scaling.
Overview
Overview
YTsaurus is a distributed storage and processing platform designed for organizations that need to handle petabyte‑to‑exabyte data volumes across many users. It combines a MapReduce engine, an SQL query layer powered by ClickHouse (CHYT), a job scheduler, and a key‑value store for OLTP workloads, all within a single multitenant ecosystem.
Core Capabilities
The system offers fault‑tolerant operation with automated replication and zero‑downtime updates, while scaling to millions of CPU cores, thousands of GPUs, and tens of thousands of nodes. Data can reside on HDD, SSD, NVMe, or RAM, and the platform supports ACID transactions, a rich set of SDKs/APIs, and secure isolation of compute and storage resources. Integrated SPYT brings Apache Spark‑compatible tools for ETL, and the web UI simplifies cluster monitoring and job management.
Deployment Options
YTsaurus can be launched locally via source builds or quickly provisioned on Kubernetes using the provided Helm chart. An online demo is also available for hands‑on evaluation. The Apache‑2.0 license permits unrestricted use and contribution, making it suitable for both on‑premises data centers and cloud environments.
Highlights
Multitenant ecosystem with MapReduce, SQL, job scheduler, and key‑value store
Fault‑tolerant architecture with automated replication and zero‑downtime updates
Massive scalability to millions of CPU cores, exabytes of data, and tens of thousands of nodes
Integrated analytics via ClickHouse‑compatible CHYT and Spark‑compatible SPYT
Pros
- High scalability for extreme data volumes
- Robust fault tolerance and no single point of failure
- Rich set of processing models (MapReduce, SQL, OLTP, Spark)
- Compatibility with familiar ClickHouse and Spark ecosystems
Considerations
- Complex deployment may require Kubernetes expertise
- Resource‑intensive at large scale
- Steep learning curve due to many subsystems
- Primary codebase in C++ may limit contributions from non‑C++ developers
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Fit guide
Great for
- Enterprises needing a unified big‑data platform across teams
- Data scientists requiring both OLAP and OLTP workloads
- Organizations with large‑scale hardware resources
- Teams leveraging ClickHouse or Spark tools
Not ideal when
- Small teams with limited infrastructure
- Projects needing a lightweight embedded database
- Users seeking a fully managed SaaS solution
- Workloads that cannot tolerate operational complexity of a distributed system
How teams use it
Real‑time clickstream analytics
Process billions of events per day with low latency using MapReduce and CHYT for instant dashboards.
Large‑scale ETL pipelines
Leverage SPYT to orchestrate Spark jobs that transform and load petabytes of data into the lake.
Multi‑tenant data lake for business units
Provide isolated storage and compute environments for different departments while sharing underlying hardware.
High‑frequency trading data storage
Store tick‑level data with ACID guarantees and query it efficiently via the ClickHouse‑compatible SQL layer.
Tech snapshot
C++51%
C26%
Python15%
Go4%
Assembly2%
Cython1%
Frequently asked questions
Which programming languages have SDKs or APIs?
YTsaurus offers SDKs and APIs for C++, Python, Java, Go, and additional languages through REST and gRPC interfaces.
How does YTsaurus avoid a single point of failure?
The platform uses automated data replication across nodes and a distributed architecture that continues operating despite individual server failures.
Can YTsaurus be run on Kubernetes?
Yes, a Helm chart and quick‑start guide enable deployment of YTsaurus clusters on Kubernetes.
What SQL engine does YTsaurus use?
The CHYT layer is powered by ClickHouse, providing a familiar ClickHouse SQL dialect for fast analytic queries.
Is there a graphical interface for managing the cluster?
YTsaurus includes a web‑based UI for monitoring nodes, managing jobs, and interacting with stored data.
Project at a glance
Active- Stars
- 2,118
- Watchers
- 2,118
- Forks
- 188
LicenseApache-2.0
Repo age3 years old
Last commit4 hours ago
Primary languageC++
Last synced 4 hours ago