About
Dnaerys is a distributed in-memory low latency genome variant store - a specialized database to store genetic variations and execute algorithms from the field of genetics.
Dnaerys provides real-time response on datasets with hundreds of thousands of WGS samples.
It runs on infrastructure from laptops to enterprise and cloud, providing the fastest distributed variant store solution on the planet.
It is designed to run on Kubernetes clusters, but it's simple to start work with on your local laptop.
Qualities
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distributed: it's a homogeneous distributed database management system. It has identical software running on all database nodes and appear through a single interface as if it were a single database. All nodes have equal roles and any node can be used for querying.
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in-memory: each node keeps all its data in RAM
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horizontally scalable: query latency stays within the same constrains while data volume & number of nodes are growing
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provides best in class performance
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designed for resilience
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no single point of failure: every node in the cluster has the same role and can service any request. At the same time, data is partitioned across all nodes.
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graceful degradation: in an event of node(s) failure(s), cluster continues to serve requests with the data available on remaining nodes, with respsonses marked as potentially incomplete
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φ accrual failure detector for detecting unreachable nodes. Flexible and configurable to adapt to a variety of environments (with wide range of n/w latencies between nodes and their deviations) and requirements (how fast recovery needs to happen).
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push-pull gossip protocol for cluster state awareness
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network partition tolerant
- sub-clusters continue to serve their respective clients
- split-brain resolver is an option
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data corruption detection: all data pass through several layers of validation and integrity checks, including non cryptographic hashes
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designed for cloud scale
- runs on infrastructure from laptops to enterprise and cloud
- Kubernetes is the reference deployment platform
- designed with a focus on Observability and Ops
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available with free Community license