Research Library

Caringo Swarm – Product Analysis

Last updated September 10th, 2019 for Swarm 11. An unbiased 17-page deep dive into the architecture and performance of Caringo Swarm. Download the full Product Analysis now!

The Caringo Swarm system is a mature object storage system for private and public cloud usage and as a target archive system. Originally called CAStor, Swarm is delivered as software that is installed on Intel X86 servers with attached storage. The scale out architecture allows the configuration to dynamically scale very large in capacity and performance. Caringo has implemented a symmetric parallel architecture that operates to manage the nodes as a distributed cluster. Nodes are automatically discovered and rebalancing occurs after booting from a network. All executing software is maintained in RAM on each node to enhance performance.

The Caringo system includes SwarmNFS to provide file access to the underlying object storage using NFSv4. FileFly is used to migrate data to Swarm from Windows and Linux file servers and NetApp ONTAP systems over CIFS/SMB or NFS.

Direct object access is accomplished by use of the S3 API, and a superset of S3 called Simple Content Storage Protocol (SCSP), which conforms to HTTP1.1 and an HDFS connector. Geographic data distribution and protection is standard through sub-clusters on the same latency network. For remote clusters, Feeds (routing function) automates the routing of objects for data distribution and data protection. Feeds are latency tolerant and take advantage of the full cluster-to-cluster capability of the system.

Key competitors include IBM Cloud Object Storage, Scality Ring, Cloudian HyperStore, DDN WOS, Dell EMC Elastic Cloud Storage, and NetApp StorageGRID WebScale.

Caringo Swarm Product Analysis Includes: 

  • Highlights
  • Overview
  • Product Architecture
  • Software Architecture
  • Data Protection and Security
  • Advanced Features
  • File Access
  • Reliability, Availability, Serviceability Features
  • Performance
  • Evaluator Group Comments

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