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Last updated 2017-08-09

Voldemort

Learn about Voldemort database

Voldemort is a distributed key-value storage system

  • Data is automatically replicated over multiple servers.
  • Data is automatically partitioned so each server contains only a subset of the total data
  • Provides tunable consistency (strict quorum or eventual consistency)
  • Server failure is handled transparently
  • Pluggable Storage Engines -- BDB-JE, MySQL, Read-Only
  • Pluggable serialization -- Protocol Buffers, Thrift, Avro and Java Serialization
  • Data items are versioned to maximize data integrity in failure scenarios without compromising availability of the system
  • Each node is independent of other nodes with no central point of failure or coordination
  • Good single node performance: you can expect 10-20k operations per second depending on the machines, the network, the disk system, and the data replication factor
  • Support for pluggable data placement strategies to support things like distribution across data centers that are geographically far apart.

It is used at LinkedIn by numerous critical services powering a large portion of the site.

Voldemort is a distributed data store that is designed as a key-value store used by LinkedIn for high-scalability storage. It is named after the fictional Harry Potter villain Lord Voldemort.

It is neither an object database, nor a relational database. It does not try to satisfy arbitrary relations and the ACID properties, but rather is a big, distributed, fault-tolerant, persistent hash table.A 2012 study comparing systems for storing application performance management monitoring data reported that Voldemort, Cassandra, and HBase offered linear scalability in most cases, with Voldemort having the lowest latency and Cassandra having the highest throughput.

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