Tag Archives: hypertable.com

10 Key/Value Store, Distributed, Open Source Databases

Riak

  • HTTP API
  • Master-less, so remains operational even if multiple nodes fail
  • Near linear scalability
  • Architecture same of both large and small clusters
  • Key/value model, flat namespace, can store anything

Redis

  • Key/value. Can store data types such as sets, sorted lists, hashes and do operations on them such as set intersection and incrementing the value in a hash.
  • In-memory dataset
  • Easy to setup, master/slave replication

Hibari

  • Very simple data model with 5 attributes: keys, values, timestamps, expiry date, flags for metadata
  • Chain replication across nodes that are geographically dispersed. Not single points of failure
  • Excellent performance for large batches (~200k) read/write operations
  • Runs on commodity hardware or blades. Does not require SAN

Hypertable

  • High performance, massively scalable, modeled after Google’s Bigtable
  • Runs on top of a distributed file system such as Apache Hadoop DFS, GlusterDS, or Kosmos File System
  • Data model is a traditional, but huge table, that is physically stored in sort order of the primary key

Voldemort

  • High scalability due to allowing only very simple key/value data access.
  • Used by LinkedIn
  • Not an object or a relational database. Just a big, distributed, fault-tolerant, persistent hash table
  • Includes in-memory caching, so separate caching tier isn’t required

MemcacheDB

  • High performance persistent storage that’s compatible with Memcache protocol

Tarantool

  • NoSQL database with messaging server
  • All data maintained in RAM. Persistence via a write ahead log.
  • Asynchronous replication and hot standby
  • Supports stored procedures
  • Data model: tuples (unique key plus any number of other fields); spaces (multiple tuples)

Apache Cassandra

  • Can use massive cluster of commodity servers with no single point of failure. Can be deploy across multiple data centers.
  • Was used by Facebook for Inbox Search until 2010
  • Read/write scales linearly with number of nodes
  • Data replicated across multiple nodes
  • Supports MapReduce, Pig, and Hive
  • Has SQL-like CQL providing for a hybrid between key/value and tabular database

HyperDex

  • NoSQL key/value that provides lower latency and higher throughput than some alternatives
  • Replicates data to multiple nodes
  • Very easy to administer and maintain
  • Data model: key plus zero or more attributes

Lightcloud

  • Great performance even on small clusters with millions of keys
  • Nodes replicated via master-to-master replication.  Hot backups and restores
  • Very small client footprint
  • Built on top of Tokyo Tyrant

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