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DBMS > BoltDB vs. HBase vs. Riak KV vs. Splice Machine

System Properties Comparison BoltDB vs. HBase vs. Riak KV vs. Splice Machine

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonHBase  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Wide-column store based on Apache Hadoop and on concepts of BigTableDistributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeWide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­boltdb/­bolthbase.apache.orgsplicemachine.com
Technical documentationhbase.apache.org/­book.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetOpenSource, formerly Basho TechnologiesSplice Machine
Initial release2013200820092014
Current release2.3.4, January 20213.2.0, December 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache version 2Open Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaErlangJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesnonorestrictedyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoC
C#
C++
Groovy
Java
PHP
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavaErlangyes infoJava
Triggersnoyesyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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More resources
BoltDBHBaseRiak KVSplice Machine
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