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DBMS > HBase vs. Kinetica vs. PouchDB vs. Splice Machine

System Properties Comparison HBase vs. Kinetica vs. PouchDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonKinetica  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUsJavaScript DBMS with an API inspired by CouchDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelWide column storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitehbase.apache.orgwww.kinetica.compouchdb.comsplicemachine.com
Technical documentationhbase.apache.org/­book.htmldocs.kinetica.compouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetKineticaApache Software FoundationSplice Machine
Initial release2008201220122014
Current release2.3.4, January 20217.1, August 20217.1.1, June 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen SourceOpen 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 languageJavaC, C++JavaScriptJava
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linuxserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
Data schemeschema-free, schema definition possibleyesschema-freeyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesnoyes
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 indexesnoyesyes infovia viewsyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoCoprocessors in Javauser defined functionsView functions in JavaScriptyes infoJava
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)nonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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HBaseKineticaPouchDBSplice Machine
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