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DBMS > BigObject vs. HBase vs. PouchDB vs. Realm vs. Splice Machine

System Properties Comparison BigObject vs. HBase vs. PouchDB vs. Realm vs. Splice Machine

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonHBase  Xexclude from comparisonPouchDB  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesWide-column store based on Apache Hadoop and on concepts of BigTableJavaScript DBMS with an API inspired by CouchDBA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedWide column storeDocument storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.28
Rank#115  Overall
#21  Document stores
Score7.60
Rank#52  Overall
#9  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitebigobject.iohbase.apache.orgpouchdb.comrealm.iosplicemachine.com
Technical documentationdocs.bigobject.iohbase.apache.org/­book.htmlpouchdb.com/­guidesrealm.io/­docssplicemachine.com/­how-it-works
DeveloperBigObject, Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationRealm, acquired by MongoDB in May 2019Splice Machine
Initial release20152008201220142014
Current release2.3.4, January 20217.1.1, June 20193.1, March 2021
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache version 2Open SourceOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js)Android
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyesyes
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.nononono
Secondary indexesyesnoyes infovia viewsyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnononoyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuayes infoCoprocessors in JavaView functions in JavaScriptno inforuns within the applications so server-side scripts are unnecessaryyes infoJava
Triggersnoyesyesyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infowith a proxy-based framework, named couchdb-loungenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infoIn-Memory realmyes
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoyesAccess rights for users, groups and roles according to SQL-standard

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More resources
BigObjectHBasePouchDBRealmSplice Machine
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