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DBMS > Google Cloud Bigtable vs. MarkLogic vs. PouchDB vs. Splice Machine

System Properties Comparison Google Cloud Bigtable vs. MarkLogic vs. PouchDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Operational and transactional Enterprise NoSQL databaseJavaScript 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 modelKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score2.34
Rank#112  Overall
#21  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecloud.google.com/­bigtablewww.marklogic.compouchdb.comsplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.marklogic.compouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperGoogleMarkLogic Corp.Apache Software FoundationSplice Machine
Initial release2015200120122014
Current release11.0, December 20227.1.1, June 20193.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScriptJava
Server operating systemshostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoSchema can be enforcedschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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.noyesno
Secondary indexesnoyesyes infovia viewsyes
SQL infoSupport of SQLnoyes infoSQL92noyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptView functions in JavaScriptyes infoJava
Triggersnoyesyesyes
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 nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesMulti-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 methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionnoACID
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.noyes, with Range Indexesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
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