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DBMS > FeatureBase vs. Google Cloud Bigtable vs. MarkLogic vs. PouchDB

System Properties Comparison FeatureBase vs. Google Cloud Bigtable vs. MarkLogic vs. PouchDB

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Google'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 CouchDB
Primary database modelRelational DBMSKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#292  Overall
#135  Relational DBMS
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
Websitewww.featurebase.comcloud.google.com/­bigtablewww.progress.com/­marklogicpouchdb.com
Technical documentationdocs.featurebase.comcloud.google.com/­bigtable/­docswww.progress.com/­marklogic/­documentationpouchdb.com/­guides
DeveloperMolecula and Pilosa Open Source ContributorsGoogleMarkLogic Corp.Apache Software Foundation
Initial release2017201520012012
Current release2022, May 202211.0, December 20227.1.1, June 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++JavaScript
Server operating systemsLinux
macOS
hostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeschema-free infoSchema can be enforcedschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.nonoyesno
Secondary indexesnonoyesyes infovia views
SQL infoSupport of SQLSQL queriesnoyes infoSQL92no
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
gRPC (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
Supported programming languagesJava
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptView functions in JavaScript
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal 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
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes
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 Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, with Range Indexesyes
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 levelsno

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More resources
FeatureBaseGoogle Cloud BigtableMarkLogicPouchDB
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