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DBMS > Ehcache vs. Google Cloud Bigtable vs. MarkLogic vs. RDFox

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. MarkLogic vs. RDFox

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsGoogle'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 databaseHigh performance knowledge graph and semantic reasoning engine
Primary database modelKey-value storeKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Graph DBMS
RDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
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
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitewww.ehcache.orgcloud.google.com/­bigtablewww.progress.com/­marklogicwww.oxfordsemantic.tech
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docswww.progress.com/­marklogic/­documentationdocs.oxfordsemantic.tech
DeveloperTerracotta Inc, owned by Software AGGoogleMarkLogic Corp.Oxford Semantic Technologies
Initial release2009201520012017
Current release3.10.0, March 202211.0, December 20226.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedyes infoRDF schemas
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes
Secondary indexesnonoyes
SQL infoSupport of SQLnonoyes infoSQL92no
APIs and other access methodsJCachegRPC (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
RESTful HTTP API
SPARQL 1.1
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
Java
Server-side scripts infoStored proceduresnonoyes infovia XQuery or JavaScript
Triggersyes infoCache Event Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zonesyesreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
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 controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsRoles, resources, and access types

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More resources
EhcacheGoogle Cloud BigtableMarkLogicRDFox
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