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DBMS > Amazon DocumentDB vs. Ehcache vs. Google Cloud Bigtable vs. MarkLogic

System Properties Comparison Amazon DocumentDB vs. Ehcache vs. Google Cloud Bigtable vs. MarkLogic

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA 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 database
Primary database modelDocument storeKey-value storeKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
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
Websiteaws.amazon.com/­documentdbwww.ehcache.orgcloud.google.com/­bigtablewww.progress.com/­marklogic
Technical documentationaws.amazon.com/­documentdb/­resourceswww.ehcache.org/­documentationcloud.google.com/­bigtable/­docswww.progress.com/­marklogic/­documentation
DeveloperTerracotta Inc, owned by Software AGGoogleMarkLogic Corp.
Initial release2019200920152001
Current release3.10.0, March 202211.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VMhostedLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyesnoyes
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.nononoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLnononoyes infoSQL92
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JCachegRPC (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
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
JavaC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononoyes infovia XQuery or JavaScript
Triggersnoyes infoCache Event Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyes infosupports JTA and can work as an XA resourceAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, with Range Indexes
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levels

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More resources
Amazon DocumentDBEhcacheGoogle Cloud BigtableMarkLogic
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