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DBMS > Amazon DocumentDB vs. Ehcache vs. Heroic vs. MarkLogic vs. Teradata Aster

System Properties Comparison Amazon DocumentDB vs. Ehcache vs. Heroic vs. MarkLogic vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEhcache  Xexclude from comparisonHeroic  Xexclude from comparisonMarkLogic  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA widely adopted Java cache with tiered storage optionsTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchOperational and transactional Enterprise NoSQL databasePlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeKey-value storeTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websiteaws.amazon.com/­documentdbwww.ehcache.orggithub.com/­spotify/­heroicwww.marklogic.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.ehcache.org/­documentationspotify.github.io/­heroicdocs.marklogic.com
DeveloperTerracotta Inc, owned by Software AGSpotifyMarkLogic Corp.Teradata
Initial release20192009201420012005
Current release3.10.0, March 202211.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
Linux
Data schemeschema-freeschema-freeschema-freeschema-free infoSchema can be enforcedFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyesyes infoin Aster File Store
Secondary indexesyesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnononoyes infoSQL92yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JCacheHQL (Heroic Query Language, a JSON-based language)
HTTP API
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
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnononoyes infovia XQuery or JavaScriptR packages
Triggersnoyes infoCache Event Listenersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Terracotta ServerShardingShardingSharding
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 Serveryesyesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyes infosupports JTA and can work as an XA resourcenoACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes 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 Indexesno
User concepts infoAccess controlAccess rights for users and rolesnoRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBEhcacheHeroicMarkLogicTeradata Aster
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