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DBMS > Amazon DocumentDB vs. MarkLogic vs. Oracle Berkeley DB vs. Spark SQL vs. Teradata Aster

System Properties Comparison Amazon DocumentDB vs. MarkLogic vs. Oracle Berkeley DB vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  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 serviceOperational and transactional Enterprise NoSQL databaseWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.progress.com/­marklogicwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourceswww.progress.com/­marklogic/­documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMarkLogic Corp.Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationTeradata
Initial release20192001199420142005
Current release11.0, December 202218.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infocommercial license availableOpen Source infoApache 2.0commercial
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 languageC++C, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemshostedLinux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-free infoSchema can be enforcedschema-freeyesFlexible 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 dateyesyesnoyesyes
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.noyesyes infoonly with the Berkeley DB XML editionnoyes infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnoyes infoSQL92yes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)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
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptnonoR packages
Triggersnoyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesSource-replica replicationnoneyes 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)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 operationsACID infocan act as a resource manager in an XA/JTA transactionACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyesnono
User concepts infoAccess controlAccess rights for users and rolesRole-based access control at the document and subdocument levelsnonofine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBMarkLogicOracle Berkeley DBSpark SQLTeradata Aster
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