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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. OpenEdge vs. SAP SQL Anywhere vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. OpenEdge vs. SAP SQL Anywhere vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonOpenEdge  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudApplication development environment with integrated database management systemRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score4.25
Rank#79  Overall
#43  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptunewww.progress.com/­openedgewww.sap.com/­products/­technology-platform/­sql-anywhere.htmlspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcesdocumentation.progress.com/­output/­ua/­OpenEdge_latesthelp.sap.com/­docs/­SAP_SQL_Anywherespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonProgress Software CorporationSAP infoformerly SybaseApache Software Foundation
Initial release20192017198419922014
Current releaseOpenEdge 12.2, March 202017, July 20153.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemshostedhostedAIX
HP-UX
Linux
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
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.nonoyesyesno
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLnonoyes infoclose to SQL 92yesSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
ADO.NET
HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Progress proprietary ABL (Advanced Business Language)C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesyes, in C/C++, Java, .Net or Perlno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning infosince Version 11.4noneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Source-replica replicationSource-replica replication infoDatabase mirroringnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in graphsyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users and groupsfine grained access rights according to SQL-standardno

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More resources
Amazon DocumentDBAmazon NeptuneOpenEdgeSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
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