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DBMS > Amazon Neptune vs. Microsoft Azure Table Storage vs. OpenEdge vs. Oracle Berkeley DB vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Microsoft Azure Table Storage vs. OpenEdge vs. Oracle Berkeley DB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Wide column storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptuneazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocumentation.progress.com/­output/­ua/­OpenEdge_latestdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonMicrosoftProgress Software CorporationOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release20172012198419942014
Current releaseOpenEdge 12.2, March 202018.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infocommercial license availableOpen 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 languageC, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemshostedhostedAIX
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonoyesyes infoonly with the Berkeley DB XML editionno
Secondary indexesnonoyesyesno
SQL infoSupport of SQLnonoyes infoclose to SQL 92yes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIJDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language).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
Server-side scripts infoStored proceduresnonoyesnono
Triggersnonoyesyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4noneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesUsers and groupsnono

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More resources
Amazon NeptuneMicrosoft Azure Table StorageOpenEdgeOracle Berkeley DBSpark SQL
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