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DBMS > Amazon Neptune vs. EDB Postgres vs. Oracle Berkeley DB vs. Spark SQL vs. Yaacomo

System Properties Comparison Amazon Neptune vs. EDB Postgres vs. Oracle Berkeley DB vs. Spark SQL vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEDB Postgres  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, reliable graph database built for the cloudThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Widely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score1.90
Rank#135  Overall
#63  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/­neptunewww.enterprisedb.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlyaacomo.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.enterprisedb.com/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonEnterpriseDBOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationQ2WEB GmbH
Initial release20172005199420142009
Current release14, December 202118.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentsOpen 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

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Implementation languageCC, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemshostedLinux
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyesschema-freeyesyes
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.noyes infospecific XML-type available, but no XML query functionality.yes infoonly with the Berkeley DB XML editionnono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.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 proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersnoyesyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoby hash, list or rangenoneyes, utilizing Spark Corehorizontal partitioning
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.Multi-source replicationSource-replica replicationnoneSource-replica replication
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 graphsyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneEDB PostgresOracle Berkeley DBSpark SQLYaacomo
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