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DBMS > Amazon Neptune vs. Greenplum vs. LevelDB vs. RDF4J vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Greenplum vs. LevelDB vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGreenplum  Xexclude from comparisonLevelDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeRDF storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunegreenplum.orggithub.com/­google/­leveldbrdf4j.orgsplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.greenplum.orggithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperAmazonPivotal Software Inc.GoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20172005201120042014
Current release7.0.0, September 20231.23, February 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSDOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemshostedLinuxIllumos
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes infoRDF Schemasyes
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 infosince Version 4.2no
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoyesnonoyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
Java
Perl
Python
R
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyesyes infoJava
Triggersnoyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenoneShared Nothhing Auto-Sharding, Columnar 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.Source-replica replicationnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infowith automatic compression on writesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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-standardnonoAccess rights for users, groups and roles according to SQL-standard

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Amazon NeptuneGreenplumLevelDBRDF4J infoformerly known as SesameSplice Machine
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