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DBMS > AllegroGraph vs. Amazon SimpleDB vs. Prometheus vs. Splice Machine

System Properties Comparison AllegroGraph vs. Amazon SimpleDB vs. Prometheus vs. Splice Machine

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAmazon SimpleDB  Xexclude from comparisonPrometheus  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreOpen-source Time Series DBMS and monitoring systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#8  Vector DBMS
Score1.88
Rank#133  Overall
#23  Key-value stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteallegrograph.comaws.amazon.com/­simpledbprometheus.iosplicemachine.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.aws.amazon.com/­simpledbprometheus.io/­docssplicemachine.com/­how-it-works
DeveloperFranz Inc.AmazonSplice Machine
Initial release2004200720152014
Current release8.0, December 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJava
Server operating systemsLinux
OS X
Windows
hostedLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoRDF schemasschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoNumeric data onlyyes
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.no infobulk load of XML files possibleno infoImport of XML data possible
Secondary indexesyesyes infoAll columns are indexed automaticallynoyes
SQL infoSupport of SQLSPARQL is used as query languagenonoyes
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIRESTful HTTP/JSON APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnonoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeswith Federationnone infoSharding must be implemented in the applicationShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoby FederationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency infocan be specified for read operations
noneImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoConcurrent data updates can be detected by the applicationnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
AllegroGraphAmazon SimpleDBPrometheusSplice Machine
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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