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DBMS > Amazon Neptune vs. Blazegraph vs. Lovefield vs. OrigoDB vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Blazegraph vs. Lovefield vs. OrigoDB vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBlazegraph  Xexclude from comparisonLovefield  Xexclude from comparisonOrigoDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionFast, reliable graph database built for the cloudHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Embeddable relational database for web apps written in pure JavaScriptA fully ACID in-memory object graph databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
Relational DBMSDocument store
Object oriented DBMS
Relational 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
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptuneblazegraph.comgoogle.github.io/­lovefieldorigodb.comsplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswiki.blazegraph.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdorigodb.com/­docssplicemachine.com/­how-it-works
DeveloperAmazonBlazegraphGoogleRobert Friberg et alSplice Machine
Initial release2017200620142009 infounder the name LiveDB2014
Current release2.1.5, March 20192.1.12, February 20173.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoextended commercial license availableOpen Source infoApache 2.0Open SourceOpen 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 languageJavaJavaScriptC#Java
Server operating systemshostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesUser defined using .NET types and collectionsyes
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.nonono infocan be achieved using .NET
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSPARQL is used as query languageSQL-like query language infovia JavaScript builder patternnoyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
.NET Client API
HTTP API
LINQ
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
JavaScript.NetC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyesyes infoJava
TriggersnonoUsing read-only observersyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedShared 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.yesnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoRelationships in Graphsyesdepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDByesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Security and Authentication via Web Application Container (Tomcat, Jetty)noRole based authorizationAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneBlazegraphLovefieldOrigoDBSplice Machine
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