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DBMS > Amazon Neptune vs. AnzoGraph DB vs. Blazegraph vs. Splice Machine vs. TigerGraph

System Properties Comparison Amazon Neptune vs. AnzoGraph DB vs. Blazegraph vs. Splice Machine vs. TigerGraph

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonBlazegraph  Xexclude from comparisonSplice Machine  Xexclude from comparisonTigerGraph  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 cloudScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
Graph DBMS
RDF store
Relational DBMSGraph 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
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­neptunecambridgesemantics.com/­anzographblazegraph.comsplicemachine.comwww.tigergraph.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwiki.blazegraph.comsplicemachine.com/­how-it-worksdocs.tigergraph.com
DeveloperAmazonCambridge SemanticsBlazegraphSplice Machine
Initial release20172018200620142017
Current release2.3, January 20212.1.5, March 20193.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoextended commercial license availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyes
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
Secondary indexesnonoyesyes
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.SPARQL is used as query languageyesSQL-like query language (GSQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
Native Spark Datasource
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Python
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesyes infoJavayes
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingShared 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.Multi-source replication in MPP-ClusteryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingnoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsno infonot needed in graphsyes infoRelationships in Graphsyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.yesyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and rolesSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles according to SQL-standardRole-based access control

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More resources
Amazon NeptuneAnzoGraph DBBlazegraphSplice MachineTigerGraph
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