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DBMS > Amazon Neptune vs. Datomic vs. Splice Machine vs. TigerGraph

System Properties Comparison Amazon Neptune vs. Datomic vs. Splice Machine vs. TigerGraph

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatomic  Xexclude from comparisonSplice Machine  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOpen-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
Relational DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score1.44
Rank#152  Overall
#14  Graph DBMS
Websiteaws.amazon.com/­neptunewww.datomic.comsplicemachine.comwww.tigergraph.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.datomic.comsplicemachine.com/­how-it-worksdocs.tigergraph.com
DeveloperAmazonCognitectSplice Machine
Initial release2017201220142017
Current release1.0.7180, July 20243.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLnonoyesSQL-like query language (GSQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes infoJavayes
TriggersnoBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShared 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.none infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlAccess 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-standardRole-based access control

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More resources
Amazon NeptuneDatomicSplice MachineTigerGraph
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