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DBMS > Amazon Neptune vs. Google Cloud Datastore vs. Oracle NoSQL vs. TigerGraph

System Properties Comparison Amazon Neptune vs. Google Cloud Datastore vs. Oracle NoSQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelGraph DBMS
RDF store
Document storeDocument store
Key-value store
Relational DBMS
Graph 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
Score4.36
Rank#72  Overall
#12  Document stores
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­datastorewww.oracle.com/­database/­nosql/­technologies/­nosqlwww.tigergraph.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­datastore/­docsdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmldocs.tigergraph.com
DeveloperAmazonGoogleOracle
Initial release2017200820112017
Current release23.3, December 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedhostedLinux
Solaris SPARC/x86
Linux
Data schemeschema-freeschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
Typing infopredefined data types such as float or dateyesyes, details hereoptionalyes
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.nononono
Secondary indexesnoyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresnousing Google App Enginenoyes
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
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 using PaxosElectable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowwith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsconfigurable infoACID within a storage node (=shard)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infooff heap cacheno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesRole-based access control

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More resources
Amazon NeptuneGoogle Cloud DatastoreOracle NoSQLTigerGraph
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