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DBMS > Amazon Neptune vs. Google Cloud Spanner vs. HugeGraph vs. Microsoft Azure Table Storage vs. OrigoDB

System Properties Comparison Amazon Neptune vs. Google Cloud Spanner vs. HugeGraph vs. Microsoft Azure Table Storage vs. OrigoDB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A fast-speed and highly-scalable Graph DBMSA Wide Column Store for rapid development using massive semi-structured datasetsA fully ACID in-memory object graph database
Primary database modelGraph DBMS
RDF store
Relational DBMSGraph DBMSWide column storeDocument store
Object oriented 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
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­spannergithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­storage/­tablesorigodb.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­spanner/­docshugegraph.apache.org/­docsorigodb.com/­docs
DeveloperAmazonGoogleBaiduMicrosoftRobert Friberg et al
Initial release20172017201820122009 infounder the name LiveDB
Current release0.9
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#
Server operating systemshostedhostedLinux
macOS
Unix
hostedLinux
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesUser defined using .NET types and collections
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.nonononono infocan be achieved using .NET
Secondary indexesnoyesyes infoalso supports composite index and range indexnoyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011nonono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API.NET Client API
HTTP API
LINQ
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Server-side scripts infoStored proceduresnonoasynchronous Gremlin script jobsnoyes
Triggersnonononoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronized
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 with 3 replicas for regional instances.yes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowvia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoedges in graphnodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
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)Users, roles and permissionsAccess rights based on private key authentication or shared access signaturesRole based authorization

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More resources
Amazon NeptuneGoogle Cloud SpannerHugeGraphMicrosoft Azure Table StorageOrigoDB
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