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

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

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Table Storage  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 datasets
Primary database modelGraph DBMS
RDF store
Relational DBMSGraph DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteaws.amazon.com/­neptunecloud.google.com/­spannergithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­spanner/­docshugegraph.apache.org/­docs
DeveloperAmazonGoogleBaiduMicrosoft
Initial release2017201720182012
Current release0.9
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedhostedLinux
macOS
Unix
hosted
Data schemeschema-freeyesyesschema-free
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.nononono
Secondary indexesnoyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011nono
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
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
Server-side scripts infoStored proceduresnonoasynchronous Gremlin script jobsno
Triggersnononono
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 service
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowvia hugegraph-sparkno
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 graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDoptimistic locking
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.noyesno
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 signatures

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More resources
Amazon NeptuneGoogle Cloud SpannerHugeGraphMicrosoft Azure Table Storage
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