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DBMS > Amazon Neptune vs. BigObject vs. Google BigQuery vs. Linter

System Properties Comparison Amazon Neptune vs. BigObject vs. Google BigQuery vs. Linter

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for real-time computations and queriesLarge scale data warehouse service with append-only tablesRDBMS for high security requirements
Primary database modelGraph DBMS
RDF store
Relational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMS
Secondary database modelsSpatial 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websiteaws.amazon.com/­neptunebigobject.iocloud.google.com/­bigquerylinter.ru
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.bigobject.iocloud.google.com/­bigquery/­docs
DeveloperAmazonBigObject, Inc.Googlerelex.ru
Initial release2017201520101990
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
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.nononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
fluentd
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresnoLuauser defined functions infoin JavaScriptyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonenonenone
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.noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoautomatically between fact table and dimension tablesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoSince BigQuery is designed for querying dataACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.yesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Amazon NeptuneBigObjectGoogle BigQueryLinter
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