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DBMS > Amazon Neptune vs. Google Cloud Spanner vs. OrigoDB vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Google Cloud Spanner vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  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 fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Object oriented DBMS
Relational 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
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­spannerorigodb.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­spanner/­docsorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGoogleRobert Friberg et alApache Software Foundation
Initial release201720172009 infounder the name LiveDB2014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#Scala
Server operating systemshostedhostedLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011noSQL-like DML and DDL statements
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
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
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.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritydepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoWrite ahead logyes
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)Role based authorizationno

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More resources
Amazon NeptuneGoogle Cloud SpannerOrigoDBSpark SQL
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