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DBMS > Amazon Neptune vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. ObjectBox

System Properties Comparison Amazon Neptune vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. ObjectBox

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A 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.Extremely fast embedded database for small devices, IoT and Mobile
Primary database modelGraph DBMS
RDF store
Key-value store
Wide column store
Relational DBMSObject oriented DBMS
Secondary database modelsTime Series 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­bigtablecloud.google.com/­spannerobjectbox.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docsdocs.objectbox.io
DeveloperAmazonGoogleGoogleObjectBox Limited
Initial release2017201520172017
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++
Server operating systemshostedhostedhostedAndroid
iOS
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesnonoyesyes
SQL infoSupport of SQLnonoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary native API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
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.Internal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.online/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoStrict serializable isolationACID
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.nonono
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, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
Amazon NeptuneGoogle Cloud BigtableGoogle Cloud SpannerObjectBox
News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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More resources
Amazon NeptuneGoogle Cloud BigtableGoogle Cloud SpannerObjectBox
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