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DBMS > Amazon Neptune vs. Cubrid vs. Datomic vs. Google Cloud Bigtable

System Properties Comparison Amazon Neptune vs. Cubrid vs. Datomic vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCubrid  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­neptunecubrid.com (korean)
cubrid.org (english)
www.datomic.comcloud.google.com/­bigtable
Technical documentationaws.amazon.com/­neptune/­developer-resourcescubrid.org/­manualsdocs.datomic.comcloud.google.com/­bigtable/­docs
DeveloperAmazonCUBRID Corporation, CUBRID FoundationCognitectGoogle
Initial release2017200820122015
Current release11.0, January 20211.0.6735, June 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaJava, Clojure
Server operating systemshostedLinux
Windows
All OS with a Java VMhosted
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesnoyesyesno
SQL infoSupport of SQLnoyesnono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
OLE DB
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Clojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes infoTransaction Functionsno
TriggersnoyesBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesnonenonenone infoBut extensive use of caching in the application peersSharding
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.Source-replica replicationnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon NeptuneCubridDatomicGoogle Cloud Bigtable
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