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DBMS > Amazon Aurora vs. Datomic vs. Google Cloud Bigtable vs. OrigoDB

System Properties Comparison Amazon Aurora vs. Datomic vs. Google Cloud Bigtable vs. OrigoDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonDatomic 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.A fully ACID in-memory object graph database
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Document store
Object oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websiteaws.amazon.com/­rds/­aurorawww.datomic.comcloud.google.com/­bigtableorigodb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.datomic.comcloud.google.com/­bigtable/­docsorigodb.com/­docs
DeveloperAmazonCognitectGoogleRobert Friberg et al
Initial release2015201220152009 infounder the name LiveDB
Current release1.0.6735, June 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source
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 languageJava, ClojureC#
Server operating systemshostedAll OS with a Java VMhostedLinux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoUser defined using .NET types and collections
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.yesnonono infocan be achieved using .NET
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesnonono
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
HTTP API
LINQ
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Clojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsnoyes
TriggersyesBy using transaction functionsnoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnonodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based authorization

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More resources
Amazon AuroraDatomicGoogle Cloud BigtableOrigoDB
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