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DBMS > Amazon Aurora vs. Datomic vs. Google Cloud Datastore vs. LeanXcale

System Properties Comparison Amazon Aurora vs. Datomic vs. Google Cloud Datastore vs. LeanXcale

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLeanXcale  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 durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Relational 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.datomic.comcloud.google.com/­datastorewww.leanxcale.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperAmazonCognitectGoogleLeanXcale
Initial release2015201220082015
Current release1.0.6735, June 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialcommercial
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, Clojure
Server operating systemshostedAll OS with a Java VMhosted
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details here
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.yesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)yes infothrough Apache Derby
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Scala
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsusing Google App Engine
TriggersyesBy using transaction functionsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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
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)

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More resources
Amazon AuroraDatomicGoogle Cloud DatastoreLeanXcale
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