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DBMS > Amazon Aurora vs. EXASOL vs. Google Cloud Datastore vs. Kinetica vs. Rockset

System Properties Comparison Amazon Aurora vs. EXASOL vs. Google Cloud Datastore vs. Kinetica vs. Rockset

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSDocument store
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websiteaws.amazon.com/­rds/­aurorawww.exasol.comcloud.google.com/­datastorewww.kinetica.comrockset.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­resourcescloud.google.com/­datastore/­docsdocs.kinetica.comdocs.rockset.com
DeveloperAmazonExasolGoogleKineticaRockset
Initial release20152000200820122019
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++
Server operating systemshostedhostedLinuxhosted
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesdynamic typing
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.yesnononono infoingestion from XML files supported
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyesyesSQL-like query language (GQL)SQL-like DML and DDL statementsRead-only SQL queries, including JOINs
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP REST
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functionsusing Google App Engineuser defined functionsno
TriggersyesyesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflownono
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 or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelAccess rights for users and organizations can be defined via Rockset console

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More resources
Amazon AuroraEXASOLGoogle Cloud DatastoreKineticaRockset
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