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DBMS > Amazon Aurora vs. EXASOL vs. Firebase Realtime Database vs. Google Cloud Spanner vs. Splice Machine

System Properties Comparison Amazon Aurora vs. EXASOL vs. Firebase Realtime Database vs. Google Cloud Spanner vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.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.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.exasol.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­spannersplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­resourcesfirebase.google.com/­docs/­databasecloud.google.com/­spanner/­docssplicemachine.com/­how-it-works
DeveloperAmazonExasolGoogle infoacquired by Google 2014GoogleSplice Machine
Initial release20152000201220172014
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedhostedLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesyesnoyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
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
Java
JavaScript
Objective-C
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionslimited functionality with using 'rules'noyes infoJava
TriggersyesyesCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnoyes infousing Google Cloud DataflowYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes 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 dataACIDACIDyesACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard

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More resources
Amazon AuroraEXASOLFirebase Realtime DatabaseGoogle Cloud SpannerSplice Machine
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