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DBMS > Amazon Aurora vs. Databricks vs. Datomic vs. Faircom EDGE vs. OrigoDB

System Properties Comparison Amazon Aurora vs. Databricks vs. Datomic vs. Faircom EDGE vs. OrigoDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA fully ACID in-memory object graph database
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Document store
Object oriented 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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Websiteaws.amazon.com/­rds/­aurorawww.databricks.comwww.datomic.comwww.faircom.com/­products/­faircom-edgeorigodb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databricks.comdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlorigodb.com/­docs
DeveloperAmazonDatabricksCognitectFairCom CorporationRobert Friberg et al
Initial release20152013201219792009 infounder the name LiveDB
Current release1.0.6735, June 2023V3, October 2020
License infoCommercial or Open Sourcecommercialcommercialcommercial infolimited edition freecommercial infoRestricted, free version availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureANSI C, C++C#
Server operating systemshostedhostedAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL TypesUser 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.yesyesnoyesno infocan be achieved using .NET
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyeswith Databricks SQLnoyes infoANSI SQL queriesno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.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
Python
R
Scala
Clojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyes infoTransaction Functionsyes info.Net, JavaScript, C/C++yes
TriggersyesBy using transaction functionsyesyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnoyes infowhen using SQLdepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyes 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.yesnoyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role based authorization
More information provided by the system vendor
Amazon AuroraDatabricksDatomicFaircom EDGE infoformerly c-treeEDGEOrigoDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon AuroraDatabricksDatomicFaircom EDGE infoformerly c-treeEDGEOrigoDB
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