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DBMS > Amazon Aurora vs. Datomic vs. OrigoDB vs. Vertica

System Properties Comparison Amazon Aurora vs. Datomic vs. OrigoDB vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatomic  Xexclude from comparisonOrigoDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 durabilityA fully ACID in-memory object graph databaseCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSDocument store
Object oriented DBMS
Relational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
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
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.datomic.comorigodb.comwww.vertica.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.datomic.comorigodb.com/­docsvertica.com/­documentation
DeveloperAmazonCognitectRobert Friberg et alOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520122009 infounder the name LiveDB2005
Current release1.0.6735, June 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC#C++
Server operating systemshostedAll OS with a Java VMLinux
Windows
Linux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP API.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
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
.NetC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsyesyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesBy using transaction functionsyes infoDomain Eventsyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peershorizontal partitioning infoclient side managed; servers are not synchronizedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnodepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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)yes infoWrite ahead logyes
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 developmentyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoRole based authorizationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon AuroraDatomicOrigoDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Amazon AuroraDatomicOrigoDBVertica infoOpenText™ Vertica™
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