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DBMS > Amazon Aurora vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. HEAVY.AI vs. Kinetica

System Properties Comparison Amazon Aurora vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. HEAVY.AI vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGeoSpock  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Spatial and temporal data processing engine for extreme data scaleA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMSSpatial DBMSSpatial 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
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.postgresql.fastware.comgeospock.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.postgresql.fastware.com/­product-manualsdocs.heavy.aidocs.kinetica.com
DeveloperAmazonPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGeoSpockHEAVY.AI, Inc.Kinetica
Initial release201520162012
Current releaseFujitsu Enterprise Postgres 14, January 20222.0, September 20195.10, January 20227.1, August 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava, JavascriptC++ and CUDAC, C++
Server operating systemshostedLinux
Windows
hostedLinuxLinux
Data schemeyesyesyesyesyes
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 indexesyesyestemporal, categoricalnoyes
SQL infoSupport of SQLyesyesANSI SQL for query only (using Presto)yesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functionsnonouser defined functions
Triggersyesyesnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningpartitioning by range, list and by hashAutomatic shardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.yesnoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users can be defined per tablefine grained access rights according to SQL-standardAccess rights for users and roles on table level
More information provided by the system vendor
Amazon AuroraFujitsu Enterprise PostgresGeoSpockHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Amazon AuroraFujitsu Enterprise PostgresGeoSpockHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
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