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DBMS > Amazon DynamoDB vs. GBase vs. Kinetica vs. PostgreSQL vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. GBase vs. Kinetica vs. PostgreSQL vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGBase  Xexclude from comparisonKinetica  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Fully vectorized database across both GPUs and CPUsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­dynamodbwww.gbase.cnwww.kinetica.comwww.postgresql.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.kinetica.comwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGeneral Data Technology Co., Ltd.KineticaPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release2012200420121989 info1989: Postgres, 1996: PostgreSQL2014
Current releaseGBase 8a, GBase 8s, GBase 8c7.1, August 202116.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialcommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonC, C++CScala
Server operating systemshostedLinuxLinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
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.yesnoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnoStandard with numerous extensionsSQL-like DML and DDL statementsyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
C API
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyes infoby integration with AWS Lambdayesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDnoACIDno
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.yes infoGPU vRAM or System RAMnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Amazon DynamoDBGBaseKineticaPostgreSQLSpark SQL
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