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DBMS > Amazon DynamoDB vs. Badger vs. Databricks vs. PostgreSQL

System Properties Comparison Amazon DynamoDB vs. Badger vs. Databricks vs. PostgreSQL

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The 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.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument store
Key-value store
Key-value storeDocument store
Relational DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument 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
Score70.06
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score0.14
Rank#328  Overall
#48  Key-value stores
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score644.36
Rank#4  Overall
#4  Relational DBMS
Websiteaws.amazon.com/­dynamodbgithub.com/­dgraph-io/­badgerwww.databricks.comwww.postgresql.org
Technical documentationdocs.aws.amazon.com/­dynamodbgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comwww.postgresql.org/­docs
DeveloperAmazonDGraph LabsDatabricksPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2012201720131989 info1989: Postgres, 1996: PostgreSQL
Current release16.4, August 2024
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache 2.0commercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageGoC
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesnoyes
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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonowith Databricks SQLyes infostandard with numerous extensions
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
GoPython
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnonouser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyes infoby integration with AWS Lambdanoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesSource-replica replication infoother methods possible by using 3rd party extensions
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
noneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
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 regionnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nofine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon DynamoDBBadgerDatabricksPostgreSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DynamoDBBadgerDatabricksPostgreSQL
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