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DBMS > Amazon DynamoDB vs. Databricks vs. Kinetica vs. Memcached vs. Valentina Server

System Properties Comparison Amazon DynamoDB vs. Databricks vs. Kinetica vs. Memcached vs. Valentina Server

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonMemcached  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudThe 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.Fully vectorized database across both GPUs and CPUsIn-memory key-value store, originally intended for cachingObject-relational database and reports server
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteaws.amazon.com/­dynamodbwww.databricks.comwww.kinetica.comwww.memcached.orgwww.valentina-db.net
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.databricks.comdocs.kinetica.comgithub.com/­memcached/­memcached/­wikivalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAmazonDatabricksKineticaDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalParadigma Software
Initial release20122013201220031999
Current release7.1, August 20211.6.25, March 20245.7.5
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialcommercialOpen Source infoBSD licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C
Server operating systemshostedhostedLinuxFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnowith Databricks SQLSQL-like DML and DDL statementsnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Proprietary protocolODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnouser defined functions and aggregatesuser defined functionsnoyes
Triggersyes infoby integration with AWS Lambdayes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replicationnone infoRepcached, a Memcached patch, provides this functionallity
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
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 configuration
Foreign keys infoReferential integritynoyesnoyes
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 regionACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and roles on table levelyes infousing SASL (Simple Authentication and Security Layer) protocolfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon DynamoDBDatabricksKineticaMemcachedValentina Server
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DynamoDBDatabricksKineticaMemcachedValentina Server
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