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DBMS > Amazon DynamoDB vs. Google BigQuery vs. Kinetica vs. Machbase Neo

System Properties Comparison Amazon DynamoDB vs. Google BigQuery vs. Kinetica vs. Machbase Neo

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonKinetica  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudLarge scale data warehouse service with append-only tablesFully vectorized database across both GPUs and CPUsTimeSeries DBMS for AIoT and BigData
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSTime Series 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
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Websiteaws.amazon.com/­dynamodbcloud.google.com/­bigquerywww.kinetica.commachbase.com
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­bigquery/­docsdocs.kinetica.commachbase.com/­dbms
DeveloperAmazonGoogleKineticaMachbase
Initial release2012201020122013
Current release7.1, August 2021V8.0, August 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialcommercialcommercial infofree test version available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C
Server operating systemshostedhostedLinuxLinux
macOS
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptuser defined functionsno
Triggersyes infoby integration with AWS Lambdanoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor
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 integritynonoyesno
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 regionno infoSince BigQuery is designed for querying datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesno
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 infovolatile and lookup table
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users and roles on table levelsimple password-based access control

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More resources
Amazon DynamoDBGoogle BigQueryKineticaMachbase Neo infoFormer name was Infiniflux
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