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DBMS > Amazon DynamoDB vs. Google BigQuery vs. Memcached vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. Google BigQuery vs. Memcached vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMemcached  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudLarge scale data warehouse service with append-only tablesIn-memory key-value store, originally intended for cachingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeRelational DBMS
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
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­dynamodbcloud.google.com/­bigquerywww.memcached.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­bigquery/­docsgithub.com/­memcached/­memcached/­wikisplicemachine.com/­how-it-works
DeveloperAmazonGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSplice Machine
Initial release2012201020032014
Current release1.6.27, May 20243.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoBSD licenseOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemshostedhostedFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-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.no
Secondary indexesyesnonoyes
SQL infoSupport of SQLnoyesnoyes
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptnoyes infoJava
Triggersyes infoby integration with AWS Lambdanonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoRepcached, a Memcached patch, provides this functionallityMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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)yes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBGoogle BigQueryMemcachedSplice Machine
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