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DBMS > Amazon DynamoDB vs. atoti vs. Google Cloud Datastore vs. searchxml vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. atoti vs. Google Cloud Datastore vs. searchxml vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonatoti  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonsearchxml  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for structured and unstructured content wrapped with an application serverOpen-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
Object oriented DBMSDocument storeNative XML DBMS
Search engine
Relational 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
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­dynamodbatoti.iocloud.google.com/­datastorewww.searchxml.net/­category/­productssplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.atoti.iocloud.google.com/­datastore/­docswww.searchxml.net/­support/­handoutssplicemachine.com/­how-it-works
DeveloperAmazonActiveViamGoogleinformationpartners gmbhSplice Machine
Initial release2012200820152014
Current release1.03.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercial infofree versions availablecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemshostedhostedWindowsLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoMultidimensional Expressions (MDX)SQL-like query language (GQL)noyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infomost other programming languages supported via APIsC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoPythonusing Google App Engineyes infoon the application serveryes infoJava
Triggersyes infoby integration with AWS LambdaCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes infosychronisation to multiple collectionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infousing Google Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
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 regionACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsmultiple readers, single writerACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes, multi-version concurrency control (MVCC)
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.yesnonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Domain, group and role-based access control at the document level and for application servicesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBatotiGoogle Cloud DatastoresearchxmlSplice Machine
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