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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. InterSystems Caché vs. Prometheus vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. InterSystems Caché vs. Prometheus vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonPrometheus  Xexclude from comparisonYaacomo  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA multi-model DBMS and application serverOpen-source Time Series DBMS and monitoring systemOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeDocument storeKey-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastorewww.intersystems.com/­products/­cacheprometheus.ioyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docsdocs.intersystems.comprometheus.io/­docs
DeveloperGoogleInterSystemsQ2WEB GmbH
Initial release20192008199720152009
Current release2018.1.4, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0commercial
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 languageGo
Server operating systemshostedhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Windows
Android
Linux
Windows
Data schemeschema-freeschema-freedepending on used data modelyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesNumeric data onlyyes
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.nonoyesno infoImport of XML data possibleno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesnoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyesno
TriggersnoCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication using PaxosSource-replica replicationyes infoby FederationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesnofine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBGoogle Cloud DatastoreInterSystems CachéPrometheusYaacomo
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