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DBMS > Cloudant vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB vs. TigerGraph

System Properties Comparison Cloudant vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB vs. TigerGraph

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Editorial information provided by DB-Engines
NameCloudant  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionDatabase as a Service offering based on Apache CouchDBAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGlobally distributed, horizontally scalable, multi-model database serviceA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeDocument storeDocument store
Graph DBMS
Key-value store
Wide column store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.45
Rank#82  Overall
#15  Document stores
Score4.81
Rank#67  Overall
#12  Document stores
Score31.51
Rank#24  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score1.00
Rank#151  Overall
#11  Graph DBMS
Websitecloudant.comcloud.google.com/­datastoreazure.microsoft.com/­services/­cosmos-dbwww.tigergraph.com
Technical documentationdocs.cloudant.comcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­cosmos-dbdocs.tigergraph.com
DeveloperIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014GoogleMicrosoft
Initial release2010200820142017
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++
Server operating systemshostedhostedhostedLinux
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details hereyes infoJSON typesyes
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 indexesyesyesyes infoAll properties auto-indexed by default
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Java
JavaScript
Objective-C
PHP
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C++
Java
Server-side scripts infoStored proceduresView functions (Map-Reduce) in JavaScriptusing Google App EngineJavaScriptyes
TriggersyesCallbacks using the Google Apps EngineJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication
Master-slave replication
Multi-Master replication using Paxosyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowwith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*yes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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.Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsMulti-item ACID transactions with snapshot isolation within a partitionACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic lockingyesyesyes
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.nonono
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelRole-based access control
More information provided by the system vendor
CloudantGoogle Cloud DatastoreMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBTigerGraph
Specific characteristicsTigerGraph is a native graph database, with massively parallel processing and fully...
» more
Competitive advantagesTigerGraph is the fastest and most scalable graph platform, powered by a native parallel...
» more
Typical application scenariosAnti Money Laundering Real-Time Fraud Detection Customer 360 Real-Time Personalized...
» more
Key customersTigerGraph’s proven technology supports applications such as fraud detection, customer...
» more
Market metricsTigerGraph is 2x to more than 8000x faster at graph traversal and query response...
» more
Licensing and pricing modelsNEW: TIGERGRAPH CLOUD - Fully managed Graph Database as a Service. Hourly pricing...
» more

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More resources
CloudantGoogle Cloud DatastoreMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBTigerGraph
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